diff --git a/.gitattributes b/.gitattributes
index 4953df946f829c76f6c5fa373edd63150f9f83d9..42a581ded5fee5857526f92cf5f4c6422de6baa3 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -172,3 +172,6 @@ backend/uploads/generated/5b6f11b554f74c5486ce33e390f8c75d.png filter=lfs diff=l
 backend/uploads/generated/836b20819d49430a9fc94c02e8e07885.png filter=lfs diff=lfs merge=lfs -text
 backend/uploads/generated/d664c83e3b614760834cdaad28769340.png filter=lfs diff=lfs merge=lfs -text
 backend/uploads/generated/dbd083972cf5430998885a9f7c36ac0a.png filter=lfs diff=lfs merge=lfs -text
+backend/texturas/Texture_wpc_deck/DECK_gris.png filter=lfs diff=lfs merge=lfs -text
+backend/texturas/Texture_wpc_deck/DECK_madera_oscuro.png filter=lfs diff=lfs merge=lfs -text
+backend/texturas/Texture_wpc_deck/DECK_madera.png filter=lfs diff=lfs merge=lfs -text
diff --git a/backend/.dockerignore b/backend/.dockerignore
index ecd53e19e5e0b70620f5a6062e6a06d0ee0527ad..c297828decf7aeab21c8a3236076f0b13a39a483 100644
--- a/backend/.dockerignore
+++ b/backend/.dockerignore
@@ -1,6 +1,6 @@
-.venv/
-__pycache__/
-*.pyc
-uploads/
-frontend/node_modules/
-frontend/dist/
+.venv/
+__pycache__/
+*.pyc
+uploads/
+frontend/node_modules/
+frontend/dist/
diff --git a/backend/.gitignore b/backend/.gitignore
index 64cf336708fa1a0223486f53b0c85792587aea65..cd07a5fd0062816e401518cdd239fa21ec66d166 100644
--- a/backend/.gitignore
+++ b/backend/.gitignore
@@ -1,33 +1,33 @@
-# Python
-__pycache__/
-*.py[cod]
-*.pyo
-*.pyd
-*.cover
-*.egg-info/
-.eggs/
-*.egg
-pip-log.txt
-pip-delete-this-directory.txt
-htmlcov/
-.tox/
-.coverage
-.coverage.*
-.cache
-.pytest_cache/
-.pytest_cache
-.env
-venv/
-ENV/
-env/
-*.env
-
-# VS Code
-.vscode/
-
-# Python virtual environment
-.venv/
-
-# OS files
-.DS_Store
-Thumbs.db
+# Python
+__pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+*.cover
+*.egg-info/
+.eggs/
+*.egg
+pip-log.txt
+pip-delete-this-directory.txt
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+.pytest_cache/
+.pytest_cache
+.env
+venv/
+ENV/
+env/
+*.env
+
+# VS Code
+.vscode/
+
+# Python virtual environment
+.venv/
+
+# OS files
+.DS_Store
+Thumbs.db
diff --git a/backend/Dockerfile b/backend/Dockerfile
index 47326e62ba843d2cf67b2380c965ca5d6661d6ba..f03669bb72d922dca6fdfb060378526853ff51ee 100644
--- a/backend/Dockerfile
+++ b/backend/Dockerfile
@@ -1,29 +1,29 @@
-FROM python:3.12-slim
-
-ENV PYTHONDONTWRITEBYTECODE=1 \
-    PYTHONUNBUFFERED=1 \
-    PIP_NO_CACHE_DIR=1 \
-    PORT=8000 \
-    HF_HUB_DISABLE_PROGRESS_BARS=0
-
-WORKDIR /app
-
-RUN apt-get update \
-    && apt-get install -y --no-install-recommends \
-        git libglib2.0-0 libsm6 libxrender1 libxext6 libx11-6 libxcb1 libgl1 libgl1-mesa-dri \
-    && rm -rf /var/lib/apt/lists/*
-
-COPY requirements.txt ./
-RUN python -m pip install --upgrade pip \
-    && python -m pip install -r requirements.txt
-
-COPY . ./
-
-RUN chmod +x entrypoint.sh
-
-# /app/models is mounted as a volume so the SAM2 checkpoint persists across restarts
-VOLUME ["/app/models"]
-
-EXPOSE 8000
-
-ENTRYPOINT ["./entrypoint.sh"]
+FROM python:3.12-slim
+
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1 \
+    PIP_NO_CACHE_DIR=1 \
+    PORT=8000 \
+    HF_HUB_DISABLE_PROGRESS_BARS=0
+
+WORKDIR /app
+
+RUN apt-get update \
+    && apt-get install -y --no-install-recommends \
+        git libglib2.0-0 libsm6 libxrender1 libxext6 libx11-6 libxcb1 libgl1 libgl1-mesa-dri \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt ./
+RUN python -m pip install --upgrade pip \
+    && python -m pip install -r requirements.txt
+
+COPY . ./
+
+RUN chmod +x entrypoint.sh
+
+# /app/models is mounted as a volume so the SAM2 checkpoint persists across restarts
+VOLUME ["/app/models"]
+
+EXPOSE 8000
+
+ENTRYPOINT ["./entrypoint.sh"]
diff --git a/backend/README.md b/backend/README.md
index 652e52f20ba339698c86cdb4c991361e9454b709..7d5694407e1b06269515082549b62c0f76a2d740 100644
--- a/backend/README.md
+++ b/backend/README.md
@@ -1,192 +1,192 @@
-# Backend - PoC SaaS Iframe
-
-Este documento explica cómo funciona el backend del proyecto, qué endpoints ofrece y cómo se integra con el frontend React.
-
-## Propósito
-
-El backend sirve como:
-
-- API para autenticación con token, configuración y gestión de sesiones.
-- servidor de archivos estáticos para el build de React en producción (`frontend/dist`).
-- punto de entrada de administración, preview y experiencia embebida.
-- watcher opcional que reconstruye el frontend cuando cambian los archivos fuente.
-
-## Estructura principal
-
-- `main.py` - servidor FastAPI principal.
-- `requirements.txt` - dependencias Python.
-- `run_server.bat` - helper para arrancar el backend con el virtual environment local.
-- `.venv/` - entorno virtual Python del backend.
-- `home.html`, `admin.html`, `preview.html` - páginas de apoyo.
-
-## Cómo ejecutar
-
-### Activar entorno virtual
-
-En Windows CMD:
-
-```cmd
-cd /d C:\Users\alane\OneDrive\Escritorio\Prueba-PoC\backend
-.venv\Scripts\activate
-```
-
-En PowerShell:
-
-```powershell
-cd C:\Users\alane\OneDrive\Escritorio\Prueba-PoC\backend
-.\.venv\Scripts\Activate.ps1
-```
-
-### Instalar dependencias
-
-```cmd
-pip install -r requirements.txt
-```
-
-### Ejecutar servidor
-
-```cmd
-python -m uvicorn main:app --reload --host 0.0.0.0 --port 8000
-```
-
-O usar el helper:
-
-```cmd
-run_server.bat
-```
-
-## Comportamiento de producción
-
-En producción, el backend sirve el build de React desde `frontend/dist` en la ruta `/app`.
-
-- El HTML principal se carga en `/app`
-- Los assets de Vite se sirven en `/app/assets/...`
-- Si `frontend/dist/index.html` no existe, se devuelve un mensaje de error claro.
-
-## Endpoints principales
-
-### Páginas y visualización
-
-- `GET /` - `home.html`
-- `GET /preview` - `preview.html`
-- `GET /admin` - `admin.html`
-- `GET /app` - React app estática servida desde `frontend/dist`
-- `GET /widget.js` - script JS que inyecta un iframe con el visualizador
-- `GET /health` - estado del backend y si el frontend build está listo
-
-### API de integración
-
-- `POST /api/token` - genera un token temporal para `client_id`
-- `GET /config` - devuelve datos del cliente según `client_id` o `token`
-- `POST /session/start` - marca la sesión como activa
-- `GET /api/keys` - lista clientes registrados
-- `POST /api/generate-key` - genera una nueva API key de cliente
-- `GET /api/active-sessions` - muestra sesiones activas actuales
-
-## Lógica de token y cliente
-
-### Validación de token
-
-- Los tokens se guardan en memoria en `TOKENS`
-- Cada token vence después de `TOKEN_TTL` segundos
-- Si el token ha expirado, se devuelve `401`
-
-### Configuración del cliente
-
-- El diccionario `CLIENTS` contiene los clientes registrados por defecto
-- Cada cliente tiene `nombre`, `color_primario` y `created_at`
-- `POST /api/generate-key` agrega un nuevo cliente a `CLIENTS`
-
-## Seguridad y headers importantes
-
-El backend habilita:
-
-- CORS abierto (`allow_origins=["*"]`) para facilitar el desarrollo
-- Eliminación de `x-frame-options` en todas las respuestas
-- Agrega `Content-Security-Policy: frame-ancestors *` para permitir iframes
-
-## Watcher automático de frontend
-
-El backend también incluye un watcher que observa cambios en el frontend y ejecuta `npm run build` automáticamente.
-
-### Qué archivos vigila
-
-- `frontend/src/**/*.{ts,tsx,js,jsx,css,json,html}`
-- `frontend/vite.config.ts`
-- `frontend/package.json`
-- `frontend/tsconfig.json`
-
-### Cómo funciona
-
-- Si el backend está ejecutándose, el watcher corre en un hilo daemon.
-- Cuando detecta cambios, ejecuta `npm run build` en `frontend/`.
-- El resultado actualiza `frontend/dist` para que `/app` sirva la versión nueva.
-
-### Requisitos del watcher
-
-- Necesitas tener `npm` instalado y accesible desde el PATH.
-- El backend debe arrancarse desde el directorio raíz del proyecto.
-
-## Desarrollo y producción
-
-### Desarrollo
-
-- Para trabajar en el frontend con hot reload, usa el dev server de Vite:
-
-```cmd
-cd /d C:\Users\alane\OneDrive\Escritorio\Prueba-PoC\frontend
-npm run dev
-```
-
-- Abre `http://localhost:5173/app?token=...`
-
-### Producción / backend
-
-- Para servir el frontend estático desde el backend:
-
-```cmd
-cd /d C:\Users\alane\OneDrive\Escritorio\Prueba-PoC\frontend
-npm run build
-```
-
-- Luego carga `http://localhost:8000/app?token=...`
-
-## Integración con hyper-ferreteria
-
-Este backend puede montar la lógica de `hyper-ferreteria` en un prefijo alterno para evitar conflictos de rutas.
-
-- Se carga si la carpeta `../hyper-ferreteria` existe junto al directorio `Prueba-PoC`.
-- La integración queda disponible en `http://localhost:8000/hf`.
-- Las rutas internas de `hyper-ferreteria` se exponen como:
-  - `http://localhost:8000/hf/upload_async`
-  - `http://localhost:8000/hf/segment_guided`
-  - `http://localhost:8000/hf/analyze_scene`
-  - `http://localhost:8000/hf/apply_texture`
-  - `http://localhost:8000/hf/textures`
-  - `http://localhost:8000/hf/image/{filename}`
-  - `http://localhost:8000/hf/masks/{filename}`
-  - `http://localhost:8000/hf/ai/{filename}`
-  - y otras rutas de `hyper-ferreteria` con el prefijo `/hf`
-
-## Docker
-
-Se añadió soporte Docker al backend con un `Dockerfile` y `.dockerignore`.
-
-- El contenedor expone el puerto `8000`.
-- El servicio arranca con `uvicorn main:app --host 0.0.0.0 --port 8000`.
-- El `requirements.txt` del backend fue ampliado para incluir las dependencias de `hyper-ferreteria`.
-
-Para construir y correr:
-
-```cmd
-cd /d C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend
-docker build -t prueba-poc-backend .
-docker run -p 8000:8000 prueba-poc-backend
-```
-
-## Notas para nuevos desarrolladores
-
-- El backend es el origen de verdad para la lógica de seguridad y sesiones.
-- El frontend puede correr en modo dev para desarrollo rápido.
-- En producción, el backend usa el build estático de React.
-- Si un cambio en `frontend/src` no se refleja, revisa si estás usando `5173` (dev) o `8000` (backend+build).
+# Backend - PoC SaaS Iframe
+
+Este documento explica cómo funciona el backend del proyecto, qué endpoints ofrece y cómo se integra con el frontend React.
+
+## Propósito
+
+El backend sirve como:
+
+- API para autenticación con token, configuración y gestión de sesiones.
+- servidor de archivos estáticos para el build de React en producción (`frontend/dist`).
+- punto de entrada de administración, preview y experiencia embebida.
+- watcher opcional que reconstruye el frontend cuando cambian los archivos fuente.
+
+## Estructura principal
+
+- `main.py` - servidor FastAPI principal.
+- `requirements.txt` - dependencias Python.
+- `run_server.bat` - helper para arrancar el backend con el virtual environment local.
+- `.venv/` - entorno virtual Python del backend.
+- `home.html`, `admin.html`, `preview.html` - páginas de apoyo.
+
+## Cómo ejecutar
+
+### Activar entorno virtual
+
+En Windows CMD:
+
+```cmd
+cd /d C:\Users\alane\OneDrive\Escritorio\Prueba-PoC\backend
+.venv\Scripts\activate
+```
+
+En PowerShell:
+
+```powershell
+cd C:\Users\alane\OneDrive\Escritorio\Prueba-PoC\backend
+.\.venv\Scripts\Activate.ps1
+```
+
+### Instalar dependencias
+
+```cmd
+pip install -r requirements.txt
+```
+
+### Ejecutar servidor
+
+```cmd
+python -m uvicorn main:app --reload --host 0.0.0.0 --port 8000
+```
+
+O usar el helper:
+
+```cmd
+run_server.bat
+```
+
+## Comportamiento de producción
+
+En producción, el backend sirve el build de React desde `frontend/dist` en la ruta `/app`.
+
+- El HTML principal se carga en `/app`
+- Los assets de Vite se sirven en `/app/assets/...`
+- Si `frontend/dist/index.html` no existe, se devuelve un mensaje de error claro.
+
+## Endpoints principales
+
+### Páginas y visualización
+
+- `GET /` - `home.html`
+- `GET /preview` - `preview.html`
+- `GET /admin` - `admin.html`
+- `GET /app` - React app estática servida desde `frontend/dist`
+- `GET /widget.js` - script JS que inyecta un iframe con el visualizador
+- `GET /health` - estado del backend y si el frontend build está listo
+
+### API de integración
+
+- `POST /api/token` - genera un token temporal para `client_id`
+- `GET /config` - devuelve datos del cliente según `client_id` o `token`
+- `POST /session/start` - marca la sesión como activa
+- `GET /api/keys` - lista clientes registrados
+- `POST /api/generate-key` - genera una nueva API key de cliente
+- `GET /api/active-sessions` - muestra sesiones activas actuales
+
+## Lógica de token y cliente
+
+### Validación de token
+
+- Los tokens se guardan en memoria en `TOKENS`
+- Cada token vence después de `TOKEN_TTL` segundos
+- Si el token ha expirado, se devuelve `401`
+
+### Configuración del cliente
+
+- El diccionario `CLIENTS` contiene los clientes registrados por defecto
+- Cada cliente tiene `nombre`, `color_primario` y `created_at`
+- `POST /api/generate-key` agrega un nuevo cliente a `CLIENTS`
+
+## Seguridad y headers importantes
+
+El backend habilita:
+
+- CORS abierto (`allow_origins=["*"]`) para facilitar el desarrollo
+- Eliminación de `x-frame-options` en todas las respuestas
+- Agrega `Content-Security-Policy: frame-ancestors *` para permitir iframes
+
+## Watcher automático de frontend
+
+El backend también incluye un watcher que observa cambios en el frontend y ejecuta `npm run build` automáticamente.
+
+### Qué archivos vigila
+
+- `frontend/src/**/*.{ts,tsx,js,jsx,css,json,html}`
+- `frontend/vite.config.ts`
+- `frontend/package.json`
+- `frontend/tsconfig.json`
+
+### Cómo funciona
+
+- Si el backend está ejecutándose, el watcher corre en un hilo daemon.
+- Cuando detecta cambios, ejecuta `npm run build` en `frontend/`.
+- El resultado actualiza `frontend/dist` para que `/app` sirva la versión nueva.
+
+### Requisitos del watcher
+
+- Necesitas tener `npm` instalado y accesible desde el PATH.
+- El backend debe arrancarse desde el directorio raíz del proyecto.
+
+## Desarrollo y producción
+
+### Desarrollo
+
+- Para trabajar en el frontend con hot reload, usa el dev server de Vite:
+
+```cmd
+cd /d C:\Users\alane\OneDrive\Escritorio\Prueba-PoC\frontend
+npm run dev
+```
+
+- Abre `http://localhost:5173/app?token=...`
+
+### Producción / backend
+
+- Para servir el frontend estático desde el backend:
+
+```cmd
+cd /d C:\Users\alane\OneDrive\Escritorio\Prueba-PoC\frontend
+npm run build
+```
+
+- Luego carga `http://localhost:8000/app?token=...`
+
+## Integración con hyper-ferreteria
+
+Este backend puede montar la lógica de `hyper-ferreteria` en un prefijo alterno para evitar conflictos de rutas.
+
+- Se carga si la carpeta `../hyper-ferreteria` existe junto al directorio `Prueba-PoC`.
+- La integración queda disponible en `http://localhost:8000/hf`.
+- Las rutas internas de `hyper-ferreteria` se exponen como:
+  - `http://localhost:8000/hf/upload_async`
+  - `http://localhost:8000/hf/segment_guided`
+  - `http://localhost:8000/hf/analyze_scene`
+  - `http://localhost:8000/hf/apply_texture`
+  - `http://localhost:8000/hf/textures`
+  - `http://localhost:8000/hf/image/{filename}`
+  - `http://localhost:8000/hf/masks/{filename}`
+  - `http://localhost:8000/hf/ai/{filename}`
+  - y otras rutas de `hyper-ferreteria` con el prefijo `/hf`
+
+## Docker
+
+Se añadió soporte Docker al backend con un `Dockerfile` y `.dockerignore`.
+
+- El contenedor expone el puerto `8000`.
+- El servicio arranca con `uvicorn main:app --host 0.0.0.0 --port 8000`.
+- El `requirements.txt` del backend fue ampliado para incluir las dependencias de `hyper-ferreteria`.
+
+Para construir y correr:
+
+```cmd
+cd /d C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend
+docker build -t prueba-poc-backend .
+docker run -p 8000:8000 prueba-poc-backend
+```
+
+## Notas para nuevos desarrolladores
+
+- El backend es el origen de verdad para la lógica de seguridad y sesiones.
+- El frontend puede correr en modo dev para desarrollo rápido.
+- En producción, el backend usa el build estático de React.
+- Si un cambio en `frontend/src` no se refleja, revisa si estás usando `5173` (dev) o `8000` (backend+build).
diff --git a/backend/admin.html b/backend/admin.html
index d6033f52cebe7b9e4d40631d65b90ef1d21f7814..042c0bf8823620d2d6f980f40c774ce49d919ec9 100644
--- a/backend/admin.html
+++ b/backend/admin.html
@@ -1,202 +1,202 @@
-<!doctype html>
-<html lang="es">
-  <head>
-    <meta charset="UTF-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Panel de Control SaaS</title>
-    <script src="https://cdn.tailwindcss.com"></script>
-  </head>
-  <body class="bg-slate-100 text-slate-900">
-    <div class="max-w-6xl mx-auto p-6 space-y-6">
-      <header
-        class="flex flex-col gap-3 md:flex-row md:items-center md:justify-between"
-      >
-        <div>
-          <h1 class="text-3xl font-bold">Panel de Control SaaS</h1>
-          <p class="text-slate-600">
-            Desde aquí puedes ver usuarios activos, generar nuevas API keys y
-            obtener el script de integración.
-          </p>
-        </div>
-        <div class="space-x-2">
-          <a
-            href="/preview"
-            class="inline-block px-4 py-2 bg-blue-600 text-white rounded-lg hover:bg-blue-700"
-            >Vista previa</a
-          >
-          <button
-            id="open-app-button"
-            class="inline-block px-4 py-2 bg-slate-200 text-slate-900 rounded-lg hover:bg-slate-300"
-          >
-            Abrir app
-          </button>
-        </div>
-      </header>
-
-      <section class="grid gap-6 lg:grid-cols-2">
-        <div class="bg-white rounded-3xl p-6 shadow-lg">
-          <h2 class="text-xl font-semibold mb-4">Generar nueva API key</h2>
-          <div class="space-y-4">
-            <label class="block">
-              <span class="text-sm font-medium text-slate-700"
-                >Nombre del cliente</span
-              >
-              <input
-                id="client-name"
-                type="text"
-                placeholder="Ej. Tienda Sur"
-                class="mt-2 w-full rounded-2xl border border-slate-300 px-4 py-3 focus:border-blue-500 focus:outline-none"
-              />
-            </label>
-            <button
-              id="generate-key"
-              class="w-full px-5 py-3 bg-green-600 text-white rounded-2xl hover:bg-green-700"
-            >
-              Generar API key
-            </button>
-            <div
-              id="generate-result"
-              class="hidden rounded-2xl border border-slate-200 bg-slate-50 p-4 text-slate-900"
-            ></div>
-          </div>
-        </div>
-
-        <div class="bg-white rounded-3xl p-6 shadow-lg">
-          <h2 class="text-xl font-semibold mb-4">
-            Instrucciones de integración
-          </h2>
-          <p class="text-slate-600 mb-4">
-            El desarrollador debe insertar un contenedor y el script del widget
-            en su HTML:
-          </p>
-          <pre
-            class="rounded-2xl bg-slate-950 p-4 text-slate-100 overflow-x-auto"
-          ><code id="static-snippet"></code></pre>
-          <script>
-            document.getElementById("static-snippet").textContent =
-              '<div id="contenedor-saas" data-client-id="ID_UNICO_DEL_CLIENTE_001"></div>\n' +
-              '<script src="' + window.location.origin + '/widget.js"><\/script>';
-          </script>
-          <p class="text-sm text-slate-500 mt-4">
-            Reemplaza <strong>ID_UNICO_DEL_CLIENTE_001</strong> por la API key
-            generada.
-          </p>
-        </div>
-      </section>
-
-      <section class="grid gap-6 lg:grid-cols-2">
-        <div class="bg-white rounded-3xl p-6 shadow-lg">
-          <h2 class="text-xl font-semibold mb-4">Clientes registrados</h2>
-          <div id="clients-list" class="space-y-3 text-slate-700"></div>
-        </div>
-        <div class="bg-white rounded-3xl p-6 shadow-lg">
-          <h2 class="text-xl font-semibold mb-4">Usuarios activos</h2>
-          <div id="active-list" class="space-y-3 text-slate-700"></div>
-        </div>
-      </section>
-    </div>
-
-    <script>
-      async function loadData() {
-        const [keysRes, activeRes] = await Promise.all([
-          fetch("/api/keys"),
-          fetch("/api/active-sessions"),
-        ]);
-        const keysData = await keysRes.json();
-        const activeData = await activeRes.json();
-
-        const clientsList = document.getElementById("clients-list");
-        clientsList.innerHTML = keysData.keys
-          .map(
-            (key) => `
-          <div class="rounded-2xl border border-slate-200 bg-slate-50 p-4">
-            <div class="font-semibold">${key.nombre}</div>
-            <div class="text-sm text-slate-500">API key: <code>${key.client_id}</code></div>
-            <div class="text-sm text-slate-500">Color primario: ${key.color_primario}</div>
-            <div class="text-sm text-slate-500">Creado: ${key.created_at}</div>
-          </div>
-        `,
-          )
-          .join("");
-
-        const activeList = document.getElementById("active-list");
-        if (activeData.active_sessions.length === 0) {
-          activeList.innerHTML =
-            '<p class="text-sm text-slate-500">No hay sesiones activas aún.</p>';
-        } else {
-          activeList.innerHTML = activeData.active_sessions
-            .map(
-              (item) => `
-            <div class="rounded-2xl border border-slate-200 bg-slate-50 p-4">
-              <div class="font-semibold">${item.client_id}</div>
-              <div class="text-sm text-slate-500">Último acceso: ${item.last_seen}</div>
-            </div>
-          `,
-            )
-            .join("");
-        }
-      }
-
-      document
-        .getElementById("generate-key")
-        .addEventListener("click", async () => {
-          const nameInput = document.getElementById("client-name");
-          const name = nameInput.value.trim();
-          if (!name) {
-            alert("Ingresa el nombre del cliente antes de generar la API key.");
-            return;
-          }
-
-          const formData = new URLSearchParams();
-          formData.append("nombre", name);
-
-          const response = await fetch("/api/generate-key", {
-            method: "POST",
-            body: formData,
-          });
-          const result = await response.json();
-
-          const resultBox = document.getElementById("generate-result");
-          resultBox.classList.remove("hidden");
-          const escapedSnippet = result.snippet
-            .replace(/&/g, "&amp;")
-            .replace(/</g, "&lt;")
-            .replace(/>/g, "&gt;");
-          resultBox.innerHTML = `
-          <p class="font-semibold text-slate-900">API key generada:</p>
-          <p class="mt-2"><code>${result.client_id}</code></p>
-          <p class="mt-3 font-semibold text-slate-900">Snippet para el cliente:</p>
-          <pre class="mt-2 rounded-2xl bg-slate-950 p-4 text-slate-100 overflow-x-auto"><code>${escapedSnippet}</code></pre>
-        `;
-
-          nameInput.value = "";
-          await loadData();
-        });
-
-      loadData();
-
-      document
-        .getElementById("open-app-button")
-        .addEventListener("click", async () => {
-          const clientId = "ID_UNICO_DEL_CLIENTE_001";
-          try {
-            const res = await fetch("/api/token", {
-              method: "POST",
-              headers: { "Content-Type": "application/x-www-form-urlencoded" },
-              body: `client_id=${encodeURIComponent(clientId)}`,
-            });
-            const data = await res.json();
-            if (!res.ok) {
-              throw new Error(data.error || "No se pudo generar token.");
-            }
-            window.open(
-              `/app?token=${encodeURIComponent(data.token)}`,
-              "_blank",
-            );
-          } catch (error) {
-            alert("No se pudo abrir el app: " + error.message);
-          }
-        });
-    </script>
-  </body>
-</html>
+<!doctype html>
+<html lang="es">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>Panel de Control SaaS</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+  </head>
+  <body class="bg-slate-100 text-slate-900">
+    <div class="max-w-6xl mx-auto p-6 space-y-6">
+      <header
+        class="flex flex-col gap-3 md:flex-row md:items-center md:justify-between"
+      >
+        <div>
+          <h1 class="text-3xl font-bold">Panel de Control SaaS</h1>
+          <p class="text-slate-600">
+            Desde aquí puedes ver usuarios activos, generar nuevas API keys y
+            obtener el script de integración.
+          </p>
+        </div>
+        <div class="space-x-2">
+          <a
+            href="/preview"
+            class="inline-block px-4 py-2 bg-blue-600 text-white rounded-lg hover:bg-blue-700"
+            >Vista previa</a
+          >
+          <button
+            id="open-app-button"
+            class="inline-block px-4 py-2 bg-slate-200 text-slate-900 rounded-lg hover:bg-slate-300"
+          >
+            Abrir app
+          </button>
+        </div>
+      </header>
+
+      <section class="grid gap-6 lg:grid-cols-2">
+        <div class="bg-white rounded-3xl p-6 shadow-lg">
+          <h2 class="text-xl font-semibold mb-4">Generar nueva API key</h2>
+          <div class="space-y-4">
+            <label class="block">
+              <span class="text-sm font-medium text-slate-700"
+                >Nombre del cliente</span
+              >
+              <input
+                id="client-name"
+                type="text"
+                placeholder="Ej. Tienda Sur"
+                class="mt-2 w-full rounded-2xl border border-slate-300 px-4 py-3 focus:border-blue-500 focus:outline-none"
+              />
+            </label>
+            <button
+              id="generate-key"
+              class="w-full px-5 py-3 bg-green-600 text-white rounded-2xl hover:bg-green-700"
+            >
+              Generar API key
+            </button>
+            <div
+              id="generate-result"
+              class="hidden rounded-2xl border border-slate-200 bg-slate-50 p-4 text-slate-900"
+            ></div>
+          </div>
+        </div>
+
+        <div class="bg-white rounded-3xl p-6 shadow-lg">
+          <h2 class="text-xl font-semibold mb-4">
+            Instrucciones de integración
+          </h2>
+          <p class="text-slate-600 mb-4">
+            El desarrollador debe insertar un contenedor y el script del widget
+            en su HTML:
+          </p>
+          <pre
+            class="rounded-2xl bg-slate-950 p-4 text-slate-100 overflow-x-auto"
+          ><code id="static-snippet"></code></pre>
+          <script>
+            document.getElementById("static-snippet").textContent =
+              '<div id="contenedor-saas" data-client-id="ID_UNICO_DEL_CLIENTE_001"></div>\n' +
+              '<script src="' + window.location.origin + '/widget.js"><\/script>';
+          </script>
+          <p class="text-sm text-slate-500 mt-4">
+            Reemplaza <strong>ID_UNICO_DEL_CLIENTE_001</strong> por la API key
+            generada.
+          </p>
+        </div>
+      </section>
+
+      <section class="grid gap-6 lg:grid-cols-2">
+        <div class="bg-white rounded-3xl p-6 shadow-lg">
+          <h2 class="text-xl font-semibold mb-4">Clientes registrados</h2>
+          <div id="clients-list" class="space-y-3 text-slate-700"></div>
+        </div>
+        <div class="bg-white rounded-3xl p-6 shadow-lg">
+          <h2 class="text-xl font-semibold mb-4">Usuarios activos</h2>
+          <div id="active-list" class="space-y-3 text-slate-700"></div>
+        </div>
+      </section>
+    </div>
+
+    <script>
+      async function loadData() {
+        const [keysRes, activeRes] = await Promise.all([
+          fetch("/api/keys"),
+          fetch("/api/active-sessions"),
+        ]);
+        const keysData = await keysRes.json();
+        const activeData = await activeRes.json();
+
+        const clientsList = document.getElementById("clients-list");
+        clientsList.innerHTML = keysData.keys
+          .map(
+            (key) => `
+          <div class="rounded-2xl border border-slate-200 bg-slate-50 p-4">
+            <div class="font-semibold">${key.nombre}</div>
+            <div class="text-sm text-slate-500">API key: <code>${key.client_id}</code></div>
+            <div class="text-sm text-slate-500">Color primario: ${key.color_primario}</div>
+            <div class="text-sm text-slate-500">Creado: ${key.created_at}</div>
+          </div>
+        `,
+          )
+          .join("");
+
+        const activeList = document.getElementById("active-list");
+        if (activeData.active_sessions.length === 0) {
+          activeList.innerHTML =
+            '<p class="text-sm text-slate-500">No hay sesiones activas aún.</p>';
+        } else {
+          activeList.innerHTML = activeData.active_sessions
+            .map(
+              (item) => `
+            <div class="rounded-2xl border border-slate-200 bg-slate-50 p-4">
+              <div class="font-semibold">${item.client_id}</div>
+              <div class="text-sm text-slate-500">Último acceso: ${item.last_seen}</div>
+            </div>
+          `,
+            )
+            .join("");
+        }
+      }
+
+      document
+        .getElementById("generate-key")
+        .addEventListener("click", async () => {
+          const nameInput = document.getElementById("client-name");
+          const name = nameInput.value.trim();
+          if (!name) {
+            alert("Ingresa el nombre del cliente antes de generar la API key.");
+            return;
+          }
+
+          const formData = new URLSearchParams();
+          formData.append("nombre", name);
+
+          const response = await fetch("/api/generate-key", {
+            method: "POST",
+            body: formData,
+          });
+          const result = await response.json();
+
+          const resultBox = document.getElementById("generate-result");
+          resultBox.classList.remove("hidden");
+          const escapedSnippet = result.snippet
+            .replace(/&/g, "&amp;")
+            .replace(/</g, "&lt;")
+            .replace(/>/g, "&gt;");
+          resultBox.innerHTML = `
+          <p class="font-semibold text-slate-900">API key generada:</p>
+          <p class="mt-2"><code>${result.client_id}</code></p>
+          <p class="mt-3 font-semibold text-slate-900">Snippet para el cliente:</p>
+          <pre class="mt-2 rounded-2xl bg-slate-950 p-4 text-slate-100 overflow-x-auto"><code>${escapedSnippet}</code></pre>
+        `;
+
+          nameInput.value = "";
+          await loadData();
+        });
+
+      loadData();
+
+      document
+        .getElementById("open-app-button")
+        .addEventListener("click", async () => {
+          const clientId = "ID_UNICO_DEL_CLIENTE_001";
+          try {
+            const res = await fetch("/api/token", {
+              method: "POST",
+              headers: { "Content-Type": "application/x-www-form-urlencoded" },
+              body: `client_id=${encodeURIComponent(clientId)}`,
+            });
+            const data = await res.json();
+            if (!res.ok) {
+              throw new Error(data.error || "No se pudo generar token.");
+            }
+            window.open(
+              `/app?token=${encodeURIComponent(data.token)}`,
+              "_blank",
+            );
+          } catch (error) {
+            alert("No se pudo abrir el app: " + error.message);
+          }
+        });
+    </script>
+  </body>
+</html>
diff --git a/backend/core/config.py b/backend/core/config.py
index b68f5980d84d7567c7af9d67583eef8d94fe5132..042d330b6933c69fffee90bdb6c670dd01c457c0 100644
--- a/backend/core/config.py
+++ b/backend/core/config.py
@@ -1,92 +1,92 @@
-import logging
-import os
-import time
-from datetime import datetime, timezone
-from pathlib import Path
-
-BASE_DIR = Path(__file__).resolve().parent.parent
-
-UPLOAD_DIR = BASE_DIR / "uploads"
-UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
-
-VIDEO_UPLOAD_DIR = UPLOAD_DIR / "videos"
-VIDEO_UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
-
-OUTPUT_DIR = BASE_DIR / "outputs"
-OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
-
-VIDEO_OUTPUT_DIR = OUTPUT_DIR / "videos"
-VIDEO_OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
-
-TEXTURE_DIR = BASE_DIR / "texturas"
-TEXTURE_DIR.mkdir(parents=True, exist_ok=True)
-
-LOG_DIR = BASE_DIR / "logs"
-LOG_DIR.mkdir(exist_ok=True)
-
-TEMPLATES_DIR = BASE_DIR / "templates"
-TEMPLATES_DIR.mkdir(parents=True, exist_ok=True)
-
-CLASSIC_DASHBOARD_HTML_PATH = TEMPLATES_DIR / "classic_dashboard.html"
-
-logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s %(levelname)s %(name)s: %(message)s",
-    handlers=[
-        logging.FileHandler(LOG_DIR / "app.log", encoding="utf-8"),
-        logging.StreamHandler(),
-    ],
-)
-logger = logging.getLogger("backend.segmentation")
-
-SAM2_CONFIG_PATH = os.getenv("SAM2_CONFIG_PATH", "configs/sam2.1/sam2.1_hiera_l.yaml")
-SAM2_MODEL_PATH = os.getenv("SAM2_MODEL_PATH")
-SAM2_DEFAULT_MODEL_NAMES = (
-    "sam2.1_hiera_large_fresh.pt",
-    "sam2.1_hiera_large.pt",
-    "sam2.1_hiera_large.pth",
-    "sam2_hiera_large.pt",
-)
-SAM2_MODEL_DIR_CANDIDATES = ("models", "modelo")
-SAM2_UNLOAD_AFTER_USE = str(os.getenv("SAM2_UNLOAD_AFTER_USE", "0")).strip().lower() in {"1", "true", "yes"}
-FRONTEND_DEBUG = str(os.getenv("FRONTEND_DEBUG", "0")).strip().lower() in {"1", "true", "yes", "on"}
-
-# URL del Space de Gradio GPU (principal). Si falla, se usa el CPU fallback.
-# Local:      http://localhost:7860
-# Producción: https://<tu-space>.hf.space
-GRADIO_SPACE_URL: str = os.getenv("GRADIO_SPACE_URL", "").rstrip("/")
-
-# URL del Space de Gradio CPU (respaldo automático si el GPU falla o agota quota).
-GRADIO_CPU_FALLBACK_URL: str = os.getenv("GRADIO_CPU_FALLBACK_URL", "").rstrip("/")
-
-MAX_UPLOAD_WIDTH = 1024
-UPLOAD_JPEG_QUALITY = 82
-SD_JOB_STALE_SECONDS = 120
-UPLOAD_JOB_STALE_SECONDS = 900
-UPLOAD_BASE_SECONDS = 8.0
-UPLOAD_SECONDS_PER_MEGAPIXEL = 70.0
-SD_QUICK_TIMEOUT_SECONDS = 15.0
-
-SEMANTIC_MODEL_ID = "nvidia/segformer-b5-finetuned-ade-640-640"
-DEPTH_MODEL_ID = "Intel/dpt-hybrid-midas"
-
-
-def utc_now_iso() -> str:
-    return datetime.now(timezone.utc).isoformat()
-
-
-def log_timing_start(step_name: str) -> float:
-    started = time.perf_counter()
-    logger.info(f"[{step_name}] START at {utc_now_iso()}")
-    return started
-
-
-def log_timing_end(step_name: str, started: float) -> None:
-    elapsed = time.perf_counter() - started
-    logger.info(f"[{step_name}] DONE {elapsed:.3f}s at {utc_now_iso()}")
-
-
-def load_classic_dashboard_html() -> str:
-    if not CLASSIC_DASHBOARD_HTML_PATH.exists() or not CLASSIC_DASHBOARD_HTML_PATH.is_file():
-        raise RuntimeError(f"Dashboard HTML template not found: {CLASSIC_DASHBOARD_HTML_PATH}")
-    return CLASSIC_DASHBOARD_HTML_PATH.read_text(encoding="utf-8")
+import logging
+import os
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+
+BASE_DIR = Path(__file__).resolve().parent.parent
+
+UPLOAD_DIR = BASE_DIR / "uploads"
+UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
+
+VIDEO_UPLOAD_DIR = UPLOAD_DIR / "videos"
+VIDEO_UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
+
+OUTPUT_DIR = BASE_DIR / "outputs"
+OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+VIDEO_OUTPUT_DIR = OUTPUT_DIR / "videos"
+VIDEO_OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+TEXTURE_DIR = BASE_DIR / "texturas"
+TEXTURE_DIR.mkdir(parents=True, exist_ok=True)
+
+LOG_DIR = BASE_DIR / "logs"
+LOG_DIR.mkdir(exist_ok=True)
+
+TEMPLATES_DIR = BASE_DIR / "templates"
+TEMPLATES_DIR.mkdir(parents=True, exist_ok=True)
+
+CLASSIC_DASHBOARD_HTML_PATH = TEMPLATES_DIR / "classic_dashboard.html"
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s %(levelname)s %(name)s: %(message)s",
+    handlers=[
+        logging.FileHandler(LOG_DIR / "app.log", encoding="utf-8"),
+        logging.StreamHandler(),
+    ],
+)
+logger = logging.getLogger("backend.segmentation")
+
+SAM2_CONFIG_PATH = os.getenv("SAM2_CONFIG_PATH", "configs/sam2.1/sam2.1_hiera_l.yaml")
+SAM2_MODEL_PATH = os.getenv("SAM2_MODEL_PATH")
+SAM2_DEFAULT_MODEL_NAMES = (
+    "sam2.1_hiera_large_fresh.pt",
+    "sam2.1_hiera_large.pt",
+    "sam2.1_hiera_large.pth",
+    "sam2_hiera_large.pt",
+)
+SAM2_MODEL_DIR_CANDIDATES = ("models", "modelo")
+SAM2_UNLOAD_AFTER_USE = str(os.getenv("SAM2_UNLOAD_AFTER_USE", "0")).strip().lower() in {"1", "true", "yes"}
+FRONTEND_DEBUG = str(os.getenv("FRONTEND_DEBUG", "0")).strip().lower() in {"1", "true", "yes", "on"}
+
+# URL del Space de Gradio GPU (principal). Si falla, se usa el CPU fallback.
+# Local:      http://localhost:7860
+# Producción: https://<tu-space>.hf.space
+GRADIO_SPACE_URL: str = os.getenv("GRADIO_SPACE_URL", "").rstrip("/")
+
+# URL del Space de Gradio CPU (respaldo automático si el GPU falla o agota quota).
+GRADIO_CPU_FALLBACK_URL: str = os.getenv("GRADIO_CPU_FALLBACK_URL", "").rstrip("/")
+
+MAX_UPLOAD_WIDTH = 1024
+UPLOAD_JPEG_QUALITY = 82
+SD_JOB_STALE_SECONDS = 120
+UPLOAD_JOB_STALE_SECONDS = 900
+UPLOAD_BASE_SECONDS = 8.0
+UPLOAD_SECONDS_PER_MEGAPIXEL = 70.0
+SD_QUICK_TIMEOUT_SECONDS = 15.0
+
+SEMANTIC_MODEL_ID = "nvidia/segformer-b5-finetuned-ade-640-640"
+DEPTH_MODEL_ID = "Intel/dpt-hybrid-midas"
+
+
+def utc_now_iso() -> str:
+    return datetime.now(timezone.utc).isoformat()
+
+
+def log_timing_start(step_name: str) -> float:
+    started = time.perf_counter()
+    logger.info(f"[{step_name}] START at {utc_now_iso()}")
+    return started
+
+
+def log_timing_end(step_name: str, started: float) -> None:
+    elapsed = time.perf_counter() - started
+    logger.info(f"[{step_name}] DONE {elapsed:.3f}s at {utc_now_iso()}")
+
+
+def load_classic_dashboard_html() -> str:
+    if not CLASSIC_DASHBOARD_HTML_PATH.exists() or not CLASSIC_DASHBOARD_HTML_PATH.is_file():
+        raise RuntimeError(f"Dashboard HTML template not found: {CLASSIC_DASHBOARD_HTML_PATH}")
+    return CLASSIC_DASHBOARD_HTML_PATH.read_text(encoding="utf-8")
diff --git a/backend/home.html b/backend/home.html
index 208f040e1fdb5a29cb42614b737a12ad6a005e72..334e661bce929a170efdc2ba35c9e2fbe415df07 100644
--- a/backend/home.html
+++ b/backend/home.html
@@ -1,61 +1,61 @@
-<!doctype html>
-<html lang="es">
-  <head>
-    <meta charset="UTF-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Home - SaaS Dev</title>
-    <script src="https://cdn.tailwindcss.com"></script>
-  </head>
-  <body class="bg-slate-100 text-slate-900">
-    <div class="max-w-5xl mx-auto p-6 space-y-6">
-      <header class="rounded-3xl bg-white p-6 shadow-lg">
-        <h1 class="text-3xl font-bold">Home de desarrollo</h1>
-        <p class="mt-2 text-slate-600">
-          Esta página es la landing principal para el equipo de desarrollo.
-          Desde aquí puedes acceder al panel administrador, la vista previa y al
-          app embebido.
-        </p>
-      </header>
-
-      <div class="grid gap-6 md:grid-cols-3">
-        <a
-          href="/admin"
-          class="block rounded-3xl bg-white p-6 shadow-lg hover:shadow-xl transition"
-        >
-          <h2 class="text-xl font-semibold">Panel de Control</h2>
-          <p class="mt-2 text-slate-600">
-            Generar API keys, ver clientes y sesiones activas.
-          </p>
-        </a>
-        <a
-          href="/preview"
-          class="block rounded-3xl bg-white p-6 shadow-lg hover:shadow-xl transition"
-        >
-          <h2 class="text-xl font-semibold">Vista Previa</h2>
-          <p class="mt-2 text-slate-600">
-            Ver cómo se carga el visualizador dentro de un iframe.
-          </p>
-        </a>
-        <a
-          href="/app?key=ID_UNICO_DEL_CLIENTE_001"
-          class="block rounded-3xl bg-white p-6 shadow-lg hover:shadow-xl transition"
-        >
-          <h2 class="text-xl font-semibold">App en producción</h2>
-          <p class="mt-2 text-slate-600">
-            Abrir el visualizador directamente en la ruta del app.
-          </p>
-        </a>
-      </div>
-
-      <div class="rounded-3xl bg-white p-6 shadow-lg">
-        <h2 class="text-xl font-semibold">Sugerencia</h2>
-        <p class="mt-2 text-slate-600">
-          Mover el app a <code>/app</code> y mantener <code>/</code> como
-          landing de desarrollo es una buena práctica. Así el servidor puede
-          servir contenido para el equipo sin confundirlo con la ruta del
-          producto embebido.
-        </p>
-      </div>
-    </div>
-  </body>
-</html>
+<!doctype html>
+<html lang="es">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>Home - SaaS Dev</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+  </head>
+  <body class="bg-slate-100 text-slate-900">
+    <div class="max-w-5xl mx-auto p-6 space-y-6">
+      <header class="rounded-3xl bg-white p-6 shadow-lg">
+        <h1 class="text-3xl font-bold">Home de desarrollo</h1>
+        <p class="mt-2 text-slate-600">
+          Esta página es la landing principal para el equipo de desarrollo.
+          Desde aquí puedes acceder al panel administrador, la vista previa y al
+          app embebido.
+        </p>
+      </header>
+
+      <div class="grid gap-6 md:grid-cols-3">
+        <a
+          href="/admin"
+          class="block rounded-3xl bg-white p-6 shadow-lg hover:shadow-xl transition"
+        >
+          <h2 class="text-xl font-semibold">Panel de Control</h2>
+          <p class="mt-2 text-slate-600">
+            Generar API keys, ver clientes y sesiones activas.
+          </p>
+        </a>
+        <a
+          href="/preview"
+          class="block rounded-3xl bg-white p-6 shadow-lg hover:shadow-xl transition"
+        >
+          <h2 class="text-xl font-semibold">Vista Previa</h2>
+          <p class="mt-2 text-slate-600">
+            Ver cómo se carga el visualizador dentro de un iframe.
+          </p>
+        </a>
+        <a
+          href="/app?key=ID_UNICO_DEL_CLIENTE_001"
+          class="block rounded-3xl bg-white p-6 shadow-lg hover:shadow-xl transition"
+        >
+          <h2 class="text-xl font-semibold">App en producción</h2>
+          <p class="mt-2 text-slate-600">
+            Abrir el visualizador directamente en la ruta del app.
+          </p>
+        </a>
+      </div>
+
+      <div class="rounded-3xl bg-white p-6 shadow-lg">
+        <h2 class="text-xl font-semibold">Sugerencia</h2>
+        <p class="mt-2 text-slate-600">
+          Mover el app a <code>/app</code> y mantener <code>/</code> como
+          landing de desarrollo es una buena práctica. Así el servidor puede
+          servir contenido para el equipo sin confundirlo con la ruta del
+          producto embebido.
+        </p>
+      </div>
+    </div>
+  </body>
+</html>
diff --git a/backend/logs/app.log b/backend/logs/app.log
index 04000c174eb2e2d9cf6fd0b89d6894bce2c2ff0b..98d720fe46c0cd70a8c5b2bb7e589a41895d441a 100644
--- a/backend/logs/app.log
+++ b/backend/logs/app.log
@@ -1,5220 +1,2392 @@
-2026-04-29 20:12:40,375 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-29 20:13:22,434 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69f2bac20e0544b45d45e6f1, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69f2bac20e0544b45d45e6f1"}, "remainingTimeMS": 30}
-2026-04-29 20:13:53,491 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:13:53.491443+00:00
-2026-04-29 20:13:53,492 INFO backend.segmentation: [JOB 667a8562af1044a6926d53449b625dd6] preparing_image progress=12
-2026-04-29 20:13:53,743 INFO backend.segmentation: [JOB 667a8562af1044a6926d53449b625dd6] segmenting_with_sam2 progress=30 estimated_seconds=51.939840000000004
-2026-04-29 20:13:56,153 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-29 20:13:56,625 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-29 20:13:56,675 WARNING services.gradio_client_service: Gradio Space call failed, falling back to local SAM2: Cannot find a function with `api_name`: /segment.
-2026-04-29 20:13:56,675 INFO backend.segmentation: [SAM2_GENERATE] START at 2026-04-30T02:13:56.675848+00:00
-2026-04-29 20:13:56,687 INFO backend.segmentation: [SAM2] Mask generator not loaded; attempting on-demand load.
-2026-04-29 20:13:56,687 WARNING backend.segmentation: [SAM2] torch not installed — SAM2 unavailable (using Gradio Space)
-2026-04-29 20:13:56,687 ERROR backend.segmentation: [JOB 667a8562af1044a6926d53449b625dd6] failed: 500: torch not installed — SAM2 unavailable (using Gradio Space)
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 145, in run_upload_job
-    label_map, mask_count = generate_label_map(image_rgb)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\scene_service.py", line 134, in generate_label_map
-    generator = get_sam2_mask_generator()
-                ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\sam2_service.py", line 184, in get_sam2_mask_generator
-    raise HTTPException(status_code=500, detail=detail)
-fastapi.exceptions.HTTPException: 500: torch not installed — SAM2 unavailable (using Gradio Space)
-2026-04-29 20:13:56,689 INFO backend.segmentation: [UPLOAD_BG] DONE 3.196s at 2026-04-30T02:13:56.689353+00:00
-2026-04-29 20:13:56,689 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-29 20:13:57,044 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-29 20:13:57,163 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/68121945-8a97-442e-8cbb-59cd817f9df3 "HTTP/1.1 200 OK"
-2026-04-29 20:16:38,951 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-29 20:16:55,032 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:16:55.032702+00:00
-2026-04-29 20:16:55,032 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] preparing_image progress=12
-2026-04-29 20:16:55,089 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] segmenting_with_sam2 progress=30 estimated_seconds=51.939840000000004
-2026-04-29 20:16:57,866 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-04-29 20:17:00,098 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-29 20:17:00,613 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-29 20:17:02,540 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/06d3302a-135c-423c-8294-e950bff0a17a "HTTP/1.1 200 OK"
-2026-04-29 20:17:02,542 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-29 20:17:04,774 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-29 20:17:07,079 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=06d3302a-135c-423c-8294-e950bff0a17a "HTTP/1.1 200 OK"
-2026-04-29 20:17:26,593 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\b17b68f6472ad2c6c0bb7499f231e242c50b344237d319bd3b45d56ef2d488aa\image.webp "HTTP/1.1 200 OK"
-2026-04-29 20:17:26,607 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🌳 Terraza / Patio / Jardín motor=Híbrido Arquitectura (Cityscapes Grande + DINO Pequeño) mask_count=20
-2026-04-29 20:17:26,607 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] saving_masks progress=92
-2026-04-29 20:17:26,690 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] segments_meta saved (20 segments)
-2026-04-29 20:17:26,690 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] done mask_count=20
-2026-04-29 20:17:26,691 INFO backend.segmentation: [UPLOAD_BG] DONE 31.658s at 2026-04-30T02:17:26.691033+00:00
-2026-04-29 20:17:26,691 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-29 20:17:45,867 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:17:45.867306+00:00
-2026-04-29 20:17:46,402 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
-2026-04-29 20:17:46,702 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.835s at 2026-04-30T02:17:46.702156+00:00
-2026-04-29 20:17:50,496 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:17:50.496976+00:00
-2026-04-29 20:17:50,819 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
-2026-04-29 20:17:50,985 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.488s at 2026-04-30T02:17:50.985122+00:00
-2026-04-29 20:17:54,307 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:17:54.307539+00:00
-2026-04-29 20:17:54,768 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
-2026-04-29 20:17:54,931 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.624s at 2026-04-30T02:17:54.931489+00:00
-2026-04-29 20:17:56,247 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:17:56.247254+00:00
-2026-04-29 20:17:56,728 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
-2026-04-29 20:17:56,898 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.651s at 2026-04-30T02:17:56.898353+00:00
-2026-04-29 20:18:00,146 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:00.146989+00:00
-2026-04-29 20:18:00,616 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
-2026-04-29 20:18:00,782 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.636s at 2026-04-30T02:18:00.782444+00:00
-2026-04-29 20:18:05,560 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:05.560412+00:00
-2026-04-29 20:18:06,116 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
-2026-04-29 20:18:06,272 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.712s at 2026-04-30T02:18:06.272748+00:00
-2026-04-29 20:18:11,868 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:18:11.868080+00:00
-2026-04-29 20:18:11,868 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] preparing_image progress=12
-2026-04-29 20:18:11,941 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-29 20:18:14,341 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-04-29 20:18:16,543 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-29 20:18:16,695 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-29 20:18:18,825 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e332d34b-376c-4071-9631-656973e262a0 "HTTP/1.1 200 OK"
-2026-04-29 20:18:18,828 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-29 20:18:21,032 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-29 20:18:23,304 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e332d34b-376c-4071-9631-656973e262a0 "HTTP/1.1 200 OK"
-2026-04-29 20:18:36,010 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7b5a7a453887652d3284bb9eabe628e95982e15d5e0f16ff718d22beb5ed2a72\image.webp "HTTP/1.1 200 OK"
-2026-04-29 20:18:36,020 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
-2026-04-29 20:18:36,021 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] saving_masks progress=92
-2026-04-29 20:18:36,063 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] segments_meta saved (14 segments)
-2026-04-29 20:18:36,063 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] done mask_count=18
-2026-04-29 20:18:36,063 INFO backend.segmentation: [UPLOAD_BG] DONE 24.195s at 2026-04-30T02:18:36.063054+00:00
-2026-04-29 20:18:36,063 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-29 20:18:44,885 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:44.885155+00:00
-2026-04-29 20:18:45,431 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:18:45,591 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.706s at 2026-04-30T02:18:45.591016+00:00
-2026-04-29 20:18:49,898 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:49.898853+00:00
-2026-04-29 20:18:50,427 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:18:50,573 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.674s at 2026-04-30T02:18:50.573101+00:00
-2026-04-29 20:18:52,643 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:52.643494+00:00
-2026-04-29 20:18:53,101 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:18:53,259 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.615s at 2026-04-30T02:18:53.259095+00:00
-2026-04-29 20:18:55,884 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:55.884791+00:00
-2026-04-29 20:18:56,336 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:18:56,483 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.599s at 2026-04-30T02:18:56.483159+00:00
-2026-04-29 20:18:58,689 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:58.689702+00:00
-2026-04-29 20:18:59,139 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:18:59,285 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.596s at 2026-04-30T02:18:59.285688+00:00
-2026-04-29 20:19:01,587 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:01.587113+00:00
-2026-04-29 20:19:02,057 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:19:02,202 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.616s at 2026-04-30T02:19:02.202912+00:00
-2026-04-29 20:19:08,881 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:08.881813+00:00
-2026-04-29 20:19:09,450 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:19:09,598 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.716s at 2026-04-30T02:19:09.598660+00:00
-2026-04-29 20:19:14,081 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:14.081047+00:00
-2026-04-29 20:19:14,613 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:19:14,765 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.684s at 2026-04-30T02:19:14.765513+00:00
-2026-04-29 20:19:20,588 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:20.588691+00:00
-2026-04-29 20:19:21,001 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:19:21,148 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.560s at 2026-04-30T02:19:21.148963+00:00
-2026-04-29 20:19:26,717 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:19:26.717015+00:00
-2026-04-29 20:19:26,717 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] preparing_image progress=12
-2026-04-29 20:19:26,784 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-29 20:19:29,222 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-04-29 20:19:31,597 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-29 20:19:31,734 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-29 20:19:34,073 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/19c5143b-64ec-4b5d-942b-098f7096a07d "HTTP/1.1 200 OK"
-2026-04-29 20:19:34,076 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-29 20:19:36,338 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-29 20:19:38,618 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=19c5143b-64ec-4b5d-942b-098f7096a07d "HTTP/1.1 200 OK"
-2026-04-29 20:19:50,817 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\627367a96ce0d7cea77d51e3b57be3a803ddd9b06e2c8a9547129f322756dd05\image.webp "HTTP/1.1 200 OK"
-2026-04-29 20:19:50,828 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=13
-2026-04-29 20:19:50,828 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] saving_masks progress=92
-2026-04-29 20:19:50,860 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] segments_meta saved (13 segments)
-2026-04-29 20:19:50,861 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] done mask_count=13
-2026-04-29 20:19:50,861 INFO backend.segmentation: [UPLOAD_BG] DONE 24.145s at 2026-04-30T02:19:50.861597+00:00
-2026-04-29 20:19:50,861 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-29 20:19:58,632 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:58.632422+00:00
-2026-04-29 20:19:58,950 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:19:59,096 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.464s at 2026-04-30T02:19:59.096073+00:00
-2026-04-29 20:20:03,025 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:20:03.025850+00:00
-2026-04-29 20:20:03,491 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:20:03,640 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.615s at 2026-04-30T02:20:03.640105+00:00
-2026-04-29 20:20:20,501 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:20:20.501928+00:00
-2026-04-29 20:20:21,076 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:20:21,227 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.727s at 2026-04-30T02:20:21.227737+00:00
-2026-04-29 20:20:28,266 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:20:28.266563+00:00
-2026-04-29 20:20:28,768 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:20:28,935 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.669s at 2026-04-30T02:20:28.935807+00:00
-2026-04-29 20:20:35,728 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:20:35.728058+00:00
-2026-04-29 20:20:35,729 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] preparing_image progress=12
-2026-04-29 20:20:35,790 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-29 20:20:38,252 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-04-29 20:20:40,610 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-29 20:20:40,810 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-29 20:20:43,106 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/31bdf8c4-3e85-4561-b055-cb540bff6222 "HTTP/1.1 200 OK"
-2026-04-29 20:20:43,110 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-29 20:20:45,435 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-29 20:20:47,968 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=31bdf8c4-3e85-4561-b055-cb540bff6222 "HTTP/1.1 200 OK"
-2026-04-29 20:21:09,199 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\de39b2da096587a3b0e0d7fb57541b12755192b377f4914a8047c40356bfbf4a\image.webp "HTTP/1.1 200 OK"
-2026-04-29 20:21:09,216 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=30
-2026-04-29 20:21:09,217 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] saving_masks progress=92
-2026-04-29 20:21:09,330 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] segments_meta saved (18 segments)
-2026-04-29 20:21:09,330 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] done mask_count=30
-2026-04-29 20:21:09,331 INFO backend.segmentation: [UPLOAD_BG] DONE 33.603s at 2026-04-30T02:21:09.331315+00:00
-2026-04-29 20:21:09,331 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-29 20:21:19,563 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:21:19.563482+00:00
-2026-04-29 20:21:19,875 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:21:20,037 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.474s at 2026-04-30T02:21:20.037544+00:00
-2026-04-29 20:21:27,716 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:21:27.716717+00:00
-2026-04-29 20:21:28,240 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:21:28,388 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.671s at 2026-04-30T02:21:28.388007+00:00
-2026-04-29 20:21:33,770 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:21:33.770053+00:00
-2026-04-29 20:21:34,297 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:21:34,445 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.676s at 2026-04-30T02:21:34.445668+00:00
-2026-04-29 20:21:45,556 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:21:45.556315+00:00
-2026-04-29 20:21:46,063 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:21:46,214 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.658s at 2026-04-30T02:21:46.214366+00:00
-2026-04-29 20:21:54,885 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:21:54.885450+00:00
-2026-04-29 20:21:54,886 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] preparing_image progress=12
-2026-04-29 20:21:55,003 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] segmenting_with_sam2 progress=30 estimated_seconds=138.4576
-2026-04-29 20:21:57,389 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-04-29 20:21:59,757 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-29 20:21:59,891 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-29 20:22:02,312 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-29 20:22:02,322 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/3f8ed7a1-4b28-46c2-9e01-7e4358b38e76 "HTTP/1.1 200 OK"
-2026-04-29 20:22:04,682 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-29 20:22:07,179 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=3f8ed7a1-4b28-46c2-9e01-7e4358b38e76 "HTTP/1.1 200 OK"
-2026-04-29 20:22:33,186 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\80421cbcd599451a04044e3ece45f375843574c97db6199cd4e3f022f90b9311\image.webp "HTTP/1.1 200 OK"
-2026-04-29 20:22:33,213 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=16
-2026-04-29 20:22:33,214 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] saving_masks progress=92
-2026-04-29 20:22:33,419 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] segments_meta saved (16 segments)
-2026-04-29 20:22:33,419 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] done mask_count=16
-2026-04-29 20:22:33,419 INFO backend.segmentation: [UPLOAD_BG] DONE 38.534s at 2026-04-30T02:22:33.419503+00:00
-2026-04-29 20:22:33,420 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-29 20:22:38,594 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:22:38.593824+00:00
-2026-04-29 20:22:38,977 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:22:39,402 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.808s at 2026-04-30T02:22:39.402689+00:00
-2026-04-29 20:22:44,189 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:22:44.189800+00:00
-2026-04-29 20:22:44,726 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:22:45,179 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.990s at 2026-04-30T02:22:45.179303+00:00
-2026-04-29 20:22:50,087 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:22:50.087424+00:00
-2026-04-29 20:22:50,751 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-29 20:22:51,466 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.379s at 2026-04-30T02:22:51.466435+00:00
-2026-04-29 20:26:39,065 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-29 20:26:39,964 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-29 20:33:56,025 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-29 20:34:02,828 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:34:02.828129+00:00
-2026-04-29 20:34:02,830 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] preparing_image progress=12
-2026-04-29 20:34:02,900 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] segmenting_with_sam2 progress=30 estimated_seconds=51.939840000000004
-2026-04-29 20:34:04,067 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-29 20:34:04,727 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-29 20:34:05,153 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-29 20:34:05,258 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/b306737b-bf28-4f02-8963-83b74032d449 "HTTP/1.1 200 OK"
-2026-04-29 20:34:05,354 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-29 20:34:05,788 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-29 20:34:06,344 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=b306737b-bf28-4f02-8963-83b74032d449 "HTTP/1.1 200 OK"
-2026-04-29 20:34:24,624 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/edcd82066c73a2359a9133192b4091c873fb9fca768c0f377a7a519aeb9f9b3a/image.webp "HTTP/1.1 200 OK"
-2026-04-29 20:34:24,678 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🌳 Terraza / Patio / Jardín motor=Híbrido Arquitectura (Cityscapes Grande + DINO Pequeño) mask_count=20
-2026-04-29 20:34:24,684 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] saving_masks progress=92
-2026-04-29 20:34:24,781 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] segments_meta saved (20 segments)
-2026-04-29 20:34:24,782 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] done mask_count=20
-2026-04-29 20:34:24,782 INFO backend.segmentation: [UPLOAD_BG] DONE 21.955s at 2026-04-30T02:34:24.782746+00:00
-2026-04-29 20:34:24,783 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-29 20:34:27,987 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:34:27.987941+00:00
-2026-04-29 20:34:28,292 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
-2026-04-29 20:34:28,570 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.582s at 2026-04-30T02:34:28.570140+00:00
-2026-04-30 11:28:10,082 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 11:28:10,113 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-30 11:28:44,116 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T17:28:44.116002+00:00
-2026-04-30 11:28:44,117 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] preparing_image progress=12
-2026-04-30 11:28:44,411 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-30 11:28:44,411 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 11:28:47,099 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-30 11:28:47,585 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-30 11:28:48,272 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-30 11:28:48,363 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/7d7be152-f5b8-4924-8c4d-1a0b61711e8f "HTTP/1.1 200 OK"
-2026-04-30 11:28:48,476 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-30 11:28:48,934 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-30 11:28:49,386 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=7d7be152-f5b8-4924-8c4d-1a0b61711e8f "HTTP/1.1 200 OK"
-2026-04-30 11:29:08,489 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
-2026-04-30 11:29:08,588 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
-2026-04-30 11:29:08,590 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] saving_masks progress=92
-2026-04-30 11:29:08,688 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] segments_meta saved (14 segments)
-2026-04-30 11:29:08,688 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] done mask_count=18
-2026-04-30 11:29:08,689 INFO backend.segmentation: [UPLOAD_BG] DONE 24.573s at 2026-04-30T17:29:08.689489+00:00
-2026-04-30 11:29:08,689 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-30 11:34:31,212 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 11:34:31,227 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-30 11:35:20,079 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 11:35:20,093 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-30 11:35:28,226 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T17:35:28.226030+00:00
-2026-04-30 11:35:28,227 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] preparing_image progress=12
-2026-04-30 11:35:28,315 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-30 11:35:28,316 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 11:35:29,381 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-30 11:35:29,927 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-30 11:35:30,567 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-30 11:35:30,680 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/846ae43c-81a8-48af-97ee-8292d522cc64 "HTTP/1.1 200 OK"
-2026-04-30 11:35:30,784 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-30 11:35:31,388 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-30 11:35:31,964 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=846ae43c-81a8-48af-97ee-8292d522cc64 "HTTP/1.1 200 OK"
-2026-04-30 11:35:43,682 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
-2026-04-30 11:35:43,788 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
-2026-04-30 11:35:43,788 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] saving_masks progress=92
-2026-04-30 11:35:43,874 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] segments_meta saved (14 segments)
-2026-04-30 11:35:43,875 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] done mask_count=18
-2026-04-30 11:35:43,875 INFO backend.segmentation: [UPLOAD_BG] DONE 15.650s at 2026-04-30T17:35:43.875230+00:00
-2026-04-30 11:35:43,876 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-30 11:37:18,311 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:18.311528+00:00
-2026-04-30 11:37:18,787 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:37:19,025 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.714s at 2026-04-30T17:37:19.025433+00:00
-2026-04-30 11:37:22,720 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:22.720207+00:00
-2026-04-30 11:37:23,223 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:37:23,371 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.651s at 2026-04-30T17:37:23.371172+00:00
-2026-04-30 11:37:27,040 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:27.040137+00:00
-2026-04-30 11:37:27,461 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:37:27,615 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.576s at 2026-04-30T17:37:27.615284+00:00
-2026-04-30 11:37:32,588 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T17:37:32.588150+00:00
-2026-04-30 11:37:32,589 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] preparing_image progress=12
-2026-04-30 11:37:32,652 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-30 11:37:32,653 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 11:37:33,265 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-30 11:37:33,854 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-30 11:37:34,045 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-30 11:37:34,638 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-30 11:37:35,300 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-30 11:37:35,353 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/f3fac27d-4abe-4757-a29c-4cc301d3c520 "HTTP/1.1 200 OK"
-2026-04-30 11:37:35,860 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=f3fac27d-4abe-4757-a29c-4cc301d3c520 "HTTP/1.1 200 OK"
-2026-04-30 11:37:45,344 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/525c342e2500d48137e90e793b9f3884aa3deedaa44ac6a6178e85433dde68ed/image.webp "HTTP/1.1 200 OK"
-2026-04-30 11:37:45,399 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=19
-2026-04-30 11:37:45,400 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] saving_masks progress=92
-2026-04-30 11:37:45,496 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] segments_meta saved (19 segments)
-2026-04-30 11:37:45,496 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] done mask_count=19
-2026-04-30 11:37:45,497 INFO backend.segmentation: [UPLOAD_BG] DONE 12.909s at 2026-04-30T17:37:45.497768+00:00
-2026-04-30 11:37:45,497 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-30 11:37:51,411 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:51.411336+00:00
-2026-04-30 11:37:51,902 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:37:52,048 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.637s at 2026-04-30T17:37:52.048476+00:00
-2026-04-30 11:37:54,874 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:54.874358+00:00
-2026-04-30 11:37:55,381 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:37:55,525 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.652s at 2026-04-30T17:37:55.525845+00:00
-2026-04-30 11:37:59,388 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:59.388707+00:00
-2026-04-30 11:37:59,889 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.05 < 0.35, skip perspective)
-2026-04-30 11:37:59,903 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:38:00,058 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.670s at 2026-04-30T17:38:00.058226+00:00
-2026-04-30 11:38:04,419 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:04.419644+00:00
-2026-04-30 11:38:04,939 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:38:05,083 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.664s at 2026-04-30T17:38:05.083669+00:00
-2026-04-30 11:38:09,485 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:09.485185+00:00
-2026-04-30 11:38:10,004 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:38:10,164 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.679s at 2026-04-30T17:38:10.164696+00:00
-2026-04-30 11:38:14,863 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:14.863574+00:00
-2026-04-30 11:38:15,447 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:38:15,612 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.750s at 2026-04-30T17:38:15.612415+00:00
-2026-04-30 11:38:18,118 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:18.118131+00:00
-2026-04-30 11:38:18,776 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:38:18,995 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.879s at 2026-04-30T17:38:18.995927+00:00
-2026-04-30 11:38:22,037 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:22.037510+00:00
-2026-04-30 11:38:22,686 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:38:22,873 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.835s at 2026-04-30T17:38:22.873532+00:00
-2026-04-30 11:38:25,520 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:25.520184+00:00
-2026-04-30 11:38:26,145 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:38:26,334 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.815s at 2026-04-30T17:38:26.334641+00:00
-2026-04-30 11:38:28,140 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:28.140486+00:00
-2026-04-30 11:38:28,847 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:38:29,023 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.882s at 2026-04-30T17:38:29.023363+00:00
-2026-04-30 11:38:35,098 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:35.098342+00:00
-2026-04-30 11:38:35,824 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:38:36,028 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.930s at 2026-04-30T17:38:36.028300+00:00
-2026-04-30 11:41:41,140 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T17:41:41.140015+00:00
-2026-04-30 11:41:41,149 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] preparing_image progress=12
-2026-04-30 11:41:41,245 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-30 11:41:41,246 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 11:41:41,911 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-30 11:41:42,462 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-30 11:41:42,643 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-30 11:41:43,175 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/3aef8110-e818-4b0d-b6eb-ea6e1e3f6d26 "HTTP/1.1 200 OK"
-2026-04-30 11:41:43,286 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-30 11:41:43,879 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-30 11:41:44,473 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=3aef8110-e818-4b0d-b6eb-ea6e1e3f6d26 "HTTP/1.1 200 OK"
-2026-04-30 11:41:54,142 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/be028661dd9bac57589c50374ec81fba3f6d33d75c68656f138199c7ecd043d5/image.webp "HTTP/1.1 200 OK"
-2026-04-30 11:41:54,248 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=13
-2026-04-30 11:41:54,250 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] saving_masks progress=92
-2026-04-30 11:41:54,306 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] segments_meta saved (13 segments)
-2026-04-30 11:41:54,307 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] done mask_count=13
-2026-04-30 11:41:54,307 INFO backend.segmentation: [UPLOAD_BG] DONE 13.167s at 2026-04-30T17:41:54.307037+00:00
-2026-04-30 11:41:54,308 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-30 11:43:18,472 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:43:18.472363+00:00
-2026-04-30 11:43:19,016 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:43:19,160 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.688s at 2026-04-30T17:43:19.160192+00:00
-2026-04-30 11:43:30,372 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:43:30.372475+00:00
-2026-04-30 11:43:30,954 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:43:31,098 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.727s at 2026-04-30T17:43:31.098668+00:00
-2026-04-30 11:47:34,143 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:47:34.143047+00:00
-2026-04-30 11:47:34,404 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:47:34,532 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.389s at 2026-04-30T17:47:34.532555+00:00
-2026-04-30 11:47:55,089 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:47:55.089325+00:00
-2026-04-30 11:47:55,583 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 11:47:55,730 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.641s at 2026-04-30T17:47:55.730378+00:00
-2026-04-30 12:04:38,148 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 12:04:38,173 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-30 12:09:38,204 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 12:09:38,219 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-30 12:13:52,707 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T18:13:52.707043+00:00
-2026-04-30 12:13:52,707 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] preparing_image progress=12
-2026-04-30 12:13:52,799 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-30 12:13:52,799 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 12:13:53,878 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-30 12:13:54,504 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-30 12:13:55,176 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-30 12:13:55,270 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/41cb0056-465a-425e-83c0-301658311ea8 "HTTP/1.1 200 OK"
-2026-04-30 12:13:55,368 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-30 12:13:55,904 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-30 12:13:56,487 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=41cb0056-465a-425e-83c0-301658311ea8 "HTTP/1.1 200 OK"
-2026-04-30 12:14:07,019 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
-2026-04-30 12:14:07,128 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
-2026-04-30 12:14:07,129 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] saving_masks progress=92
-2026-04-30 12:14:07,214 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] segments_meta saved (14 segments)
-2026-04-30 12:14:07,214 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] done mask_count=18
-2026-04-30 12:14:07,215 INFO backend.segmentation: [UPLOAD_BG] DONE 14.509s at 2026-04-30T18:14:07.215535+00:00
-2026-04-30 12:14:07,216 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-30 12:15:26,031 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:26.031154+00:00
-2026-04-30 12:15:26,320 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 12:15:26,583 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.552s at 2026-04-30T18:15:26.583372+00:00
-2026-04-30 12:15:31,474 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:31.474416+00:00
-2026-04-30 12:15:31,999 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 12:15:32,141 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.667s at 2026-04-30T18:15:32.141076+00:00
-2026-04-30 12:15:37,533 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:37.533421+00:00
-2026-04-30 12:15:38,003 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 12:15:38,148 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.615s at 2026-04-30T18:15:38.148131+00:00
-2026-04-30 12:15:43,112 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:43.112106+00:00
-2026-04-30 12:15:43,495 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 12:15:43,639 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.528s at 2026-04-30T18:15:43.639421+00:00
-2026-04-30 12:15:48,170 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:48.170441+00:00
-2026-04-30 12:15:48,545 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 12:15:48,688 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.518s at 2026-04-30T18:15:48.688355+00:00
-2026-04-30 12:21:38,766 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T18:21:38.766212+00:00
-2026-04-30 12:21:38,766 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] preparing_image progress=12
-2026-04-30 12:21:38,838 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-30 12:21:38,838 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 12:21:39,938 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-30 12:21:41,143 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-30 12:21:41,334 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-30 12:21:41,668 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/a637527a-5267-4a6e-acc0-e57a7de5119a "HTTP/1.1 200 OK"
-2026-04-30 12:21:41,761 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-30 12:21:42,216 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-30 12:21:42,820 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=a637527a-5267-4a6e-acc0-e57a7de5119a "HTTP/1.1 200 OK"
-2026-04-30 12:21:50,974 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
-2026-04-30 12:21:51,074 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
-2026-04-30 12:21:51,074 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] saving_masks progress=92
-2026-04-30 12:21:51,145 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] segments_meta saved (14 segments)
-2026-04-30 12:21:51,146 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] done mask_count=18
-2026-04-30 12:21:51,147 INFO backend.segmentation: [UPLOAD_BG] DONE 12.381s at 2026-04-30T18:21:51.147398+00:00
-2026-04-30 12:21:51,147 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-30 12:22:28,223 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:22:28.223162+00:00
-2026-04-30 12:22:28,488 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 12:22:28,633 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.410s at 2026-04-30T18:22:28.633219+00:00
-2026-04-30 12:23:38,541 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:23:38.541894+00:00
-2026-04-30 12:23:39,059 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.28 < 0.35, skip perspective)
-2026-04-30 12:23:39,078 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 12:23:39,224 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.682s at 2026-04-30T18:23:39.224901+00:00
-2026-04-30 12:23:47,739 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:23:47.739936+00:00
-2026-04-30 12:23:48,234 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.29 < 0.35, skip perspective)
-2026-04-30 12:23:48,249 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 12:23:48,393 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.654s at 2026-04-30T18:23:48.393543+00:00
-2026-04-30 12:35:04,237 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T18:35:04.237929+00:00
-2026-04-30 12:35:04,237 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] preparing_image progress=12
-2026-04-30 12:35:04,252 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] segmenting_with_sam2 progress=30 estimated_seconds=28.89164
-2026-04-30 12:35:04,252 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 12:35:04,919 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-30 12:35:05,542 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-30 12:35:05,767 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-30 12:35:06,228 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/e02fbff5-268c-40cf-bacf-e1c35bcf4346 "HTTP/1.1 200 OK"
-2026-04-30 12:35:06,341 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-30 12:35:06,892 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-30 12:35:07,458 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=e02fbff5-268c-40cf-bacf-e1c35bcf4346 "HTTP/1.1 200 OK"
-2026-04-30 12:35:29,382 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/75fa9ee4d8e3aa2f3926aa662e35acdfbaa3f94163e61a68527474a5a60675c3/image.webp "HTTP/1.1 200 OK"
-2026-04-30 12:35:29,438 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🏙️ Fachada / Exterior motor=Híbrido Arquitectura (Cityscapes Grande + DINO Pequeño) mask_count=12
-2026-04-30 12:35:29,439 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] saving_masks progress=92
-2026-04-30 12:35:29,463 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] segments_meta saved (11 segments)
-2026-04-30 12:35:29,463 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] done mask_count=12
-2026-04-30 12:35:29,463 INFO backend.segmentation: [UPLOAD_BG] DONE 25.226s at 2026-04-30T18:35:29.463948+00:00
-2026-04-30 12:35:29,464 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-30 15:39:34,392 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 15:39:34,422 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-04-30 15:40:07,782 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69f3cc370fe929ed6cff073d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69f3cc370fe929ed6cff073d"}, "remainingTimeMS": 30}
-2026-04-30 15:40:18,856 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T21:40:18.856487+00:00
-2026-04-30 15:40:18,856 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] preparing_image progress=12
-2026-04-30 15:40:19,134 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-04-30 15:40:19,134 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-04-30 15:40:21,980 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-04-30 15:40:22,624 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-04-30 15:40:23,391 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-04-30 15:40:23,497 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/314c6a15-7cd5-4d38-88c5-58a08df1fad6 "HTTP/1.1 200 OK"
-2026-04-30 15:40:23,607 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-04-30 15:40:24,238 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-04-30 15:40:24,860 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=314c6a15-7cd5-4d38-88c5-58a08df1fad6 "HTTP/1.1 200 OK"
-2026-04-30 15:40:33,216 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
-2026-04-30 15:40:33,324 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
-2026-04-30 15:40:33,325 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] saving_masks progress=92
-2026-04-30 15:40:33,428 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] segments_meta saved (14 segments)
-2026-04-30 15:40:33,428 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] done mask_count=18
-2026-04-30 15:40:33,429 INFO backend.segmentation: [UPLOAD_BG] DONE 14.573s at 2026-04-30T21:40:33.429138+00:00
-2026-04-30 15:40:33,429 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-04-30 15:40:38,479 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T21:40:38.479968+00:00
-2026-04-30 15:40:38,976 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 15:40:39,252 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.773s at 2026-04-30T21:40:39.252883+00:00
-2026-04-30 16:21:48,502 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T22:21:48.502651+00:00
-2026-04-30 16:21:49,012 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-04-30 16:21:49,158 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.656s at 2026-04-30T22:21:49.158351+00:00
-2026-05-06 18:02:51,635 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-06 18:02:51,663 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 18:03:05,661 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fbd6b9d024dc8e891e4555, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fbd6b9d024dc8e891e4555"}, "remainingTimeMS": 30}
-2026-05-06 18:03:54,118 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:03:54.118398+00:00
-2026-05-06 18:03:54,119 INFO backend.segmentation: [JOB e0df636678f746dc9b2d4a29256ab769] preparing_image progress=12
-2026-05-06 18:03:54,441 INFO backend.segmentation: [JOB e0df636678f746dc9b2d4a29256ab769] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
-2026-05-06 18:03:54,441 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 18:03:59,802 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:04:02,031 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:04:02,051 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:04:02,051 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7860
-2026-05-06 18:04:02,487 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:04:04,382 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:04:04,396 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/07a1a8b9-03be-4f34-9425-2b264489eb61 "HTTP/1.1 200 OK"
-2026-05-06 18:04:06,807 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:04:06,810 ERROR backend.segmentation: [JOB e0df636678f746dc9b2d4a29256ab769] failed: cannot access local variable 'exc_gpu' where it is not associated with a value
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 89, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
-    _overlay_file, combined_json_str = client.predict(
-                                       ^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 497, in predict
-    return self.submit(
-           ^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 543, in submit
-    inferred_fn_index = self._infer_fn_index(api_name, fn_index)
-                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 881, in _infer_fn_index
-    raise ValueError(error_message)
-ValueError: Cannot find a function with `api_name`: /segment.
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    f"  GPU ({GRADIO_SPACE_URL}): {exc_gpu}\n"
-                                   ^^^^^^^
-UnboundLocalError: cannot access local variable 'exc_gpu' where it is not associated with a value
-2026-05-06 18:04:06,834 INFO backend.segmentation: [UPLOAD_BG] DONE 12.716s at 2026-05-07T00:04:06.834047+00:00
-2026-05-06 18:04:06,838 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 18:04:06,884 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:04:09,275 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/04b260c2-1554-4cba-a89f-13976ed4ac4d "HTTP/1.1 200 OK"
-2026-05-06 18:09:42,042 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-06 18:09:42,064 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 18:09:42,071 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:09:42.071378+00:00
-2026-05-06 18:09:42,076 INFO backend.segmentation: [JOB 45db3dde20444c6f97e1653fd7df1d17] preparing_image progress=12
-2026-05-06 18:09:42,120 INFO backend.segmentation: [JOB 45db3dde20444c6f97e1653fd7df1d17] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
-2026-05-06 18:09:42,121 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 18:09:44,483 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:09:46,855 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:09:46,857 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:09:46,861 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7860
-2026-05-06 18:09:47,293 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:09:49,183 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/1780c9d0-ac88-47b0-b6c1-3cf40997667d "HTTP/1.1 200 OK"
-2026-05-06 18:09:49,199 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:09:51,480 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:09:51,485 ERROR backend.segmentation: [JOB 45db3dde20444c6f97e1653fd7df1d17] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
-    _overlay_file, combined_json_str = client.predict(
-                                       ^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 497, in predict
-    return self.submit(
-           ^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 543, in submit
-    inferred_fn_index = self._infer_fn_index(api_name, fn_index)
-                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 881, in _infer_fn_index
-    raise ValueError(error_message)
-ValueError: Cannot find a function with `api_name`: /segment.
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-2026-05-06 18:09:51,487 INFO backend.segmentation: [UPLOAD_BG] DONE 9.415s at 2026-05-07T00:09:51.487122+00:00
-2026-05-06 18:09:51,487 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 18:09:51,545 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:09:53,753 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/36233c91-f2f7-4ec1-9a12-3d21c85acebf "HTTP/1.1 200 OK"
-2026-05-06 18:13:22,286 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:13:22.286531+00:00
-2026-05-06 18:13:22,286 INFO backend.segmentation: [JOB 1d0df1096d5f465b92fae7922f6f7018] preparing_image progress=12
-2026-05-06 18:13:22,361 INFO backend.segmentation: [JOB 1d0df1096d5f465b92fae7922f6f7018] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
-2026-05-06 18:13:22,362 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 18:13:24,786 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:13:27,139 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:13:27,145 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:13:27,146 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7860
-2026-05-06 18:13:27,264 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:13:29,620 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/903b6662-21a9-407f-849d-a09f627bf22b "HTTP/1.1 200 OK"
-2026-05-06 18:13:29,696 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:13:32,103 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:13:32,109 ERROR backend.segmentation: [JOB 1d0df1096d5f465b92fae7922f6f7018] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
-    _overlay_file, combined_json_str = client.predict(
-                                       ^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 497, in predict
-    return self.submit(
-           ^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 543, in submit
-    inferred_fn_index = self._infer_fn_index(api_name, fn_index)
-                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 881, in _infer_fn_index
-    raise ValueError(error_message)
-ValueError: Cannot find a function with `api_name`: /segment.
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-2026-05-06 18:13:32,119 INFO backend.segmentation: [UPLOAD_BG] DONE 9.833s at 2026-05-07T00:13:32.119224+00:00
-2026-05-06 18:13:32,120 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 18:13:32,165 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:13:34,556 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e4f38b15-d04a-41ee-bb91-06226b8fcbae "HTTP/1.1 200 OK"
-2026-05-06 18:14:12,194 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-06 18:14:12,207 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 18:14:24,360 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:14:24.360597+00:00
-2026-05-06 18:14:24,360 INFO backend.segmentation: [JOB d0714cc4813c4ff5b969676107410712] preparing_image progress=12
-2026-05-06 18:14:24,496 INFO backend.segmentation: [JOB d0714cc4813c4ff5b969676107410712] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
-2026-05-06 18:14:24,496 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 18:14:27,292 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:14:29,710 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:14:29,737 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:14:29,738 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7860
-2026-05-06 18:14:30,337 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:14:32,244 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/b1361a06-2ac6-4b8d-8a1c-79a0b653d2d4 "HTTP/1.1 200 OK"
-2026-05-06 18:14:32,247 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:14:34,724 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:14:34,728 ERROR backend.segmentation: [JOB d0714cc4813c4ff5b969676107410712] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
-    _overlay_file, combined_json_str = client.predict(
-                                       ^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 497, in predict
-    return self.submit(
-           ^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 543, in submit
-    inferred_fn_index = self._infer_fn_index(api_name, fn_index)
-                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 881, in _infer_fn_index
-    raise ValueError(error_message)
-ValueError: Cannot find a function with `api_name`: /segment.
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
-2026-05-06 18:14:34,732 INFO backend.segmentation: [UPLOAD_BG] DONE 10.372s at 2026-05-07T00:14:34.731556+00:00
-2026-05-06 18:14:34,732 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 18:14:34,784 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:14:37,121 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e7673631-cbf6-43a7-8391-415fae5fc0e9 "HTTP/1.1 200 OK"
-2026-05-06 18:16:40,330 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-06 18:16:40,344 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 18:16:46,189 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:16:46.189444+00:00
-2026-05-06 18:16:46,189 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] preparing_image progress=12
-2026-05-06 18:16:46,293 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
-2026-05-06 18:16:46,293 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 18:16:49,078 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:16:51,479 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:16:51,497 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:16:51,498 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 18:16:52,101 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:16:54,019 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/6b53345b-dde9-4c3f-9adc-6c494ed360ef "HTTP/1.1 200 OK"
-2026-05-06 18:16:54,024 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 18:16:56,487 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:16:56,549 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:16:58,924 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/74fea2e0-6f0d-4dda-a138-a42ba84fc0aa "HTTP/1.1 200 OK"
-2026-05-06 18:16:58,960 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 18:17:01,339 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 18:17:03,913 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=74fea2e0-6f0d-4dda-a138-a42ba84fc0aa "HTTP/1.1 200 OK"
-2026-05-06 18:19:23,132 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\bdc55057e453f1e4793eccb7f3297d66322074e960cb173c3fcf63268faa1561\image.webp "HTTP/1.1 200 OK"
-2026-05-06 18:19:23,155 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🏙️ Fachada / Exterior motor=SAM Auto (Exteriores - Sin Prompts) mask_count=95
-2026-05-06 18:19:23,156 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] saving_masks progress=92
-2026-05-06 18:19:23,605 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] segments_meta saved (93 segments)
-2026-05-06 18:19:23,607 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] done mask_count=95
-2026-05-06 18:19:23,607 INFO backend.segmentation: [UPLOAD_BG] DONE 157.419s at 2026-05-07T00:19:23.607772+00:00
-2026-05-06 18:19:23,607 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 18:19:34,201 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:34.200405+00:00
-2026-05-06 18:19:34,746 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:19:35,040 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.840s at 2026-05-07T00:19:35.040623+00:00
-2026-05-06 18:19:42,196 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:42.196103+00:00
-2026-05-06 18:19:42,742 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:19:42,974 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.779s at 2026-05-07T00:19:42.974981+00:00
-2026-05-06 18:19:47,421 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:47.421826+00:00
-2026-05-06 18:19:47,977 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:19:48,182 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.759s at 2026-05-07T00:19:48.182179+00:00
-2026-05-06 18:19:54,412 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:54.412542+00:00
-2026-05-06 18:19:54,866 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:19:55,074 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.662s at 2026-05-07T00:19:55.074817+00:00
-2026-05-06 18:19:57,905 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:57.905487+00:00
-2026-05-06 18:19:58,384 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:19:58,598 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.692s at 2026-05-07T00:19:58.598145+00:00
-2026-05-06 18:19:59,918 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:59.918562+00:00
-2026-05-06 18:20:00,391 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:00,605 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.687s at 2026-05-07T00:20:00.605635+00:00
-2026-05-06 18:20:01,887 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:01.887221+00:00
-2026-05-06 18:20:02,339 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:02,550 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.663s at 2026-05-07T00:20:02.550706+00:00
-2026-05-06 18:20:04,982 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:04.982372+00:00
-2026-05-06 18:20:05,541 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:05,754 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.772s at 2026-05-07T00:20:05.753433+00:00
-2026-05-06 18:20:09,130 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:09.130132+00:00
-2026-05-06 18:20:09,706 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:09,918 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.788s at 2026-05-07T00:20:09.918209+00:00
-2026-05-06 18:20:13,606 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:13.606190+00:00
-2026-05-06 18:20:14,202 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:14,419 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.813s at 2026-05-07T00:20:14.419193+00:00
-2026-05-06 18:20:24,188 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:24.188464+00:00
-2026-05-06 18:20:24,558 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:24,768 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.580s at 2026-05-07T00:20:24.768332+00:00
-2026-05-06 18:20:31,993 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:31.993128+00:00
-2026-05-06 18:20:32,461 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:32,660 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.667s at 2026-05-07T00:20:32.660620+00:00
-2026-05-06 18:20:39,799 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:39.799176+00:00
-2026-05-06 18:20:40,213 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:40,415 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.616s at 2026-05-07T00:20:40.415329+00:00
-2026-05-06 18:20:48,557 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:48.557775+00:00
-2026-05-06 18:20:48,957 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:49,152 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.594s at 2026-05-07T00:20:49.152442+00:00
-2026-05-06 18:20:51,499 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:51.499668+00:00
-2026-05-06 18:20:51,887 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:52,080 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.581s at 2026-05-07T00:20:52.080875+00:00
-2026-05-06 18:20:58,550 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:58.550802+00:00
-2026-05-06 18:20:58,974 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:20:59,172 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.621s at 2026-05-07T00:20:59.172097+00:00
-2026-05-06 18:21:05,475 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:21:05.475735+00:00
-2026-05-06 18:21:05,968 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:21:06,170 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.695s at 2026-05-07T00:21:06.170299+00:00
-2026-05-06 18:21:58,411 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:21:58.411200+00:00
-2026-05-06 18:21:58,922 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:21:59,122 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.711s at 2026-05-07T00:21:59.122602+00:00
-2026-05-06 18:22:03,353 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:03.353237+00:00
-2026-05-06 18:22:03,666 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:22:03,899 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.546s at 2026-05-07T00:22:03.899330+00:00
-2026-05-06 18:22:18,857 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:18.857782+00:00
-2026-05-06 18:22:19,152 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:22:19,352 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.495s at 2026-05-07T00:22:19.351744+00:00
-2026-05-06 18:22:33,242 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:33.241502+00:00
-2026-05-06 18:22:33,608 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:22:33,808 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.566s at 2026-05-07T00:22:33.808058+00:00
-2026-05-06 18:22:46,303 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:46.303027+00:00
-2026-05-06 18:22:46,613 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:22:46,820 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.517s at 2026-05-07T00:22:46.820104+00:00
-2026-05-06 18:22:53,994 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:53.994710+00:00
-2026-05-06 18:22:54,335 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:22:54,531 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.538s at 2026-05-07T00:22:54.531877+00:00
-2026-05-06 18:23:03,058 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:23:03.058568+00:00
-2026-05-06 18:23:03,713 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:23:03,917 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.859s at 2026-05-07T00:23:03.917765+00:00
-2026-05-06 18:23:13,406 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:23:13.406391+00:00
-2026-05-06 18:23:13,942 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
-2026-05-06 18:23:13,967 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:23:14,176 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.771s at 2026-05-07T00:23:14.176983+00:00
-2026-05-06 18:23:56,519 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:23:56.519124+00:00
-2026-05-06 18:23:57,096 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:23:57,280 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.761s at 2026-05-07T00:23:57.280365+00:00
-2026-05-06 18:30:22,767 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-06 18:30:22,786 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 18:30:23,875 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-06 18:30:23,890 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 18:30:40,305 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-06 18:30:40,318 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 18:30:47,397 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:30:47.397798+00:00
-2026-05-06 18:30:47,398 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] preparing_image progress=12
-2026-05-06 18:30:47,494 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
-2026-05-06 18:30:47,495 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 18:30:50,214 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:30:52,639 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:30:52,643 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:30:52,644 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 18:30:53,251 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:30:55,145 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 18:30:55,156 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/ecb9300c-1e9f-4a3b-9c4a-3263e97e0a30 "HTTP/1.1 200 OK"
-2026-05-06 18:30:57,506 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:30:57,568 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:30:59,968 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/b5d0cc5e-3739-47c1-96d5-e2849a4fe991 "HTTP/1.1 200 OK"
-2026-05-06 18:30:59,972 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 18:31:02,313 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 18:31:04,749 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=b5d0cc5e-3739-47c1-96d5-e2849a4fe991 "HTTP/1.1 200 OK"
-2026-05-06 18:33:25,005 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\bdc55057e453f1e4793eccb7f3297d66322074e960cb173c3fcf63268faa1561\image.webp "HTTP/1.1 200 OK"
-2026-05-06 18:33:25,027 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🏙️ Fachada / Exterior motor=SAM Auto (Exteriores - Sin Prompts) mask_count=95
-2026-05-06 18:33:25,028 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] saving_masks progress=92
-2026-05-06 18:33:25,352 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] segments_meta saved (93 segments)
-2026-05-06 18:33:25,353 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] done mask_count=95
-2026-05-06 18:33:25,353 INFO backend.segmentation: [UPLOAD_BG] DONE 157.955s at 2026-05-07T00:33:25.353379+00:00
-2026-05-06 18:33:25,354 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 18:33:32,815 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:32.815130+00:00
-2026-05-06 18:33:33,172 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:33:33,554 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.739s at 2026-05-07T00:33:33.554031+00:00
-2026-05-06 18:33:36,147 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:36.147891+00:00
-2026-05-06 18:33:36,589 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
-2026-05-06 18:33:36,616 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:33:36,847 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.700s at 2026-05-07T00:33:36.847452+00:00
-2026-05-06 18:33:39,658 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:39.658618+00:00
-2026-05-06 18:33:40,173 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
-2026-05-06 18:33:40,198 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:33:40,445 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.787s at 2026-05-07T00:33:40.445326+00:00
-2026-05-06 18:33:42,787 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:42.787102+00:00
-2026-05-06 18:33:43,295 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:33:43,530 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.744s at 2026-05-07T00:33:43.530960+00:00
-2026-05-06 18:33:44,949 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:44.949548+00:00
-2026-05-06 18:33:45,490 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:33:45,716 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.768s at 2026-05-07T00:33:45.716664+00:00
-2026-05-06 18:33:53,000 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:53.000130+00:00
-2026-05-06 18:33:53,538 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:33:53,781 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.781s at 2026-05-07T00:33:53.781571+00:00
-2026-05-06 18:34:12,078 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:12.078767+00:00
-2026-05-06 18:34:12,759 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:34:12,996 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.918s at 2026-05-07T00:34:12.996206+00:00
-2026-05-06 18:34:25,880 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:25.880027+00:00
-2026-05-06 18:34:26,401 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:34:26,649 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.770s at 2026-05-07T00:34:26.649818+00:00
-2026-05-06 18:34:33,573 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:33.572267+00:00
-2026-05-06 18:34:33,888 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:34:34,124 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.551s at 2026-05-07T00:34:34.124108+00:00
-2026-05-06 18:34:38,104 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:38.104579+00:00
-2026-05-06 18:34:38,547 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:34:38,781 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.677s at 2026-05-07T00:34:38.781767+00:00
-2026-05-06 18:34:43,958 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:43.958224+00:00
-2026-05-06 18:34:44,396 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
-2026-05-06 18:34:44,422 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:34:44,657 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.700s at 2026-05-07T00:34:44.657499+00:00
-2026-05-06 18:34:50,537 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:50.537840+00:00
-2026-05-06 18:34:50,991 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.50, h_ratio=1.82)
-2026-05-06 18:34:51,019 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:34:51,263 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.725s at 2026-05-07T00:34:51.263124+00:00
-2026-05-06 18:34:56,797 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:56.797730+00:00
-2026-05-06 18:34:57,208 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:34:57,462 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.666s at 2026-05-07T00:34:57.462972+00:00
-2026-05-06 18:35:00,689 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:35:00.689108+00:00
-2026-05-06 18:35:01,074 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:35:01,329 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.641s at 2026-05-07T00:35:01.329788+00:00
-2026-05-06 18:35:02,869 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:35:02.869035+00:00
-2026-05-06 18:35:03,292 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.45)
-2026-05-06 18:35:03,313 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:35:03,548 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.679s at 2026-05-07T00:35:03.548094+00:00
-2026-05-06 18:35:09,675 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:35:09.675245+00:00
-2026-05-06 18:35:10,176 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.21, h_ratio=1.01)
-2026-05-06 18:35:10,210 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:35:10,449 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.775s at 2026-05-07T00:35:10.449920+00:00
-2026-05-06 18:35:57,783 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:35:57.783409+00:00
-2026-05-06 18:35:58,342 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
-2026-05-06 18:35:58,368 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:35:58,597 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.814s at 2026-05-07T00:35:58.597593+00:00
-2026-05-06 18:36:05,048 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:05.048300+00:00
-2026-05-06 18:36:05,424 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
-2026-05-06 18:36:05,446 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:36:05,683 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.635s at 2026-05-07T00:36:05.683990+00:00
-2026-05-06 18:36:09,348 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:09.348934+00:00
-2026-05-06 18:36:09,689 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:36:09,939 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.591s at 2026-05-07T00:36:09.939262+00:00
-2026-05-06 18:36:11,515 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:11.515772+00:00
-2026-05-06 18:36:11,864 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:36:12,115 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.600s at 2026-05-07T00:36:12.115522+00:00
-2026-05-06 18:36:14,119 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:14.119433+00:00
-2026-05-06 18:36:14,467 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:36:14,703 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.583s at 2026-05-07T00:36:14.703339+00:00
-2026-05-06 18:36:17,955 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:17.955143+00:00
-2026-05-06 18:36:18,323 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.50, h_ratio=1.82)
-2026-05-06 18:36:18,346 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:36:18,587 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.632s at 2026-05-07T00:36:18.587038+00:00
-2026-05-06 18:36:29,722 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:29.722755+00:00
-2026-05-06 18:36:30,041 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.21, h_ratio=1.01)
-2026-05-06 18:36:30,075 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:36:30,316 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.595s at 2026-05-07T00:36:30.316931+00:00
-2026-05-06 18:36:55,258 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:55.258246+00:00
-2026-05-06 18:36:55,839 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.21, h_ratio=1.01)
-2026-05-06 18:36:55,875 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:36:56,125 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.867s at 2026-05-07T00:36:56.124977+00:00
-2026-05-06 18:36:59,138 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:59.138564+00:00
-2026-05-06 18:36:59,725 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.45)
-2026-05-06 18:36:59,750 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-06 18:36:59,984 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.846s at 2026-05-07T00:36:59.984763+00:00
-2026-05-06 18:37:16,745 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:37:16.745961+00:00
-2026-05-06 18:37:16,745 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] preparing_image progress=12
-2026-05-06 18:37:16,797 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] segmenting_with_sam2 progress=30 estimated_seconds=94.01599999999999
-2026-05-06 18:37:16,798 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 18:37:19,202 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:37:21,617 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:37:21,620 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:37:21,623 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 18:37:21,755 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:37:24,077 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/09adaa1b-fd4b-4053-96e7-e3e0b7cb26b3 "HTTP/1.1 200 OK"
-2026-05-06 18:37:24,081 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 18:37:26,501 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:37:26,560 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:37:28,941 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/450ca127-bb6f-4e37-b304-d51b440a9dbd "HTTP/1.1 200 OK"
-2026-05-06 18:37:28,947 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 18:37:31,443 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 18:37:33,986 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=450ca127-bb6f-4e37-b304-d51b440a9dbd "HTTP/1.1 200 OK"
-2026-05-06 18:39:54,826 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\8fee556ace9ab88dababff8e3183ddda34f5b57dd22cd0c9c4270241d97fe1a7\image.webp "HTTP/1.1 200 OK"
-2026-05-06 18:39:54,847 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🏙️ Fachada / Exterior motor=SAM Auto (Exteriores - Sin Prompts) mask_count=91
-2026-05-06 18:39:54,847 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] saving_masks progress=92
-2026-05-06 18:39:55,291 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] segments_meta saved (90 segments)
-2026-05-06 18:39:55,291 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] done mask_count=91
-2026-05-06 18:39:55,292 INFO backend.segmentation: [UPLOAD_BG] DONE 158.546s at 2026-05-07T00:39:55.291225+00:00
-2026-05-06 18:39:55,292 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 18:40:28,080 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:28.080549+00:00
-2026-05-06 18:40:28,641 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-06 18:40:29,060 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.980s at 2026-05-07T00:40:29.060020+00:00
-2026-05-06 18:40:37,726 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:37.726439+00:00
-2026-05-06 18:40:38,269 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-06 18:40:38,656 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.930s at 2026-05-07T00:40:38.656587+00:00
-2026-05-06 18:40:41,361 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:41.361471+00:00
-2026-05-06 18:40:41,870 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-06 18:40:42,256 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.895s at 2026-05-07T00:40:42.255570+00:00
-2026-05-06 18:40:50,492 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:50.492837+00:00
-2026-05-06 18:40:51,018 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-06 18:40:51,365 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.872s at 2026-05-07T00:40:51.364239+00:00
-2026-05-06 18:40:53,275 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:53.275769+00:00
-2026-05-06 18:40:53,826 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-06 18:40:54,179 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.905s at 2026-05-07T00:40:54.179973+00:00
-2026-05-06 18:41:02,123 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:41:02.123703+00:00
-2026-05-06 18:41:02,497 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-06 18:41:02,880 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.756s at 2026-05-07T00:41:02.880196+00:00
-2026-05-06 18:41:13,602 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:41:13.602484+00:00
-2026-05-06 18:41:14,055 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-06 18:41:14,428 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.827s at 2026-05-07T00:41:14.428892+00:00
-2026-05-06 18:41:19,676 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:41:19.676717+00:00
-2026-05-06 18:41:20,113 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-06 18:41:20,484 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.808s at 2026-05-07T00:41:20.484587+00:00
-2026-05-06 18:41:28,383 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:41:28.383560+00:00
-2026-05-06 18:41:28,729 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-06 18:41:29,136 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.752s at 2026-05-07T00:41:29.136269+00:00
-2026-05-06 18:42:20,651 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:42:20.651898+00:00
-2026-05-06 18:42:20,652 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] preparing_image progress=12
-2026-05-06 18:42:20,720 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-06 18:42:20,722 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 18:42:23,169 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:42:25,513 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:42:25,518 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:42:25,523 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 18:42:25,648 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:42:27,979 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 18:42:28,011 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/eff4d6f4-a526-4e3c-885b-21716e034b5b "HTTP/1.1 200 OK"
-2026-05-06 18:42:30,320 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:42:30,384 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:42:32,775 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/bb6c3136-6f1c-4623-bf35-86865beea318 "HTTP/1.1 200 OK"
-2026-05-06 18:42:32,825 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 18:42:35,212 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 18:42:37,701 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=bb6c3136-6f1c-4623-bf35-86865beea318 "HTTP/1.1 200 OK"
-2026-05-06 18:43:12,742 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\bd5cc89cdf220f59a58e54c17de42ccd2fe478787be6fafda37778eaf1d6f8c0\image.webp "HTTP/1.1 200 OK"
-2026-05-06 18:43:12,768 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛋️ Interiores (Sala / Cuartos) motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=15
-2026-05-06 18:43:12,768 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] saving_masks progress=92
-2026-05-06 18:43:12,827 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] segments_meta saved (9 segments)
-2026-05-06 18:43:12,828 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] done mask_count=15
-2026-05-06 18:43:12,828 INFO backend.segmentation: [UPLOAD_BG] DONE 52.177s at 2026-05-07T00:43:12.828557+00:00
-2026-05-06 18:43:12,829 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 18:43:24,334 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:43:24.334962+00:00
-2026-05-06 18:43:24,892 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.41.58.jpg
-2026-05-06 18:43:25,127 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.792s at 2026-05-07T00:43:25.127393+00:00
-2026-05-06 18:45:52,139 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:45:52.139300+00:00
-2026-05-06 18:45:52,631 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
-2026-05-06 18:45:52,652 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.41.58.jpg
-2026-05-06 18:45:52,934 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.795s at 2026-05-07T00:45:52.934786+00:00
-2026-05-06 18:48:05,742 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:48:05.742257+00:00
-2026-05-06 18:48:05,742 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] preparing_image progress=12
-2026-05-06 18:48:05,805 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-06 18:48:05,806 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 18:48:08,161 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 18:48:10,524 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:48:10,528 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:48:10,529 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 18:48:10,657 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:48:12,980 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/7be43e9c-5bea-422d-bb06-60720d9880bf "HTTP/1.1 200 OK"
-2026-05-06 18:48:12,981 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 18:48:15,268 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:48:15,340 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:48:17,721 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/562af56b-498c-4c62-9020-b784b3cd3643 "HTTP/1.1 200 OK"
-2026-05-06 18:48:17,756 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 18:48:20,089 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 18:48:22,469 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=562af56b-498c-4c62-9020-b784b3cd3643 "HTTP/1.1 200 OK"
-2026-05-06 18:50:33,287 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\307e144a6a358b2b31461825d5a83d98d89d0a4426bbff036b53a58abbce6a7f\image.webp "HTTP/1.1 200 OK"
-2026-05-06 18:50:33,299 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=75
-2026-05-06 18:50:33,301 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] saving_masks progress=92
-2026-05-06 18:50:33,531 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] segments_meta saved (65 segments)
-2026-05-06 18:50:33,534 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] done mask_count=75
-2026-05-06 18:50:33,534 INFO backend.segmentation: [UPLOAD_BG] DONE 147.793s at 2026-05-07T00:50:33.534228+00:00
-2026-05-06 18:50:33,535 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 18:50:43,317 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:50:43.317662+00:00
-2026-05-06 18:50:43,744 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.18, h_ratio=287.00)
-2026-05-06 18:50:43,761 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:50:43,971 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.654s at 2026-05-07T00:50:43.971226+00:00
-2026-05-06 18:50:48,879 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:50:48.879893+00:00
-2026-05-06 18:50:49,294 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:50:49,529 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.649s at 2026-05-07T00:50:49.529626+00:00
-2026-05-06 18:50:57,857 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:50:57.857319+00:00
-2026-05-06 18:50:58,384 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=1.27)
-2026-05-06 18:50:58,407 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:50:58,621 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.764s at 2026-05-07T00:50:58.621573+00:00
-2026-05-06 18:51:06,144 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:51:06.144106+00:00
-2026-05-06 18:51:06,633 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.25, h_ratio=1.00)
-2026-05-06 18:51:06,651 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:51:06,863 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.719s at 2026-05-07T00:51:06.863196+00:00
-2026-05-06 18:51:15,682 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:51:15.682186+00:00
-2026-05-06 18:51:16,277 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
-2026-05-06 18:51:16,298 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:51:16,515 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.833s at 2026-05-07T00:51:16.515186+00:00
-2026-05-06 18:51:19,654 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:51:19.654232+00:00
-2026-05-06 18:51:19,971 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
-2026-05-06 18:51:19,990 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:51:20,208 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.555s at 2026-05-07T00:51:20.208584+00:00
-2026-05-06 18:52:00,456 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:00.456384+00:00
-2026-05-06 18:52:00,996 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=292.55)
-2026-05-06 18:52:01,022 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:52:01,244 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.788s at 2026-05-07T00:52:01.244355+00:00
-2026-05-06 18:52:26,614 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:26.614595+00:00
-2026-05-06 18:52:27,072 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
-2026-05-06 18:52:27,091 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:52:27,309 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.695s at 2026-05-07T00:52:27.309474+00:00
-2026-05-06 18:52:31,418 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:31.418579+00:00
-2026-05-06 18:52:31,917 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
-2026-05-06 18:52:31,937 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:52:32,167 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.748s at 2026-05-07T00:52:32.167442+00:00
-2026-05-06 18:52:36,908 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:36.908697+00:00
-2026-05-06 18:52:37,340 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
-2026-05-06 18:52:37,360 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:52:37,571 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.663s at 2026-05-07T00:52:37.571758+00:00
-2026-05-06 18:52:42,394 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:42.394838+00:00
-2026-05-06 18:52:42,800 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:52:43,012 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.618s at 2026-05-07T00:52:43.012733+00:00
-2026-05-06 18:53:17,599 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:17.599012+00:00
-2026-05-06 18:53:18,767 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:53:19,517 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.918s at 2026-05-07T00:53:19.517003+00:00
-2026-05-06 18:53:20,941 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:20.941029+00:00
-2026-05-06 18:53:22,268 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.18, h_ratio=287.00)
-2026-05-06 18:53:22,309 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:53:22,958 INFO backend.segmentation: [APPLY_TEXTURE] DONE 2.017s at 2026-05-07T00:53:22.958657+00:00
-2026-05-06 18:53:26,815 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:26.815426+00:00
-2026-05-06 18:53:27,767 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.18, h_ratio=287.00)
-2026-05-06 18:53:27,822 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:53:28,496 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.681s at 2026-05-07T00:53:28.496136+00:00
-2026-05-06 18:53:29,211 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:29.211502+00:00
-2026-05-06 18:53:30,092 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:53:30,714 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.503s at 2026-05-07T00:53:30.714065+00:00
-2026-05-06 18:53:43,274 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:43.274502+00:00
-2026-05-06 18:53:44,185 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.80)
-2026-05-06 18:53:44,258 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 18:53:44,915 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.642s at 2026-05-07T00:53:44.915473+00:00
-2026-05-06 18:56:42,127 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-06 18:56:42,164 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 18:56:55,483 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:56:55.483048+00:00
-2026-05-06 18:56:55,487 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] preparing_image progress=12
-2026-05-06 18:56:55,916 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-06 18:56:55,930 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-06 18:57:00,068 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-06 18:57:01,629 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:57:01,716 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 18:57:01,731 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 18:57:02,949 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:57:03,037 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/a5e246b1-7256-4e47-bd59-4324d860981a "HTTP/1.1 200 OK"
-2026-05-06 18:57:04,851 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 18:57:08,278 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 18:57:08,445 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 18:57:11,795 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/80c98c2b-f464-4c63-be57-df896c3ca445 "HTTP/1.1 200 OK"
-2026-05-06 18:57:11,848 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 18:57:14,425 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 18:57:16,934 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=80c98c2b-f464-4c63-be57-df896c3ca445 "HTTP/1.1 200 OK"
-2026-05-06 18:59:19,174 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\307e144a6a358b2b31461825d5a83d98d89d0a4426bbff036b53a58abbce6a7f\image.webp "HTTP/1.1 200 OK"
-2026-05-06 18:59:19,199 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=75
-2026-05-06 18:59:19,201 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] saving_masks progress=92
-2026-05-06 18:59:19,479 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] segments_meta saved (65 segments)
-2026-05-06 18:59:19,480 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] done mask_count=75
-2026-05-06 18:59:19,481 INFO backend.segmentation: [UPLOAD_BG] DONE 143.997s at 2026-05-07T00:59:19.481114+00:00
-2026-05-06 18:59:19,481 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:00:44,615 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-06 19:00:44,631 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 19:00:54,117 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:00:54.117066+00:00
-2026-05-06 19:00:54,118 INFO backend.segmentation: [JOB 857272f2f2794d61a8320ba9fc0a0b9c] preparing_image progress=12
-2026-05-06 19:00:54,227 INFO backend.segmentation: [JOB 857272f2f2794d61a8320ba9fc0a0b9c] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-06 19:00:54,228 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-06 19:00:55,352 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-06 19:00:55,962 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:00:56,025 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:00:56,027 ERROR backend.segmentation: [JOB 857272f2f2794d61a8320ba9fc0a0b9c] failed: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 87, in segment_via_gradio_sync
-    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
-RuntimeError: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
-2026-05-06 19:00:56,028 INFO backend.segmentation: [UPLOAD_BG] DONE 1.912s at 2026-05-07T01:00:56.028803+00:00
-2026-05-06 19:00:56,029 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:00:56,598 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:00:56,674 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/4209bbfb-31fd-49ce-8bfa-3bd088857ca8 "HTTP/1.1 200 OK"
-2026-05-06 19:01:51,403 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:01:51.403342+00:00
-2026-05-06 19:01:51,403 INFO backend.segmentation: [JOB 3767a577a5df43449aa13600c7a14d0c] preparing_image progress=12
-2026-05-06 19:01:51,499 INFO backend.segmentation: [JOB 3767a577a5df43449aa13600c7a14d0c] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-06 19:01:51,499 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-06 19:01:52,190 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-06 19:01:52,799 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:01:52,856 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:01:52,857 ERROR backend.segmentation: [JOB 3767a577a5df43449aa13600c7a14d0c] failed: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 87, in segment_via_gradio_sync
-    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
-RuntimeError: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
-2026-05-06 19:01:52,858 INFO backend.segmentation: [UPLOAD_BG] DONE 1.455s at 2026-05-07T01:01:52.858105+00:00
-2026-05-06 19:01:52,858 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:01:53,023 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:01:53,494 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/2c3065a9-d718-45a7-8b87-980f332c885e "HTTP/1.1 200 OK"
-2026-05-06 19:17:22,918 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:17:22.918521+00:00
-2026-05-06 19:17:22,918 INFO backend.segmentation: [JOB 2f51a6c8a71e4a1abde690771af923c8] preparing_image progress=12
-2026-05-06 19:17:23,012 INFO backend.segmentation: [JOB 2f51a6c8a71e4a1abde690771af923c8] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-06 19:17:23,013 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-06 19:17:23,790 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-06 19:17:24,541 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:17:24,595 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:17:24,596 ERROR backend.segmentation: [JOB 2f51a6c8a71e4a1abde690771af923c8] failed: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 87, in segment_via_gradio_sync
-    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
-RuntimeError: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
-2026-05-06 19:17:24,598 INFO backend.segmentation: [UPLOAD_BG] DONE 1.680s at 2026-05-07T01:17:24.598238+00:00
-2026-05-06 19:17:24,599 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:17:24,970 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:17:25,584 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/0dc57ee9-5e05-4959-abe6-f013266fa198 "HTTP/1.1 200 OK"
-2026-05-06 19:17:42,518 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-06 19:17:42,533 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 19:17:51,915 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:17:51.915900+00:00
-2026-05-06 19:17:51,915 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] preparing_image progress=12
-2026-05-06 19:17:52,074 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-06 19:17:52,077 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 19:17:55,274 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 19:17:57,503 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:17:57,507 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:17:57,507 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 19:17:57,893 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:17:59,796 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/f7a98d0a-9306-4dbc-93b7-601ff79c950e "HTTP/1.1 200 OK"
-2026-05-06 19:17:59,799 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 19:18:02,032 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:18:02,104 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:18:04,304 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/2d410380-be25-4691-8948-df224948856b "HTTP/1.1 200 OK"
-2026-05-06 19:18:04,308 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 19:18:06,507 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 19:18:08,705 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=2d410380-be25-4691-8948-df224948856b "HTTP/1.1 200 OK"
-2026-05-06 19:20:30,315 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\ba6745bca4b9348c165f22fc4ea78e92894e852d9a17a054a2f8f302e7eede49\image.webp "HTTP/1.1 200 OK"
-2026-05-06 19:20:30,336 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=108
-2026-05-06 19:20:30,342 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] saving_masks progress=92
-2026-05-06 19:20:30,735 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] segments_meta saved (94 segments)
-2026-05-06 19:20:30,736 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] done mask_count=108
-2026-05-06 19:20:30,736 INFO backend.segmentation: [UPLOAD_BG] DONE 158.821s at 2026-05-07T01:20:30.736356+00:00
-2026-05-06 19:20:30,736 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:20:54,598 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:20:54.598398+00:00
-2026-05-06 19:20:55,454 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.22, h_ratio=1.42)
-2026-05-06 19:20:55,479 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:20:55,852 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.253s at 2026-05-07T01:20:55.852286+00:00
-2026-05-06 19:21:02,878 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:02.878905+00:00
-2026-05-06 19:21:03,409 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.03)
-2026-05-06 19:21:03,430 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:21:03,652 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.774s at 2026-05-07T01:21:03.652782+00:00
-2026-05-06 19:21:04,556 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:04.556252+00:00
-2026-05-06 19:21:05,073 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:21:05,304 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.749s at 2026-05-07T01:21:05.304889+00:00
-2026-05-06 19:21:09,382 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:09.382363+00:00
-2026-05-06 19:21:09,876 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:21:10,099 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.717s at 2026-05-07T01:21:10.099363+00:00
-2026-05-06 19:21:12,168 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:12.168998+00:00
-2026-05-06 19:21:12,676 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:21:12,902 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.734s at 2026-05-07T01:21:12.902123+00:00
-2026-05-06 19:21:17,676 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:17.676155+00:00
-2026-05-06 19:21:18,186 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:21:18,406 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.730s at 2026-05-07T01:21:18.406221+00:00
-2026-05-06 19:21:28,033 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:28.033139+00:00
-2026-05-06 19:21:28,602 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.04, h_ratio=30.15)
-2026-05-06 19:21:28,621 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:21:28,847 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.815s at 2026-05-07T01:21:28.847576+00:00
-2026-05-06 19:21:37,759 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:37.759732+00:00
-2026-05-06 19:21:38,294 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.08, h_ratio=2.31)
-2026-05-06 19:21:38,324 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:21:38,542 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.783s at 2026-05-07T01:21:38.542862+00:00
-2026-05-06 19:21:45,517 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:45.517095+00:00
-2026-05-06 19:21:45,886 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.45, h_ratio=1.00)
-2026-05-06 19:21:45,904 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:21:46,127 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.610s at 2026-05-07T01:21:46.127155+00:00
-2026-05-06 19:21:47,910 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:47.910379+00:00
-2026-05-06 19:21:48,240 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.03)
-2026-05-06 19:21:48,258 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:21:48,550 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.640s at 2026-05-07T01:21:48.550311+00:00
-2026-05-06 19:22:01,490 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:01.490043+00:00
-2026-05-06 19:22:01,800 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.40, h_ratio=1.19)
-2026-05-06 19:22:01,820 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:22:02,038 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.549s at 2026-05-07T01:22:02.038685+00:00
-2026-05-06 19:22:14,676 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:14.676095+00:00
-2026-05-06 19:22:14,981 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.24)
-2026-05-06 19:22:15,000 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:22:15,217 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.542s at 2026-05-07T01:22:15.217076+00:00
-2026-05-06 19:22:18,393 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:18.393596+00:00
-2026-05-06 19:22:18,727 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=3.19, h_ratio=1.08)
-2026-05-06 19:22:18,748 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:22:18,967 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.573s at 2026-05-07T01:22:18.967471+00:00
-2026-05-06 19:22:20,453 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:20.453051+00:00
-2026-05-06 19:22:20,787 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.25, h_ratio=1.00)
-2026-05-06 19:22:20,807 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:22:21,031 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.578s at 2026-05-07T01:22:21.031223+00:00
-2026-05-06 19:22:21,815 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:21.815779+00:00
-2026-05-06 19:22:22,122 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:22:22,328 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.512s at 2026-05-07T01:22:22.328994+00:00
-2026-05-06 19:23:32,211 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:23:32.211857+00:00
-2026-05-06 19:23:32,509 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:23:32,730 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.518s at 2026-05-07T01:23:32.730152+00:00
-2026-05-06 19:23:38,227 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:23:38.227849+00:00
-2026-05-06 19:23:38,534 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:23:38,859 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.632s at 2026-05-07T01:23:38.859962+00:00
-2026-05-06 19:26:19,159 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:26:19.158670+00:00
-2026-05-06 19:26:19,159 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] preparing_image progress=12
-2026-05-06 19:26:19,236 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-06 19:26:19,237 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 19:26:21,653 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 19:26:24,033 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:26:24,036 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:26:24,038 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 19:26:24,154 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:26:25,313 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:26:25.313791+00:00
-2026-05-06 19:26:25,314 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] preparing_image progress=12
-2026-05-06 19:26:25,380 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-06 19:26:25,382 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 19:26:26,501 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 19:26:26,514 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/253a1026-e06a-44b1-a442-8e6324d90510 "HTTP/1.1 200 OK"
-2026-05-06 19:26:27,773 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 19:26:28,745 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:26:28,804 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:26:29,998 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:26:30,000 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:26:30,000 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 19:26:30,064 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:26:31,044 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/ef93ac7c-1d1e-49c1-a68d-1e312c61dbd6 "HTTP/1.1 200 OK"
-2026-05-06 19:26:31,045 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 19:26:32,302 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/f94b5838-f8e4-404c-b91a-44c18e0fd13d "HTTP/1.1 200 OK"
-2026-05-06 19:26:32,303 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 19:26:33,276 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 19:26:34,511 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:26:34,571 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:26:35,511 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=ef93ac7c-1d1e-49c1-a68d-1e312c61dbd6 "HTTP/1.1 200 OK"
-2026-05-06 19:26:36,930 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/f61335a1-cff8-4529-990e-d2408f346c4b "HTTP/1.1 200 OK"
-2026-05-06 19:26:36,985 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 19:26:39,872 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 19:26:42,392 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=f61335a1-cff8-4529-990e-d2408f346c4b "HTTP/1.1 200 OK"
-2026-05-06 19:28:56,877 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\6ab9a3531b560f214c105197415e0af0532fde83c6bfe58ed1c0313fcd859477\image.webp "HTTP/1.1 200 OK"
-2026-05-06 19:28:56,897 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=131
-2026-05-06 19:28:56,898 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] saving_masks progress=92
-2026-05-06 19:28:57,283 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] segments_meta saved (100 segments)
-2026-05-06 19:28:57,286 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] done mask_count=131
-2026-05-06 19:28:57,290 INFO backend.segmentation: [UPLOAD_BG] DONE 158.131s at 2026-05-07T01:28:57.289976+00:00
-2026-05-06 19:28:57,290 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:31:09,088 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\0fad9dd5d2167e81275663b268759f254ced3260a00596d8148c4b82b18a447b\image.webp "HTTP/1.1 200 OK"
-2026-05-06 19:31:09,105 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=108
-2026-05-06 19:31:09,106 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] saving_masks progress=92
-2026-05-06 19:31:09,387 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] segments_meta saved (83 segments)
-2026-05-06 19:31:09,388 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] done mask_count=108
-2026-05-06 19:31:09,389 INFO backend.segmentation: [UPLOAD_BG] DONE 284.075s at 2026-05-07T01:31:09.389195+00:00
-2026-05-06 19:31:09,389 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:31:25,769 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:25.769543+00:00
-2026-05-06 19:31:26,322 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.38, h_ratio=1.21)
-2026-05-06 19:31:26,345 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:31:26,561 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.791s at 2026-05-07T01:31:26.561149+00:00
-2026-05-06 19:31:30,093 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:30.093130+00:00
-2026-05-06 19:31:30,610 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=73.16, h_ratio=1.19)
-2026-05-06 19:31:30,630 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:31:30,852 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.760s at 2026-05-07T01:31:30.852656+00:00
-2026-05-06 19:31:32,510 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:32.510227+00:00
-2026-05-06 19:31:33,024 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:31:33,261 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.751s at 2026-05-07T01:31:33.261864+00:00
-2026-05-06 19:31:34,688 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:34.688411+00:00
-2026-05-06 19:31:35,245 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.82, h_ratio=1.04)
-2026-05-06 19:31:35,273 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:31:35,585 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.897s at 2026-05-07T01:31:35.585466+00:00
-2026-05-06 19:31:37,308 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:37.308846+00:00
-2026-05-06 19:31:37,845 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:31:38,063 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.754s at 2026-05-07T01:31:38.063134+00:00
-2026-05-06 19:31:39,470 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:39.470279+00:00
-2026-05-06 19:31:40,021 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.28)
-2026-05-06 19:31:40,041 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:31:40,265 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.795s at 2026-05-07T01:31:40.265221+00:00
-2026-05-06 19:32:07,072 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:32:07.072763+00:00
-2026-05-06 19:32:07,073 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] preparing_image progress=12
-2026-05-06 19:32:07,137 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-06 19:32:07,137 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 19:32:09,529 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 19:32:11,885 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:32:11,888 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:32:11,888 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 19:32:12,020 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:32:14,326 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/be75cb37-7b07-4bcc-8b3d-efdee17bbc4a "HTTP/1.1 200 OK"
-2026-05-06 19:32:14,327 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 19:32:16,703 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:32:16,767 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:32:19,164 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/c6911703-f527-40a3-889a-6c77edcd8d21 "HTTP/1.1 200 OK"
-2026-05-06 19:32:19,202 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 19:32:21,606 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 19:32:24,189 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=c6911703-f527-40a3-889a-6c77edcd8d21 "HTTP/1.1 200 OK"
-2026-05-06 19:34:39,587 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\21889eae2fc6a2146ef59d302265bd9c57edff263c81a559c184526108f142d6\image.webp "HTTP/1.1 200 OK"
-2026-05-06 19:34:39,600 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=160
-2026-05-06 19:34:39,601 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] saving_masks progress=92
-2026-05-06 19:34:39,913 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] segments_meta saved (109 segments)
-2026-05-06 19:34:39,916 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] done mask_count=160
-2026-05-06 19:34:39,916 INFO backend.segmentation: [UPLOAD_BG] DONE 152.844s at 2026-05-07T01:34:39.916411+00:00
-2026-05-06 19:34:39,917 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:34:58,860 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:34:58.860869+00:00
-2026-05-06 19:34:59,384 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=2.09)
-2026-05-06 19:34:59,410 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 19:34:59,597 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.737s at 2026-05-07T01:34:59.597723+00:00
-2026-05-06 19:35:04,315 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:35:04.314184+00:00
-2026-05-06 19:35:04,828 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 19:35:05,031 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.717s at 2026-05-07T01:35:05.031564+00:00
-2026-05-06 19:35:07,195 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:35:07.195100+00:00
-2026-05-06 19:35:07,775 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 19:35:07,959 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.764s at 2026-05-07T01:35:07.959507+00:00
-2026-05-06 19:35:16,717 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:35:16.717055+00:00
-2026-05-06 19:35:17,292 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.12, h_ratio=1.24)
-2026-05-06 19:35:17,313 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 19:35:17,489 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.772s at 2026-05-07T01:35:17.489338+00:00
-2026-05-06 19:35:21,896 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:35:21.896286+00:00
-2026-05-06 19:35:22,460 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=2.25)
-2026-05-06 19:35:22,477 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 19:35:22,652 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.756s at 2026-05-07T01:35:22.652693+00:00
-2026-05-06 19:35:31,661 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:35:31.661603+00:00
-2026-05-06 19:35:31,662 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] preparing_image progress=12
-2026-05-06 19:35:31,730 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-06 19:35:31,730 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 19:35:34,148 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 19:35:36,513 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:35:36,516 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:35:36,517 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 19:35:36,647 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:35:38,956 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/bee4b6dd-5fb5-46e5-b79e-991fbe34799b "HTTP/1.1 200 OK"
-2026-05-06 19:35:38,972 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 19:35:41,374 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:35:41,437 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:35:43,849 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 19:35:43,862 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/d8a928aa-2516-473b-85f5-9bf75d1e3f77 "HTTP/1.1 200 OK"
-2026-05-06 19:35:46,265 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 19:35:48,784 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=d8a928aa-2516-473b-85f5-9bf75d1e3f77 "HTTP/1.1 200 OK"
-2026-05-06 19:38:08,031 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\21889eae2fc6a2146ef59d302265bd9c57edff263c81a559c184526108f142d6\image.webp "HTTP/1.1 200 OK"
-2026-05-06 19:38:08,050 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=160
-2026-05-06 19:38:08,051 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] saving_masks progress=92
-2026-05-06 19:38:08,352 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] segments_meta saved (109 segments)
-2026-05-06 19:38:08,353 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] done mask_count=160
-2026-05-06 19:38:08,353 INFO backend.segmentation: [UPLOAD_BG] DONE 156.692s at 2026-05-07T01:38:08.353974+00:00
-2026-05-06 19:38:08,353 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:38:54,725 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:38:54.725946+00:00
-2026-05-06 19:38:55,301 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 19:38:55,485 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.760s at 2026-05-07T01:38:55.485826+00:00
-2026-05-06 19:39:02,094 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:39:02.094076+00:00
-2026-05-06 19:39:02,676 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 19:39:02,898 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.805s at 2026-05-07T01:39:02.898407+00:00
-2026-05-06 19:39:05,813 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:39:05.813452+00:00
-2026-05-06 19:39:05,813 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] preparing_image progress=12
-2026-05-06 19:39:05,890 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-06 19:39:05,891 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-06 19:39:08,294 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-06 19:39:10,647 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:39:10,650 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:39:10,650 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
-2026-05-06 19:39:10,769 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:39:13,127 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/4460ecf1-ea82-47e4-a1d6-b5bc3d4c71d2 "HTTP/1.1 200 OK"
-2026-05-06 19:39:13,130 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-06 19:39:15,535 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:39:15,595 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:39:17,956 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/97643e3a-0304-4e2b-8472-769ee08d3b1b "HTTP/1.1 200 OK"
-2026-05-06 19:39:17,959 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 19:39:20,370 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 19:39:22,889 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=97643e3a-0304-4e2b-8472-769ee08d3b1b "HTTP/1.1 200 OK"
-2026-05-06 19:41:28,459 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\76d9b286b2fcdbd80abdc7e15a0a7f680d3f4fbf2b90ca4d6d6f24bbf1545d1c\image.webp "HTTP/1.1 200 OK"
-2026-05-06 19:41:28,470 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=166
-2026-05-06 19:41:28,471 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] saving_masks progress=92
-2026-05-06 19:41:28,681 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] segments_meta saved (137 segments)
-2026-05-06 19:41:28,681 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] done mask_count=166
-2026-05-06 19:41:28,682 INFO backend.segmentation: [UPLOAD_BG] DONE 142.868s at 2026-05-07T01:41:28.682118+00:00
-2026-05-06 19:41:28,682 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:50:21,809 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-06 19:50:21,823 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-06 19:50:26,378 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:50:26.378489+00:00
-2026-05-06 19:50:26,384 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] preparing_image progress=12
-2026-05-06 19:50:26,471 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-06 19:50:26,472 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-06 19:50:27,262 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-06 19:50:27,877 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:50:27,893 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-06 19:50:27,897 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-06 19:50:28,465 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:50:28,587 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/5aad3e23-2d4a-4ff2-b2d1-2ff407eed648 "HTTP/1.1 200 OK"
-2026-05-06 19:50:28,729 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-06 19:50:29,178 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 19:50:29,318 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 19:50:30,078 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 19:50:30,375 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/bf131e2f-59cc-4bcb-90cf-326d0eed81f6 "HTTP/1.1 200 OK"
-2026-05-06 19:50:30,577 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 19:50:30,996 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=bf131e2f-59cc-4bcb-90cf-326d0eed81f6 "HTTP/1.1 200 OK"
-2026-05-06 19:56:12,792 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/file=/tmp/gradio/ca352ba59707f92cf2713ac194ff5f07119898301b89fe92d0d511d51a9854a3/image.webp "HTTP/1.1 200 OK"
-2026-05-06 19:56:12,902 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=108
-2026-05-06 19:56:12,904 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] saving_masks progress=92
-2026-05-06 19:56:13,248 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] segments_meta saved (94 segments)
-2026-05-06 19:56:13,248 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] done mask_count=108
-2026-05-06 19:56:13,248 INFO backend.segmentation: [UPLOAD_BG] DONE 346.870s at 2026-05-07T01:56:13.248662+00:00
-2026-05-06 19:56:13,249 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 19:56:28,190 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:28.190920+00:00
-2026-05-06 19:56:28,586 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.89, h_ratio=1.16)
-2026-05-06 19:56:28,610 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:56:28,946 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.756s at 2026-05-07T01:56:28.946955+00:00
-2026-05-06 19:56:32,308 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:32.308758+00:00
-2026-05-06 19:56:32,636 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:56:32,842 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.534s at 2026-05-07T01:56:32.842046+00:00
-2026-05-06 19:56:38,221 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:38.221694+00:00
-2026-05-06 19:56:38,549 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.45, h_ratio=1.00)
-2026-05-06 19:56:38,582 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:56:38,797 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.576s at 2026-05-07T01:56:38.797605+00:00
-2026-05-06 19:56:40,976 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:40.976482+00:00
-2026-05-06 19:56:41,307 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.03)
-2026-05-06 19:56:41,347 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:56:41,596 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.620s at 2026-05-07T01:56:41.596887+00:00
-2026-05-06 19:56:45,053 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:45.053373+00:00
-2026-05-06 19:56:45,558 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:56:45,750 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.697s at 2026-05-07T01:56:45.750699+00:00
-2026-05-06 19:56:48,758 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:48.757132+00:00
-2026-05-06 19:56:49,268 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.08, h_ratio=2.31)
-2026-05-06 19:56:49,292 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:56:49,508 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.751s at 2026-05-07T01:56:49.508898+00:00
-2026-05-06 19:56:53,597 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:53.597538+00:00
-2026-05-06 19:56:54,195 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.45, h_ratio=1.00)
-2026-05-06 19:56:54,219 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-06 19:56:54,438 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.841s at 2026-05-07T01:56:54.438299+00:00
-2026-05-06 20:00:21,372 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T02:00:21.372294+00:00
-2026-05-06 20:00:21,372 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] preparing_image progress=12
-2026-05-06 20:00:21,437 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-06 20:00:21,437 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-06 20:00:22,134 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-06 20:00:22,726 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-06 20:00:22,915 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-06 20:00:23,461 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/c7959aba-7eb6-4ecb-81ad-712329ac5c7c "HTTP/1.1 200 OK"
-2026-05-06 20:00:23,560 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-06 20:00:24,012 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-06 20:00:24,861 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=c7959aba-7eb6-4ecb-81ad-712329ac5c7c "HTTP/1.1 200 OK"
-2026-05-06 20:00:42,409 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/b16694b4215c6ddd7ab507195e91a516ff5142807df0ec7e847eb878eb7c1ab3/image.webp "HTTP/1.1 200 OK"
-2026-05-06 20:00:42,518 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=131
-2026-05-06 20:00:42,519 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] saving_masks progress=92
-2026-05-06 20:00:42,727 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] segments_meta saved (114 segments)
-2026-05-06 20:00:42,727 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] done mask_count=131
-2026-05-06 20:00:42,727 INFO backend.segmentation: [UPLOAD_BG] DONE 21.356s at 2026-05-07T02:00:42.727446+00:00
-2026-05-06 20:00:42,728 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-06 20:17:14,645 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:14.645451+00:00
-2026-05-06 20:17:15,135 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=1.09)
-2026-05-06 20:17:15,152 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 20:17:15,329 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.684s at 2026-05-07T02:17:15.329979+00:00
-2026-05-06 20:17:15,339 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:15.339985+00:00
-2026-05-06 20:17:15,656 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=1.09)
-2026-05-06 20:17:15,678 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 20:17:15,875 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.535s at 2026-05-07T02:17:15.875096+00:00
-2026-05-06 20:17:34,601 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:34.601321+00:00
-2026-05-06 20:17:34,920 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 20:17:35,110 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.510s at 2026-05-07T02:17:35.110889+00:00
-2026-05-06 20:17:42,322 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:42.322700+00:00
-2026-05-06 20:17:42,821 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 20:17:42,999 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.677s at 2026-05-07T02:17:42.998640+00:00
-2026-05-06 20:17:46,209 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:46.209208+00:00
-2026-05-06 20:17:46,792 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=1.09)
-2026-05-06 20:17:46,811 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-06 20:17:46,990 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.781s at 2026-05-07T02:17:46.990848+00:00
-2026-05-07 12:51:24,606 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 12:51:24,620 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 12:51:38,487 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T18:51:38.487778+00:00
-2026-05-07 12:51:38,488 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] preparing_image progress=12
-2026-05-07 12:51:38,722 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 12:51:38,722 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 12:51:57,921 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 12:51:58,597 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 12:51:59,277 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 12:51:59,382 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/94b31a0d-c4b3-4776-9bf3-feb7cfb2deb5 "HTTP/1.1 200 OK"
-2026-05-07 12:51:59,569 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 12:52:00,104 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 12:52:00,784 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=94b31a0d-c4b3-4776-9bf3-feb7cfb2deb5 "HTTP/1.1 200 OK"
-2026-05-07 12:52:21,780 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/58f73381cbe3266caa6d35a2c12cb77e720345122d5cf9f7cdb96e041ceca7c9/image.webp "HTTP/1.1 200 OK"
-2026-05-07 12:52:21,889 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=108
-2026-05-07 12:52:21,890 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] saving_masks progress=92
-2026-05-07 12:52:22,192 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] segments_meta saved (94 segments)
-2026-05-07 12:52:22,192 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] done mask_count=108
-2026-05-07 12:52:22,192 INFO backend.segmentation: [UPLOAD_BG] DONE 43.706s at 2026-05-07T18:52:22.192480+00:00
-2026-05-07 12:52:22,193 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 12:56:10,928 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T18:56:10.928142+00:00
-2026-05-07 12:56:10,929 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] preparing_image progress=12
-2026-05-07 12:56:10,997 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 12:56:10,997 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 12:56:11,625 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 12:56:12,229 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 12:56:12,412 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 12:56:12,966 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/ed1495a1-4a2c-4fab-a409-975c2768b89c "HTTP/1.1 200 OK"
-2026-05-07 12:56:13,063 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 12:56:13,579 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 12:56:14,152 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=ed1495a1-4a2c-4fab-a409-975c2768b89c "HTTP/1.1 200 OK"
-2026-05-07 12:56:25,727 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/58f73381cbe3266caa6d35a2c12cb77e720345122d5cf9f7cdb96e041ceca7c9/image.webp "HTTP/1.1 200 OK"
-2026-05-07 12:56:25,845 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=108
-2026-05-07 12:56:25,845 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] saving_masks progress=92
-2026-05-07 12:56:26,112 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] segments_meta saved (94 segments)
-2026-05-07 12:56:26,112 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] done mask_count=108
-2026-05-07 12:56:26,112 INFO backend.segmentation: [UPLOAD_BG] DONE 15.184s at 2026-05-07T18:56:26.112231+00:00
-2026-05-07 12:56:26,112 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 13:01:56,800 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T19:01:56.800564+00:00
-2026-05-07 13:01:56,801 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] preparing_image progress=12
-2026-05-07 13:01:56,873 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 13:01:56,874 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 13:01:57,517 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 13:01:58,135 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 13:01:58,320 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 13:01:58,810 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/5c3e334b-800c-4d78-93b4-35d66a611f5d "HTTP/1.1 200 OK"
-2026-05-07 13:01:58,963 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 13:01:59,514 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 13:02:00,027 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=5c3e334b-800c-4d78-93b4-35d66a611f5d "HTTP/1.1 200 OK"
-2026-05-07 13:02:11,627 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/58f73381cbe3266caa6d35a2c12cb77e720345122d5cf9f7cdb96e041ceca7c9/image.webp "HTTP/1.1 200 OK"
-2026-05-07 13:02:11,743 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=108
-2026-05-07 13:02:11,747 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] saving_masks progress=92
-2026-05-07 13:02:12,035 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] segments_meta saved (94 segments)
-2026-05-07 13:02:12,035 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] done mask_count=108
-2026-05-07 13:02:12,035 INFO backend.segmentation: [UPLOAD_BG] DONE 15.235s at 2026-05-07T19:02:12.035158+00:00
-2026-05-07 13:02:12,036 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 14:54:46,839 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 14:54:46,873 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 14:55:18,464 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T20:55:18.464808+00:00
-2026-05-07 14:55:18,465 INFO backend.segmentation: [JOB e2978c252391482ea410013edd5dd614] preparing_image progress=12
-2026-05-07 14:55:18,684 INFO backend.segmentation: [JOB e2978c252391482ea410013edd5dd614] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 14:55:18,684 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 14:55:20,941 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 14:55:21,523 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 14:55:22,147 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 14:55:22,266 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/044411e2-1c1d-423c-8a2b-1bf8aa03347d "HTTP/1.1 200 OK"
-2026-05-07 14:55:22,418 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 14:55:22,953 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 14:55:23,627 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=044411e2-1c1d-423c-8a2b-1bf8aa03347d "HTTP/1.1 200 OK"
-2026-05-07 14:55:38,599 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/e46ee411d94ec777ba35b9e436d075e4a9639d5f1e564687b887320d75811f38/image.webp "HTTP/1.1 200 OK"
-2026-05-07 14:55:38,603 WARNING services.gradio_client_service: GPU Space failed (Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^), trying CPU fallback...
-2026-05-07 14:55:38,604 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-07 14:55:39,263 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 14:55:39,888 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 14:55:40,067 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 14:55:40,580 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/0cb7d459-fd3f-4435-b44f-3d93594c3e32 "HTTP/1.1 200 OK"
-2026-05-07 14:55:40,750 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 14:55:41,291 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 14:55:41,867 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=0cb7d459-fd3f-4435-b44f-3d93594c3e32 "HTTP/1.1 200 OK"
-2026-05-07 14:59:17,106 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T20:59:17.106093+00:00
-2026-05-07 14:59:17,106 INFO backend.segmentation: [JOB 9d8e54c57b804dd6a5868f2f16907d6a] preparing_image progress=12
-2026-05-07 14:59:17,177 INFO backend.segmentation: [JOB 9d8e54c57b804dd6a5868f2f16907d6a] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 14:59:17,178 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 14:59:17,820 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 14:59:18,429 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 14:59:18,612 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 14:59:19,270 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/4bafc24c-7b3e-47e5-ab5c-040b1104f6ad "HTTP/1.1 200 OK"
-2026-05-07 14:59:19,316 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 14:59:19,895 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 14:59:20,498 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=4bafc24c-7b3e-47e5-ab5c-040b1104f6ad "HTTP/1.1 200 OK"
-2026-05-07 14:59:22,556 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/e46ee411d94ec777ba35b9e436d075e4a9639d5f1e564687b887320d75811f38/image.webp "HTTP/1.1 200 OK"
-2026-05-07 14:59:22,561 WARNING services.gradio_client_service: GPU Space failed (Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^), trying CPU fallback...
-2026-05-07 14:59:22,562 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-07 14:59:23,331 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 14:59:24,033 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 14:59:24,159 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 14:59:24,691 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/58739913-8194-4cc9-ae76-fab58874372a "HTTP/1.1 200 OK"
-2026-05-07 14:59:24,844 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 14:59:25,478 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 14:59:26,087 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=58739913-8194-4cc9-ae76-fab58874372a "HTTP/1.1 200 OK"
-2026-05-07 14:59:38,140 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/file=/tmp/gradio/0870aa16fb1d36280b4436effe666b2d40896a35db44e69dfe24e623f43e743b/image.webp "HTTP/1.1 200 OK"
-2026-05-07 14:59:38,143 ERROR backend.segmentation: [JOB e2978c252391482ea410013edd5dd614] failed: Both Gradio Spaces failed.
-  GPU (https://eduardo4547-hyper-reality-sam2-gpu.hf.space): Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/usr/local/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 47, in _call_gradio_sync
-    raise RuntimeError(f"Gradio Space error: {combined['error'][:500]}")
-RuntimeError: Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/usr/local/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-RuntimeError: Both Gradio Spaces failed.
-  GPU (https://eduardo4547-hyper-reality-sam2-gpu.hf.space): Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/usr/local/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-2026-05-07 14:59:38,144 INFO backend.segmentation: [UPLOAD_BG] DONE 259.680s at 2026-05-07T20:59:38.144994+00:00
-2026-05-07 14:59:38,144 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:02:17,066 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 15:02:17,090 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 15:02:54,241 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:02:54.241047+00:00
-2026-05-07 15:02:54,241 INFO backend.segmentation: [JOB 77ed4dd081d7432cbc3073f159883876] preparing_image progress=12
-2026-05-07 15:02:54,369 INFO backend.segmentation: [JOB 77ed4dd081d7432cbc3073f159883876] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 15:02:54,369 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 15:02:55,466 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 15:02:55,989 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:02:56,471 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:02:56,561 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/ae72d127-eaf7-4469-8805-b2f2d63b0e9a "HTTP/1.1 200 OK"
-2026-05-07 15:02:56,764 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:02:57,222 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:02:57,668 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=ae72d127-eaf7-4469-8805-b2f2d63b0e9a "HTTP/1.1 200 OK"
-2026-05-07 15:02:59,650 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/e46ee411d94ec777ba35b9e436d075e4a9639d5f1e564687b887320d75811f38/image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:02:59,653 WARNING services.gradio_client_service: GPU Space failed (Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^), trying CPU fallback...
-2026-05-07 15:02:59,654 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-07 15:03:01,621 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 15:03:02,088 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:03:02,262 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:03:02,629 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/2f3a5842-bc35-4aa3-8198-e3338bde647a "HTTP/1.1 200 OK"
-2026-05-07 15:03:02,785 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:03:03,183 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:03:03,623 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=2f3a5842-bc35-4aa3-8198-e3338bde647a "HTTP/1.1 200 OK"
-2026-05-07 15:11:16,099 ERROR backend.segmentation: [JOB 77ed4dd081d7432cbc3073f159883876] failed: Both Gradio Spaces failed.
-  GPU (https://eduardo4547-hyper-reality-sam2-gpu.hf.space): Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): 
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
-    _overlay_file, combined_json_str = client.predict(
-                                       ^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 499, in predict
-    ).result()
-      ^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 1484, in result
-    return super().result(timeout=timeout)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.12_3.12.2800.0_x64__qbz5n2kfra8p0\Lib\concurrent\futures\_base.py", line 456, in result
-    return self.__get_result()
-           ^^^^^^^^^^^^^^^^^^^
-  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.12_3.12.2800.0_x64__qbz5n2kfra8p0\Lib\concurrent\futures\_base.py", line 401, in __get_result
-    raise self._exception
-  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.12_3.12.2800.0_x64__qbz5n2kfra8p0\Lib\concurrent\futures\thread.py", line 59, in run
-    result = self.fn(*self.args, **self.kwargs)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 1080, in _inner
-    predictions = _predict(*data, **kwargs)
-                  ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 1188, in _predict
-    result = self._sse_fn_v1plus(helper, event_id, self.protocol)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 1388, in _sse_fn_v1plus
-    return utils.get_pred_from_sse_v1plus(
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\utils.py", line 395, in get_pred_from_sse_v1plus
-    raise exception
-  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.12_3.12.2800.0_x64__qbz5n2kfra8p0\Lib\concurrent\futures\thread.py", line 59, in run
-    result = self.fn(*self.args, **self.kwargs)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\utils.py", line 511, in stream_sse_v1plus
-    raise concurrent.futures.CancelledError()
-concurrent.futures._base.CancelledError
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-RuntimeError: Both Gradio Spaces failed.
-  GPU (https://eduardo4547-hyper-reality-sam2-gpu.hf.space): Gradio Space error: Traceback (most recent call last):
-  File "/app/app.py", line 133, in segment_for_backend
-    resultado = sam_vit_pipeline(
-        pil_image,
-    ...<5 lines>...
-        crops_n_layers=PARAMS["crops_n_layers"],
-    )
-  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
-    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
-           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): 
-2026-05-07 15:11:16,123 INFO backend.segmentation: [UPLOAD_BG] DONE 501.883s at 2026-05-07T21:11:16.123777+00:00
-2026-05-07 15:11:16,123 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:11:33,448 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 15:11:33,462 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 15:11:38,641 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:11:38.641727+00:00
-2026-05-07 15:11:38,642 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] preparing_image progress=12
-2026-05-07 15:11:38,745 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 15:11:38,747 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 15:11:39,778 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 15:11:40,250 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:11:40,717 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:11:40,821 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/2ba41729-fa1a-4207-b1a6-9c3ef6526887 "HTTP/1.1 200 OK"
-2026-05-07 15:11:40,924 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:11:41,336 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:11:42,039 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=2ba41729-fa1a-4207-b1a6-9c3ef6526887 "HTTP/1.1 200 OK"
-2026-05-07 15:12:02,740 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d17dd4b993c601f166cf197f34896b5d17a23e30a9fe1f5022b368a594a3f823/image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:12:02,846 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
-2026-05-07 15:12:02,846 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] saving_masks progress=92
-2026-05-07 15:12:02,991 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] segments_meta saved (54 segments)
-2026-05-07 15:12:02,991 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] done mask_count=63
-2026-05-07 15:12:02,992 INFO backend.segmentation: [UPLOAD_BG] DONE 24.350s at 2026-05-07T21:12:02.992931+00:00
-2026-05-07 15:12:02,992 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:12:30,031 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:12:30.031296+00:00
-2026-05-07 15:12:30,558 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:12:30,891 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.860s at 2026-05-07T21:12:30.891199+00:00
-2026-05-07 15:13:18,964 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:13:18.964838+00:00
-2026-05-07 15:13:18,964 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] preparing_image progress=12
-2026-05-07 15:13:19,050 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 15:13:19,051 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 15:13:19,623 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 15:13:20,207 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:13:20,445 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:13:20,882 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/6b2ee8fb-256a-4778-af39-73fbc7180d64 "HTTP/1.1 200 OK"
-2026-05-07 15:13:21,064 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:13:21,680 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:13:22,271 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=6b2ee8fb-256a-4778-af39-73fbc7180d64 "HTTP/1.1 200 OK"
-2026-05-07 15:13:32,414 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d17dd4b993c601f166cf197f34896b5d17a23e30a9fe1f5022b368a594a3f823/image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:13:32,528 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
-2026-05-07 15:13:32,528 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] saving_masks progress=92
-2026-05-07 15:13:32,702 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] segments_meta saved (54 segments)
-2026-05-07 15:13:32,703 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] done mask_count=63
-2026-05-07 15:13:32,703 INFO backend.segmentation: [UPLOAD_BG] DONE 13.740s at 2026-05-07T21:13:32.703517+00:00
-2026-05-07 15:13:32,704 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:19:48,376 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:19:48.376272+00:00
-2026-05-07 15:19:48,376 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] preparing_image progress=12
-2026-05-07 15:19:48,443 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 15:19:48,444 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-07 15:19:49,095 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-07 15:19:49,716 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:19:49,928 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:19:50,414 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/c601fff9-ae77-444d-86f4-c6eb6ee29ae8 "HTTP/1.1 200 OK"
-2026-05-07 15:19:50,537 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:19:51,092 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:19:51,642 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=c601fff9-ae77-444d-86f4-c6eb6ee29ae8 "HTTP/1.1 200 OK"
-2026-05-07 15:20:01,890 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d17dd4b993c601f166cf197f34896b5d17a23e30a9fe1f5022b368a594a3f823/image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:20:02,004 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
-2026-05-07 15:20:02,005 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] saving_masks progress=92
-2026-05-07 15:20:02,221 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] segments_meta saved (54 segments)
-2026-05-07 15:20:02,221 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] done mask_count=63
-2026-05-07 15:20:02,221 INFO backend.segmentation: [UPLOAD_BG] DONE 13.846s at 2026-05-07T21:20:02.221722+00:00
-2026-05-07 15:20:02,222 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:21:36,330 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:21:36.330551+00:00
-2026-05-07 15:21:36,908 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:21:37,121 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.790s at 2026-05-07T21:21:37.121352+00:00
-2026-05-07 15:21:45,205 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:21:45.203794+00:00
-2026-05-07 15:21:45,723 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
-2026-05-07 15:21:45,743 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:21:45,953 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.748s at 2026-05-07T21:21:45.953335+00:00
-2026-05-07 15:21:49,795 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:21:49.795014+00:00
-2026-05-07 15:21:50,312 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.24)
-2026-05-07 15:21:50,331 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:21:50,547 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.753s at 2026-05-07T21:21:50.547610+00:00
-2026-05-07 15:21:56,068 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:21:56.068945+00:00
-2026-05-07 15:21:56,572 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.18, h_ratio=287.00)
-2026-05-07 15:21:56,592 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:21:56,802 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.734s at 2026-05-07T21:21:56.802967+00:00
-2026-05-07 15:23:52,960 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 15:23:52,981 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 15:24:42,274 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:24:42.274969+00:00
-2026-05-07 15:24:42,274 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] preparing_image progress=12
-2026-05-07 15:24:42,409 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 15:24:42,414 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 15:24:45,341 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 15:24:47,723 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:24:48,299 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:24:50,226 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/dab64d79-0e60-4114-b75e-b53930a5d4f7 "HTTP/1.1 200 OK"
-2026-05-07 15:24:50,247 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:24:54,192 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:24:56,620 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=dab64d79-0e60-4114-b75e-b53930a5d4f7 "HTTP/1.1 200 OK"
-2026-05-07 15:27:24,526 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:27:24,538 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
-2026-05-07 15:27:24,538 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] saving_masks progress=92
-2026-05-07 15:27:24,702 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] segments_meta saved (63 segments)
-2026-05-07 15:27:24,702 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] done mask_count=63
-2026-05-07 15:27:24,702 INFO backend.segmentation: [UPLOAD_BG] DONE 162.428s at 2026-05-07T21:27:24.702523+00:00
-2026-05-07 15:27:24,702 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:27:41,959 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:41.959810+00:00
-2026-05-07 15:27:42,278 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.05, h_ratio=416.39)
-2026-05-07 15:27:42,305 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:27:42,814 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.854s at 2026-05-07T21:27:42.814627+00:00
-2026-05-07 15:27:46,763 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:46.763830+00:00
-2026-05-07 15:27:47,166 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:27:47,378 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.614s at 2026-05-07T21:27:47.378508+00:00
-2026-05-07 15:27:49,193 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:49.193540+00:00
-2026-05-07 15:27:49,513 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-07 15:27:49,532 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:27:49,729 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.536s at 2026-05-07T21:27:49.729431+00:00
-2026-05-07 15:27:51,249 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:51.249369+00:00
-2026-05-07 15:27:51,544 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:27:51,755 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.506s at 2026-05-07T21:27:51.755618+00:00
-2026-05-07 15:27:52,680 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:52.680739+00:00
-2026-05-07 15:27:52,986 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:27:53,211 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.531s at 2026-05-07T21:27:53.211475+00:00
-2026-05-07 15:27:54,203 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:54.203416+00:00
-2026-05-07 15:27:54,500 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:27:54,736 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.533s at 2026-05-07T21:27:54.736190+00:00
-2026-05-07 15:28:31,805 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:28:31.805147+00:00
-2026-05-07 15:28:32,098 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:28:32,338 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.534s at 2026-05-07T21:28:32.338930+00:00
-2026-05-07 15:28:42,559 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:28:42.559339+00:00
-2026-05-07 15:28:43,089 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:28:43,307 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.748s at 2026-05-07T21:28:43.307767+00:00
-2026-05-07 15:28:46,313 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:28:46.313349+00:00
-2026-05-07 15:28:46,831 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.74, h_ratio=1.19)
-2026-05-07 15:28:46,865 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:28:47,077 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.764s at 2026-05-07T21:28:47.077622+00:00
-2026-05-07 15:28:59,114 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:28:59.114208+00:00
-2026-05-07 15:28:59,643 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:28:59,870 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.756s at 2026-05-07T21:28:59.870175+00:00
-2026-05-07 15:29:02,857 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:29:02.857460+00:00
-2026-05-07 15:29:03,385 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:29:03,598 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.741s at 2026-05-07T21:29:03.598245+00:00
-2026-05-07 15:29:09,230 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:29:09.230242+00:00
-2026-05-07 15:29:09,812 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-07 15:29:09,836 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:29:10,063 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.832s at 2026-05-07T21:29:10.063265+00:00
-2026-05-07 15:30:08,609 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:30:08.608222+00:00
-2026-05-07 15:30:09,164 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-07 15:30:09,188 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:30:09,393 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.785s at 2026-05-07T21:30:09.393640+00:00
-2026-05-07 15:30:14,390 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:30:14.390221+00:00
-2026-05-07 15:30:14,951 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-07 15:30:14,970 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 15:30:15,192 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.803s at 2026-05-07T21:30:15.192554+00:00
-2026-05-07 15:30:40,712 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:30:40.712459+00:00
-2026-05-07 15:30:40,713 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] preparing_image progress=12
-2026-05-07 15:30:40,791 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
-2026-05-07 15:30:40,792 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 15:30:43,195 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 15:30:45,588 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:30:45,733 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:30:48,162 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:30:48,173 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/d1c209e4-d368-4e81-8ce0-b7c8824ed437 "HTTP/1.1 200 OK"
-2026-05-07 15:30:50,534 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:30:53,316 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=d1c209e4-d368-4e81-8ce0-b7c8824ed437 "HTTP/1.1 200 OK"
-2026-05-07 15:33:13,981 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\3944faeeae589a5b426a0f9b9ce0280816fb839f02b7dd9ab2628c5aef775da2\image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:33:13,999 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=66
-2026-05-07 15:33:14,000 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] saving_masks progress=92
-2026-05-07 15:33:14,323 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] segments_meta saved (66 segments)
-2026-05-07 15:33:14,324 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] done mask_count=66
-2026-05-07 15:33:14,325 INFO backend.segmentation: [UPLOAD_BG] DONE 153.613s at 2026-05-07T21:33:14.324926+00:00
-2026-05-07 15:33:14,325 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:33:20,991 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:20.991904+00:00
-2026-05-07 15:33:21,557 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.03)
-2026-05-07 15:33:21,587 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-07 15:33:21,856 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.865s at 2026-05-07T21:33:21.856475+00:00
-2026-05-07 15:33:23,187 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:23.187537+00:00
-2026-05-07 15:33:23,640 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=106.02)
-2026-05-07 15:33:23,660 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-07 15:33:23,887 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.700s at 2026-05-07T21:33:23.887323+00:00
-2026-05-07 15:33:28,666 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:28.666370+00:00
-2026-05-07 15:33:29,256 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=1.13)
-2026-05-07 15:33:29,278 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-07 15:33:29,514 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.849s at 2026-05-07T21:33:29.514966+00:00
-2026-05-07 15:33:35,559 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:35.559814+00:00
-2026-05-07 15:33:36,119 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.03)
-2026-05-07 15:33:36,156 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-07 15:33:36,369 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.810s at 2026-05-07T21:33:36.369980+00:00
-2026-05-07 15:33:41,348 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:41.348944+00:00
-2026-05-07 15:33:41,841 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.03)
-2026-05-07 15:33:41,873 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-07 15:33:42,143 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.796s at 2026-05-07T21:33:42.143571+00:00
-2026-05-07 15:34:05,661 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:34:05.661441+00:00
-2026-05-07 15:34:06,223 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
-2026-05-07 15:34:06,245 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
-2026-05-07 15:34:06,458 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.797s at 2026-05-07T21:34:06.458559+00:00
-2026-05-07 15:37:38,373 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:37:38.373999+00:00
-2026-05-07 15:37:38,375 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] preparing_image progress=12
-2026-05-07 15:37:38,423 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] segmenting_with_sam2 progress=30 estimated_seconds=94.01599999999999
-2026-05-07 15:37:38,423 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 15:37:40,841 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 15:37:43,152 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:37:43,304 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:37:45,640 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:37:45,645 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/96233e8c-fcb3-4e6e-a52b-43f262d4afc5 "HTTP/1.1 200 OK"
-2026-05-07 15:37:48,001 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:37:50,838 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=96233e8c-fcb3-4e6e-a52b-43f262d4afc5 "HTTP/1.1 200 OK"
-2026-05-07 15:39:30,039 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\56758f540e1c547de434b369fae158810fde033fe3650199c54eecf9fd68ac46\image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:39:30,055 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=58
-2026-05-07 15:39:30,056 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] saving_masks progress=92
-2026-05-07 15:39:30,380 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] segments_meta saved (58 segments)
-2026-05-07 15:39:30,381 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] done mask_count=58
-2026-05-07 15:39:30,381 INFO backend.segmentation: [UPLOAD_BG] DONE 112.008s at 2026-05-07T21:39:30.381897+00:00
-2026-05-07 15:39:30,381 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:42:27,756 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:27.756524+00:00
-2026-05-07 15:42:28,316 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 15:42:28,714 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.958s at 2026-05-07T21:42:28.714486+00:00
-2026-05-07 15:42:31,110 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:31.110675+00:00
-2026-05-07 15:42:31,681 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 15:42:32,030 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.920s at 2026-05-07T21:42:32.030068+00:00
-2026-05-07 15:42:36,790 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:36.789013+00:00
-2026-05-07 15:42:37,354 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 15:42:37,723 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.934s at 2026-05-07T21:42:37.723785+00:00
-2026-05-07 15:42:43,821 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:43.821895+00:00
-2026-05-07 15:42:44,133 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 15:42:44,503 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.682s at 2026-05-07T21:42:44.503891+00:00
-2026-05-07 15:42:45,709 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:45.709851+00:00
-2026-05-07 15:42:46,014 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 15:42:46,365 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.656s at 2026-05-07T21:42:46.365851+00:00
-2026-05-07 15:42:48,755 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:48.755885+00:00
-2026-05-07 15:42:49,065 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 15:42:49,433 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.677s at 2026-05-07T21:42:49.433452+00:00
-2026-05-07 15:42:56,861 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:56.861868+00:00
-2026-05-07 15:42:57,289 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 15:42:57,689 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.827s at 2026-05-07T21:42:57.687938+00:00
-2026-05-07 15:47:02,637 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:47:02.637766+00:00
-2026-05-07 15:47:02,987 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 15:47:03,354 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.717s at 2026-05-07T21:47:03.354802+00:00
-2026-05-07 15:47:06,315 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:47:06.315345+00:00
-2026-05-07 15:47:06,692 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.31, h_ratio=1.04)
-2026-05-07 15:47:06,734 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 15:47:07,092 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.777s at 2026-05-07T21:47:07.092208+00:00
-2026-05-07 15:47:19,592 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:47:19.592166+00:00
-2026-05-07 15:47:19,593 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] preparing_image progress=12
-2026-05-07 15:47:20,196 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] segmenting_with_sam2 progress=30 estimated_seconds=57.674240000000005
-2026-05-07 15:47:20,197 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 15:47:22,577 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 15:47:24,974 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:47:25,112 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:47:27,430 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9d1507c0-f15b-4ce4-8a14-a75643934023 "HTTP/1.1 200 OK"
-2026-05-07 15:47:27,451 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:47:29,917 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:47:32,852 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9d1507c0-f15b-4ce4-8a14-a75643934023 "HTTP/1.1 200 OK"
-2026-05-07 15:49:56,285 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7fb2980e7537a93df201edb46c01cac70b34b0d407baf16d8c766c8326b688bb\image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:49:56,299 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=56
-2026-05-07 15:49:56,301 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] saving_masks progress=92
-2026-05-07 15:49:56,485 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] segments_meta saved (56 segments)
-2026-05-07 15:49:56,486 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] done mask_count=56
-2026-05-07 15:49:56,486 INFO backend.segmentation: [UPLOAD_BG] DONE 156.895s at 2026-05-07T21:49:56.486476+00:00
-2026-05-07 15:49:56,486 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:50:23,300 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:23.300896+00:00
-2026-05-07 15:50:23,632 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.43)
-2026-05-07 15:50:23,649 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
-2026-05-07 15:50:23,860 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.560s at 2026-05-07T21:50:23.860900+00:00
-2026-05-07 15:50:25,390 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:25.390001+00:00
-2026-05-07 15:50:25,729 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.05, h_ratio=1.59)
-2026-05-07 15:50:25,748 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
-2026-05-07 15:50:25,961 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.573s at 2026-05-07T21:50:25.961503+00:00
-2026-05-07 15:50:29,067 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:29.067701+00:00
-2026-05-07 15:50:29,357 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
-2026-05-07 15:50:29,574 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.505s at 2026-05-07T21:50:29.573244+00:00
-2026-05-07 15:50:30,765 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:30.765933+00:00
-2026-05-07 15:50:31,113 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.43, h_ratio=1.00)
-2026-05-07 15:50:31,135 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
-2026-05-07 15:50:31,381 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.616s at 2026-05-07T21:50:31.381120+00:00
-2026-05-07 15:50:34,372 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:34.372354+00:00
-2026-05-07 15:50:34,702 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
-2026-05-07 15:50:34,919 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.547s at 2026-05-07T21:50:34.919402+00:00
-2026-05-07 15:50:38,283 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:38.283908+00:00
-2026-05-07 15:50:38,620 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
-2026-05-07 15:50:38,822 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.538s at 2026-05-07T21:50:38.821521+00:00
-2026-05-07 15:50:42,362 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:42.362356+00:00
-2026-05-07 15:50:42,752 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=81.06)
-2026-05-07 15:50:42,770 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
-2026-05-07 15:50:42,983 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.622s at 2026-05-07T21:50:42.983933+00:00
-2026-05-07 15:50:46,827 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:46.827950+00:00
-2026-05-07 15:50:47,260 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
-2026-05-07 15:50:47,509 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.681s at 2026-05-07T21:50:47.509694+00:00
-2026-05-07 15:50:51,671 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:51.671277+00:00
-2026-05-07 15:50:52,056 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
-2026-05-07 15:50:52,261 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.591s at 2026-05-07T21:50:52.261800+00:00
-2026-05-07 15:51:01,177 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:51:01.177947+00:00
-2026-05-07 15:51:01,177 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] preparing_image progress=12
-2026-05-07 15:51:01,277 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] segmenting_with_sam2 progress=30 estimated_seconds=71.65183999999999
-2026-05-07 15:51:01,279 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 15:51:03,724 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 15:51:06,105 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:51:06,299 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:51:08,531 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/1f6ec649-450c-4d10-a42f-a0714e8554c6 "HTTP/1.1 200 OK"
-2026-05-07 15:51:08,533 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:51:10,974 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:51:13,861 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=1f6ec649-450c-4d10-a42f-a0714e8554c6 "HTTP/1.1 200 OK"
-2026-05-07 15:53:32,035 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\9b2d1c318212280bd44f91bf2c3aa028767f3015780e04d1e67d456398adfe23\image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:53:32,051 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=55
-2026-05-07 15:53:32,051 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] saving_masks progress=92
-2026-05-07 15:53:32,291 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] segments_meta saved (55 segments)
-2026-05-07 15:53:32,291 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] done mask_count=55
-2026-05-07 15:53:32,291 INFO backend.segmentation: [UPLOAD_BG] DONE 151.115s at 2026-05-07T21:53:32.291574+00:00
-2026-05-07 15:53:32,291 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:53:42,312 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:53:42.312363+00:00
-2026-05-07 15:53:42,838 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.04, h_ratio=1.36)
-2026-05-07 15:53:42,868 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
-2026-05-07 15:53:43,124 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.812s at 2026-05-07T21:53:43.124323+00:00
-2026-05-07 15:53:45,407 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:53:45.407699+00:00
-2026-05-07 15:53:45,913 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
-2026-05-07 15:53:46,160 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.752s at 2026-05-07T21:53:46.160544+00:00
-2026-05-07 15:53:51,917 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:53:51.917268+00:00
-2026-05-07 15:53:52,460 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.04, h_ratio=1.36)
-2026-05-07 15:53:52,504 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
-2026-05-07 15:53:52,784 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.868s at 2026-05-07T21:53:52.784729+00:00
-2026-05-07 15:53:59,737 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:53:59.737940+00:00
-2026-05-07 15:54:00,303 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.26)
-2026-05-07 15:54:00,325 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
-2026-05-07 15:54:00,581 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.843s at 2026-05-07T21:54:00.581113+00:00
-2026-05-07 15:54:07,204 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:54:07.204959+00:00
-2026-05-07 15:54:07,723 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.02 < 0.35, skip perspective)
-2026-05-07 15:54:07,755 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
-2026-05-07 15:54:08,011 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.806s at 2026-05-07T21:54:08.011194+00:00
-2026-05-07 15:54:14,251 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:54:14.251503+00:00
-2026-05-07 15:54:14,586 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.02 < 0.35, skip perspective)
-2026-05-07 15:54:14,618 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
-2026-05-07 15:54:14,893 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.642s at 2026-05-07T21:54:14.893824+00:00
-2026-05-07 15:54:20,951 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:54:20.951821+00:00
-2026-05-07 15:54:21,369 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.00, h_ratio=1.21)
-2026-05-07 15:54:21,394 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
-2026-05-07 15:54:21,654 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.703s at 2026-05-07T21:54:21.654007+00:00
-2026-05-07 15:55:49,324 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:55:49.324991+00:00
-2026-05-07 15:55:49,325 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] preparing_image progress=12
-2026-05-07 15:55:49,407 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-07 15:55:49,407 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 15:55:51,777 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 15:55:54,163 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:55:54,303 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:55:56,641 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/ddc1fa5d-ad06-492d-be12-a7f5ee46894f "HTTP/1.1 200 OK"
-2026-05-07 15:55:56,647 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:55:59,061 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:56:01,950 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=ddc1fa5d-ad06-492d-be12-a7f5ee46894f "HTTP/1.1 200 OK"
-2026-05-07 15:58:10,784 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\63f35ee774073b13ee87a1d3c7e73d1d3b47b4183190f3b098b633273f464612\image.webp "HTTP/1.1 200 OK"
-2026-05-07 15:58:10,799 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=61
-2026-05-07 15:58:10,799 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] saving_masks progress=92
-2026-05-07 15:58:11,031 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] segments_meta saved (61 segments)
-2026-05-07 15:58:11,033 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] done mask_count=61
-2026-05-07 15:58:11,033 INFO backend.segmentation: [UPLOAD_BG] DONE 141.708s at 2026-05-07T21:58:11.033788+00:00
-2026-05-07 15:58:11,033 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 15:58:20,920 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:20.920319+00:00
-2026-05-07 15:58:21,375 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.07)
-2026-05-07 15:58:21,407 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 15:58:21,598 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.679s at 2026-05-07T21:58:21.598068+00:00
-2026-05-07 15:58:24,623 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:24.623163+00:00
-2026-05-07 15:58:25,169 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.07)
-2026-05-07 15:58:25,191 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 15:58:25,360 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.738s at 2026-05-07T21:58:25.360818+00:00
-2026-05-07 15:58:28,165 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:28.165635+00:00
-2026-05-07 15:58:28,661 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 15:58:28,843 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.678s at 2026-05-07T21:58:28.843020+00:00
-2026-05-07 15:58:32,464 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:32.464694+00:00
-2026-05-07 15:58:32,978 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.08, h_ratio=1.42)
-2026-05-07 15:58:32,994 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 15:58:33,161 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.696s at 2026-05-07T21:58:33.161634+00:00
-2026-05-07 15:58:38,273 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:38.273840+00:00
-2026-05-07 15:58:38,781 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.13, h_ratio=2.54)
-2026-05-07 15:58:38,796 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 15:58:39,000 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.726s at 2026-05-07T21:58:39.000222+00:00
-2026-05-07 15:58:46,330 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:46.330265+00:00
-2026-05-07 15:58:46,828 INFO backend.segmentation: [APPLY_TEXTURE] perspective floor tiling applied (trap=1.00)
-2026-05-07 15:58:46,842 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 15:58:47,013 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.682s at 2026-05-07T21:58:47.013199+00:00
-2026-05-07 15:58:50,609 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:50.609562+00:00
-2026-05-07 15:58:51,166 INFO backend.segmentation: [APPLY_TEXTURE] perspective floor tiling applied (trap=1.00)
-2026-05-07 15:58:51,183 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 15:58:51,361 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.752s at 2026-05-07T21:58:51.361385+00:00
-2026-05-07 15:58:55,441 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:55.441205+00:00
-2026-05-07 15:58:55,946 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 15:58:56,114 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.673s at 2026-05-07T21:58:56.113779+00:00
-2026-05-07 15:59:08,450 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:59:08.450556+00:00
-2026-05-07 15:59:08,975 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.07)
-2026-05-07 15:59:09,001 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 15:59:09,173 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.723s at 2026-05-07T21:59:09.173815+00:00
-2026-05-07 15:59:16,551 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:59:16.551116+00:00
-2026-05-07 15:59:16,552 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] preparing_image progress=12
-2026-05-07 15:59:16,631 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-07 15:59:16,631 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 15:59:18,993 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 15:59:21,337 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 15:59:21,485 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 15:59:23,779 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/c1c694f0-2678-4cce-a664-ce7657360059 "HTTP/1.1 200 OK"
-2026-05-07 15:59:23,799 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 15:59:26,196 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 15:59:29,114 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=c1c694f0-2678-4cce-a664-ce7657360059 "HTTP/1.1 200 OK"
-2026-05-07 16:01:40,463 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\3f4bbc5e6cf6ca3e1f300135e65cb8423907d8d2601a24cab61eaf4e68bb94d8\image.webp "HTTP/1.1 200 OK"
-2026-05-07 16:01:40,478 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=51
-2026-05-07 16:01:40,479 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] saving_masks progress=92
-2026-05-07 16:01:40,648 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] segments_meta saved (51 segments)
-2026-05-07 16:01:40,649 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] done mask_count=51
-2026-05-07 16:01:40,649 INFO backend.segmentation: [UPLOAD_BG] DONE 144.098s at 2026-05-07T22:01:40.649441+00:00
-2026-05-07 16:01:40,649 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 16:04:16,992 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:04:16.992111+00:00
-2026-05-07 16:04:17,540 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 16:04:17,715 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.724s at 2026-05-07T22:04:17.715600+00:00
-2026-05-07 16:04:20,514 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:04:20.514659+00:00
-2026-05-07 16:04:21,019 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=1.38)
-2026-05-07 16:04:21,036 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 16:04:21,242 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.727s at 2026-05-07T22:04:21.242012+00:00
-2026-05-07 16:04:28,071 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:04:28.071982+00:00
-2026-05-07 16:04:28,407 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.30, h_ratio=1.35)
-2026-05-07 16:04:28,428 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 16:04:28,596 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.525s at 2026-05-07T22:04:28.596511+00:00
-2026-05-07 16:04:30,490 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:04:30.490530+00:00
-2026-05-07 16:04:30,813 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.02, h_ratio=1.81)
-2026-05-07 16:04:30,833 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 16:04:31,008 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.519s at 2026-05-07T22:04:31.008084+00:00
-2026-05-07 16:05:02,767 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:05:02.767829+00:00
-2026-05-07 16:05:03,251 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
-2026-05-07 16:05:03,405 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.636s at 2026-05-07T22:05:03.405079+00:00
-2026-05-07 16:05:43,990 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:05:43.990943+00:00
-2026-05-07 16:05:43,990 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] preparing_image progress=12
-2026-05-07 16:05:44,067 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-07 16:05:44,067 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 16:05:46,491 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 16:05:48,868 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 16:05:49,016 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 16:05:51,323 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/6f95fab4-a857-4501-89ac-ccbf7e0581ea "HTTP/1.1 200 OK"
-2026-05-07 16:05:51,327 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 16:05:53,691 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 16:05:56,691 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=6f95fab4-a857-4501-89ac-ccbf7e0581ea "HTTP/1.1 200 OK"
-2026-05-07 16:08:09,268 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\63f35ee774073b13ee87a1d3c7e73d1d3b47b4183190f3b098b633273f464612\image.webp "HTTP/1.1 200 OK"
-2026-05-07 16:08:09,288 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=61
-2026-05-07 16:08:09,289 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] saving_masks progress=92
-2026-05-07 16:08:09,486 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] segments_meta saved (61 segments)
-2026-05-07 16:08:09,486 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] done mask_count=61
-2026-05-07 16:08:09,488 INFO backend.segmentation: [UPLOAD_BG] DONE 145.497s at 2026-05-07T22:08:09.488380+00:00
-2026-05-07 16:08:09,488 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 16:22:47,224 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:22:47.224087+00:00
-2026-05-07 16:22:47,225 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] preparing_image progress=12
-2026-05-07 16:22:47,297 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 16:22:47,298 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 16:22:49,799 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 16:22:52,184 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 16:22:52,330 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 16:22:54,605 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/3d5ff637-214a-47c4-8a4f-d64d884b7a8b "HTTP/1.1 200 OK"
-2026-05-07 16:22:54,640 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 16:22:57,021 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 16:23:00,162 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=3d5ff637-214a-47c4-8a4f-d64d884b7a8b "HTTP/1.1 200 OK"
-2026-05-07 16:25:15,470 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
-2026-05-07 16:25:15,487 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
-2026-05-07 16:25:15,487 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] saving_masks progress=92
-2026-05-07 16:25:15,707 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] segments_meta saved (63 segments)
-2026-05-07 16:25:15,708 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] done mask_count=63
-2026-05-07 16:25:15,708 INFO backend.segmentation: [UPLOAD_BG] DONE 148.483s at 2026-05-07T22:25:15.708008+00:00
-2026-05-07 16:25:15,708 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 16:29:50,418 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:29:50.418894+00:00
-2026-05-07 16:29:50,418 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] preparing_image progress=12
-2026-05-07 16:29:50,498 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 16:29:50,500 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 16:29:52,926 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 16:29:55,311 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 16:29:55,457 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 16:29:57,773 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/c79c4e3d-25f5-4e6a-a4ba-45e7493b7b23 "HTTP/1.1 200 OK"
-2026-05-07 16:29:57,774 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 16:30:00,168 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 16:30:03,061 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=c79c4e3d-25f5-4e6a-a4ba-45e7493b7b23 "HTTP/1.1 200 OK"
-2026-05-07 16:32:17,053 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
-2026-05-07 16:32:17,071 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
-2026-05-07 16:32:17,071 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] saving_masks progress=92
-2026-05-07 16:32:17,286 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] segments_meta saved (63 segments)
-2026-05-07 16:32:17,286 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] done mask_count=63
-2026-05-07 16:32:17,288 INFO backend.segmentation: [UPLOAD_BG] DONE 146.869s at 2026-05-07T22:32:17.288291+00:00
-2026-05-07 16:32:17,288 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 16:32:41,697 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:32:41.697454+00:00
-2026-05-07 16:32:42,204 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 16:32:42,424 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.726s at 2026-05-07T22:32:42.424111+00:00
-2026-05-07 16:33:01,624 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:33:01.624117+00:00
-2026-05-07 16:33:01,624 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] preparing_image progress=12
-2026-05-07 16:33:01,697 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 16:33:01,698 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 16:33:04,132 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 16:33:06,530 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 16:33:06,692 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 16:33:08,991 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/78cd91de-4ac8-417d-a699-df5ceae4592f "HTTP/1.1 200 OK"
-2026-05-07 16:33:08,994 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 16:33:11,414 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 16:33:14,289 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=78cd91de-4ac8-417d-a699-df5ceae4592f "HTTP/1.1 200 OK"
-2026-05-07 16:35:33,030 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
-2026-05-07 16:35:33,049 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
-2026-05-07 16:35:33,049 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] saving_masks progress=92
-2026-05-07 16:35:33,274 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] segments_meta saved (63 segments)
-2026-05-07 16:35:33,275 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] done mask_count=63
-2026-05-07 16:35:33,276 INFO backend.segmentation: [UPLOAD_BG] DONE 151.652s at 2026-05-07T22:35:33.276280+00:00
-2026-05-07 16:35:33,276 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 16:36:09,236 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:09.236174+00:00
-2026-05-07 16:36:09,540 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.59, h_ratio=1.44)
-2026-05-07 16:36:09,562 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 16:36:09,777 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.540s at 2026-05-07T22:36:09.777110+00:00
-2026-05-07 16:36:15,985 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:15.985071+00:00
-2026-05-07 16:36:16,483 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.16, h_ratio=1.26)
-2026-05-07 16:36:16,504 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 16:36:16,716 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.731s at 2026-05-07T22:36:16.716050+00:00
-2026-05-07 16:36:25,017 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:25.017619+00:00
-2026-05-07 16:36:25,564 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=1.37)
-2026-05-07 16:36:25,587 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 16:36:25,803 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.786s at 2026-05-07T22:36:25.803112+00:00
-2026-05-07 16:36:26,817 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:26.817271+00:00
-2026-05-07 16:36:27,352 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 16:36:27,584 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.767s at 2026-05-07T22:36:27.584739+00:00
-2026-05-07 16:36:28,334 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:28.334300+00:00
-2026-05-07 16:36:28,857 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 16:36:29,081 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.747s at 2026-05-07T22:36:29.081102+00:00
-2026-05-07 16:36:32,240 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:32.240623+00:00
-2026-05-07 16:36:32,772 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 16:36:33,003 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.763s at 2026-05-07T22:36:33.003855+00:00
-2026-05-07 16:40:31,573 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:40:31.573485+00:00
-2026-05-07 16:40:31,573 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] preparing_image progress=12
-2026-05-07 16:40:31,619 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] segmenting_with_sam2 progress=30 estimated_seconds=94.01599999999999
-2026-05-07 16:40:31,620 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 16:40:34,052 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 16:40:36,278 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 16:40:36,412 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 16:40:38,556 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e3bbcd8a-d009-4eb7-b2ef-0318dd7f287c "HTTP/1.1 200 OK"
-2026-05-07 16:40:38,575 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 16:40:40,832 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 16:40:43,079 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e3bbcd8a-d009-4eb7-b2ef-0318dd7f287c "HTTP/1.1 200 OK"
-2026-05-07 16:42:01,159 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\56758f540e1c547de434b369fae158810fde033fe3650199c54eecf9fd68ac46\image.webp "HTTP/1.1 200 OK"
-2026-05-07 16:42:01,173 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=58
-2026-05-07 16:42:01,174 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] saving_masks progress=92
-2026-05-07 16:42:01,396 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] segments_meta saved (58 segments)
-2026-05-07 16:42:01,397 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] done mask_count=58
-2026-05-07 16:42:01,397 INFO backend.segmentation: [UPLOAD_BG] DONE 89.824s at 2026-05-07T22:42:01.397333+00:00
-2026-05-07 16:42:01,397 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 16:43:02,036 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:43:02.036847+00:00
-2026-05-07 16:43:02,036 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] preparing_image progress=12
-2026-05-07 16:43:02,378 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] segmenting_with_sam2 progress=30 estimated_seconds=105.8432
-2026-05-07 16:43:02,380 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 16:43:04,773 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 16:43:07,148 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 16:43:07,281 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 16:43:09,603 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/a89250d1-ac0d-45ef-9bdc-7f28bdbd5c74 "HTTP/1.1 200 OK"
-2026-05-07 16:43:09,607 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 16:43:12,018 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 16:43:14,837 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=a89250d1-ac0d-45ef-9bdc-7f28bdbd5c74 "HTTP/1.1 200 OK"
-2026-05-07 16:45:52,678 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\fe7e296f49e3953b396fc8aeb7f4885b83ba4201a8d3f8d451ff0339d7391c52\image.webp "HTTP/1.1 200 OK"
-2026-05-07 16:45:52,698 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=74
-2026-05-07 16:45:52,698 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] saving_masks progress=92
-2026-05-07 16:45:53,143 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] segments_meta saved (74 segments)
-2026-05-07 16:45:53,143 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] done mask_count=74
-2026-05-07 16:45:53,144 INFO backend.segmentation: [UPLOAD_BG] DONE 171.106s at 2026-05-07T22:45:53.144055+00:00
-2026-05-07 16:45:53,144 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 16:46:04,090 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:04.090988+00:00
-2026-05-07 16:46:04,428 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.31 < 0.35, skip perspective)
-2026-05-07 16:46:04,482 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 16:46:04,894 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.803s at 2026-05-07T22:46:04.893619+00:00
-2026-05-07 16:46:13,581 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:13.581681+00:00
-2026-05-07 16:46:13,926 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 16:46:14,330 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.749s at 2026-05-07T22:46:14.330751+00:00
-2026-05-07 16:46:19,978 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:19.978023+00:00
-2026-05-07 16:46:20,448 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.31 < 0.35, skip perspective)
-2026-05-07 16:46:20,501 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 16:46:20,917 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.939s at 2026-05-07T22:46:20.917957+00:00
-2026-05-07 16:46:24,322 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:24.322422+00:00
-2026-05-07 16:46:24,904 INFO backend.segmentation: [APPLY_TEXTURE] perspective floor tiling applied (trap=1.00)
-2026-05-07 16:46:24,949 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 16:46:25,362 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.040s at 2026-05-07T22:46:25.362160+00:00
-2026-05-07 16:46:29,955 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:29.955304+00:00
-2026-05-07 16:46:30,502 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
-2026-05-07 16:46:30,549 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 16:46:30,987 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.033s at 2026-05-07T22:46:30.987573+00:00
-2026-05-07 16:46:38,234 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:38.234058+00:00
-2026-05-07 16:46:38,637 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.31 < 0.35, skip perspective)
-2026-05-07 16:46:38,690 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 16:46:39,101 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.867s at 2026-05-07T22:46:39.101314+00:00
-2026-05-07 17:01:04,655 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:01:04.655845+00:00
-2026-05-07 17:01:05,250 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.05, h_ratio=1.68)
-2026-05-07 17:01:05,308 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:01:05,726 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.071s at 2026-05-07T23:01:05.726857+00:00
-2026-05-07 17:19:38,903 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 17:19:38,930 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 17:20:05,519 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:05.519131+00:00
-2026-05-07 17:20:05,664 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
-2026-05-07 17:20:05,718 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:20:06,288 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.770s at 2026-05-07T23:20:06.288369+00:00
-2026-05-07 17:20:10,885 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:10.885784+00:00
-2026-05-07 17:20:11,012 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
-2026-05-07 17:20:11,057 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:20:11,494 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.609s at 2026-05-07T23:20:11.493854+00:00
-2026-05-07 17:20:16,040 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:16.040610+00:00
-2026-05-07 17:20:16,136 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:20:16,549 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.509s at 2026-05-07T23:20:16.549652+00:00
-2026-05-07 17:20:18,515 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:18.515915+00:00
-2026-05-07 17:20:18,600 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.31 < 0.35, skip perspective)
-2026-05-07 17:20:18,652 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:20:19,065 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.550s at 2026-05-07T23:20:19.065884+00:00
-2026-05-07 17:20:25,048 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:25.048663+00:00
-2026-05-07 17:20:25,199 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.17, h_ratio=1.48)
-2026-05-07 17:20:25,233 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:20:25,664 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.616s at 2026-05-07T23:20:25.664798+00:00
-2026-05-07 17:20:29,831 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:29.831966+00:00
-2026-05-07 17:20:29,986 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.17, h_ratio=1.48)
-2026-05-07 17:20:30,018 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:20:30,460 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.629s at 2026-05-07T23:20:30.460822+00:00
-2026-05-07 17:20:31,763 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:31.763484+00:00
-2026-05-07 17:20:31,886 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
-2026-05-07 17:20:31,929 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:20:32,354 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.591s at 2026-05-07T23:20:32.354006+00:00
-2026-05-07 17:20:33,945 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:33.945098+00:00
-2026-05-07 17:20:34,040 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:20:34,468 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.523s at 2026-05-07T23:20:34.468881+00:00
-2026-05-07 17:20:35,606 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:35.606548+00:00
-2026-05-07 17:20:35,728 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
-2026-05-07 17:20:35,776 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:20:36,186 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.580s at 2026-05-07T23:20:36.186410+00:00
-2026-05-07 17:21:19,858 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:21:19.858037+00:00
-2026-05-07 17:21:19,984 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
-2026-05-07 17:21:20,031 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
-2026-05-07 17:21:20,492 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.633s at 2026-05-07T23:21:20.492075+00:00
-2026-05-07 17:23:17,203 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 17:23:17,220 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 17:34:54,520 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 17:34:54,537 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 17:34:55,382 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 17:34:55,400 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 17:35:53,725 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd21d97b5fb8b402d113c5, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd21d97b5fb8b402d113c5"}, "remainingTimeMS": 30}
-2026-05-07 17:38:06,088 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T23:38:06.088546+00:00
-2026-05-07 17:38:06,088 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] preparing_image progress=12
-2026-05-07 17:38:06,177 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-07 17:38:06,178 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 17:38:10,859 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 17:38:13,266 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 17:38:13,842 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 17:38:15,792 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9771f2ad-8cd2-4dbb-bf76-dbcaa54a9e8c "HTTP/1.1 200 OK"
-2026-05-07 17:38:15,799 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 17:38:18,175 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 17:38:21,015 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9771f2ad-8cd2-4dbb-bf76-dbcaa54a9e8c "HTTP/1.1 200 OK"
-2026-05-07 17:39:18,012 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
-2026-05-07 17:39:18,026 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
-2026-05-07 17:39:18,026 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] saving_masks progress=92
-2026-05-07 17:39:18,184 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] segments_meta saved (63 segments)
-2026-05-07 17:39:18,184 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] done mask_count=63
-2026-05-07 17:39:18,184 INFO backend.segmentation: [UPLOAD_BG] DONE 72.097s at 2026-05-07T23:39:18.184964+00:00
-2026-05-07 17:39:18,184 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 17:41:23,776 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:41:23.776644+00:00
-2026-05-07 17:41:24,331 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
-2026-05-07 17:41:24,357 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 17:41:24,711 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.935s at 2026-05-07T23:41:24.711180+00:00
-2026-05-07 17:41:27,452 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:41:27.452983+00:00
-2026-05-07 17:41:27,541 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-07 17:41:27,564 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 17:41:27,800 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.348s at 2026-05-07T23:41:27.800164+00:00
-2026-05-07 17:41:30,962 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:41:30.962686+00:00
-2026-05-07 17:41:31,048 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-07 17:41:31,065 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 17:41:31,301 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.338s at 2026-05-07T23:41:31.301380+00:00
-2026-05-07 17:41:33,842 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:41:33.842810+00:00
-2026-05-07 17:41:33,933 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-07 17:41:33,960 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 17:41:34,187 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.345s at 2026-05-07T23:41:34.187626+00:00
-2026-05-07 17:41:37,885 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:41:37.885854+00:00
-2026-05-07 17:41:38,391 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 17:41:38,616 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.730s at 2026-05-07T23:41:38.616620+00:00
-2026-05-07 17:41:41,951 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:41:41.951324+00:00
-2026-05-07 17:41:42,020 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 17:41:42,238 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.287s at 2026-05-07T23:41:42.238675+00:00
-2026-05-07 17:41:44,128 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:41:44.128975+00:00
-2026-05-07 17:41:44,212 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
-2026-05-07 17:41:44,225 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 17:41:44,443 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.314s at 2026-05-07T23:41:44.443647+00:00
-2026-05-07 17:41:53,244 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:41:53.244718+00:00
-2026-05-07 17:41:53,307 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 17:41:53,534 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.290s at 2026-05-07T23:41:53.534468+00:00
-2026-05-07 17:41:56,242 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:41:56.242076+00:00
-2026-05-07 17:41:56,315 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 17:41:56,547 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.305s at 2026-05-07T23:41:56.547354+00:00
-2026-05-07 17:42:12,026 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T23:42:12.026351+00:00
-2026-05-07 17:42:12,027 INFO backend.segmentation: [JOB 31ffcc550acc49ebaef7694d019e4738] preparing_image progress=12
-2026-05-07 17:42:12,087 INFO backend.segmentation: [JOB 31ffcc550acc49ebaef7694d019e4738] segmenting_with_sam2 progress=30 estimated_seconds=94.01599999999999
-2026-05-07 17:42:12,087 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-07 17:42:14,504 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-07 17:42:16,891 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-07 17:42:17,033 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-07 17:42:19,359 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-07 17:42:19,359 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/5caf9962-b05a-4b4b-9ff5-a4e57abaa4d1 "HTTP/1.1 200 OK"
-2026-05-07 17:42:21,816 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-07 17:42:24,647 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=5caf9962-b05a-4b4b-9ff5-a4e57abaa4d1 "HTTP/1.1 200 OK"
-2026-05-07 17:44:44,214 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\56758f540e1c547de434b369fae158810fde033fe3650199c54eecf9fd68ac46\image.webp "HTTP/1.1 200 OK"
-2026-05-07 17:44:44,229 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=58
-2026-05-07 17:44:44,229 INFO backend.segmentation: [JOB 31ffcc550acc49ebaef7694d019e4738] saving_masks progress=92
-2026-05-07 17:44:44,558 INFO backend.segmentation: [JOB 31ffcc550acc49ebaef7694d019e4738] segments_meta saved (58 segments)
-2026-05-07 17:44:44,559 INFO backend.segmentation: [JOB 31ffcc550acc49ebaef7694d019e4738] done mask_count=58
-2026-05-07 17:44:44,559 INFO backend.segmentation: [UPLOAD_BG] DONE 152.534s at 2026-05-07T23:44:44.559631+00:00
-2026-05-07 17:44:44,559 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-07 17:46:08,455 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:46:08.455801+00:00
-2026-05-07 17:46:08,553 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 17:46:08,947 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.492s at 2026-05-07T23:46:08.947932+00:00
-2026-05-07 17:46:17,471 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:46:17.471758+00:00
-2026-05-07 17:46:17,573 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 17:46:17,959 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.487s at 2026-05-07T23:46:17.959003+00:00
-2026-05-07 17:46:28,129 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:46:28.129424+00:00
-2026-05-07 17:46:28,200 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 17:46:28,582 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.453s at 2026-05-07T23:46:28.582760+00:00
-2026-05-07 17:46:33,212 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:46:33.212302+00:00
-2026-05-07 17:46:33,309 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 17:46:33,672 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.460s at 2026-05-07T23:46:33.672645+00:00
-2026-05-07 17:46:35,529 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:46:35.528619+00:00
-2026-05-07 17:46:35,619 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 17:46:35,998 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.469s at 2026-05-07T23:46:35.998355+00:00
-2026-05-07 17:46:44,349 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:46:44.349770+00:00
-2026-05-07 17:46:44,480 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.47, h_ratio=1.33)
-2026-05-07 17:46:44,518 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 17:46:44,874 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.525s at 2026-05-07T23:46:44.874683+00:00
-2026-05-07 17:46:47,684 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:46:47.684050+00:00
-2026-05-07 17:46:47,763 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 17:46:48,178 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.495s at 2026-05-07T23:46:48.178702+00:00
-2026-05-07 17:46:49,167 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:46:49.167867+00:00
-2026-05-07 17:46:49,306 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.21)
-2026-05-07 17:46:49,338 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 17:46:49,729 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.561s at 2026-05-07T23:46:49.729581+00:00
-2026-05-07 17:46:51,803 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:46:51.803036+00:00
-2026-05-07 17:46:51,895 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 17:46:52,269 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.466s at 2026-05-07T23:46:52.269260+00:00
-2026-05-07 18:03:29,289 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 18:03:29,305 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 18:03:30,206 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 18:03:30,226 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 18:03:32,234 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd28548290d5e8dcce656f, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd28548290d5e8dcce656f"}, "remainingTimeMS": 30}
-2026-05-07 18:03:33,344 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd28558290d5e8dcce6570, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd28558290d5e8dcce6570"}, "remainingTimeMS": 30}
-2026-05-07 18:06:07,885 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 18:06:07,912 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 18:06:08,821 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 18:06:08,841 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 18:06:09,044 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd28f1cb744fdfd968df4f, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd28f1cb744fdfd968df4f"}, "remainingTimeMS": 30}
-2026-05-07 18:06:09,046 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd28f1cb744fdfd968df4f, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd28f1cb744fdfd968df4f"}, "remainingTimeMS": 30}
-2026-05-07 18:06:17,672 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T00:06:17.672406+00:00
-2026-05-07 18:06:17,774 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-07 18:06:18,277 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.606s at 2026-05-08T00:06:18.277654+00:00
-2026-05-07 18:06:29,233 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd2905cb744fdfd968df50, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd2905cb744fdfd968df50"}, "remainingTimeMS": 30}
-2026-05-07 18:06:29,234 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd2905cb744fdfd968df50, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd2905cb744fdfd968df50"}, "remainingTimeMS": 30}
-2026-05-07 18:06:38,021 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T00:06:38.021739+00:00
-2026-05-07 18:06:38,533 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
-2026-05-07 18:06:38,551 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 18:06:38,763 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.741s at 2026-05-08T00:06:38.763203+00:00
-2026-05-07 18:06:41,375 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T00:06:41.375987+00:00
-2026-05-07 18:06:41,901 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-07 18:06:41,921 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 18:06:42,135 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.760s at 2026-05-08T00:06:42.135731+00:00
-2026-05-07 18:17:10,342 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T00:17:10.342893+00:00
-2026-05-07 18:17:10,422 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
-2026-05-07 18:17:10,446 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 18:17:10,653 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.310s at 2026-05-08T00:17:10.653040+00:00
-2026-05-07 18:22:51,279 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 18:22:51,299 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 18:22:52,229 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-07 18:22:52,245 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-07 18:22:52,461 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd2cdc61ddd2197e4f4ad3, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd2cdc61ddd2197e4f4ad3"}, "remainingTimeMS": 30}
-2026-05-07 18:22:52,461 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd2cdc61ddd2197e4f4ad3, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd2cdc61ddd2197e4f4ad3"}, "remainingTimeMS": 30}
-2026-05-07 18:23:18,919 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T00:23:18.919571+00:00
-2026-05-07 18:23:19,016 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
-2026-05-07 18:23:19,038 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-07 18:23:19,455 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.535s at 2026-05-08T00:23:19.455089+00:00
-2026-05-07 18:23:32,434 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd2d0461ddd2197e4f4ad4, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd2d0461ddd2197e4f4ad4"}, "remainingTimeMS": 30}
-2026-05-07 18:23:32,438 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd2d0461ddd2197e4f4ad4, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd2d0461ddd2197e4f4ad4"}, "remainingTimeMS": 30}
-2026-05-08 08:43:50,985 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-08 08:43:51,012 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-08 08:51:57,553 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-08 08:51:57,570 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-08 08:52:05,523 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fdf8956fe8a54546e7c788, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fdf8956fe8a54546e7c788"}, "remainingTimeMS": 30}
-2026-05-08 08:52:28,781 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-08T14:52:28.781286+00:00
-2026-05-08 08:52:28,783 INFO backend.segmentation: [JOB c4b00bfba3cd41d8a99b995eb5a3f820] preparing_image progress=12
-2026-05-08 08:52:28,924 INFO backend.segmentation: [JOB c4b00bfba3cd41d8a99b995eb5a3f820] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
-2026-05-08 08:52:28,925 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-08 08:52:31,787 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-08 08:52:32,342 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-08 08:52:32,963 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-08 08:52:33,084 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/10657327-6236-4afa-91e1-25f259cc9a15 "HTTP/1.1 200 OK"
-2026-05-08 08:52:33,241 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-08 08:52:33,773 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-08 08:52:34,439 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=10657327-6236-4afa-91e1-25f259cc9a15 "HTTP/1.1 200 OK"
-2026-05-08 08:52:53,788 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/1ee1c9088fcbba7f467623e6851741770894d9f669f8b560de748311e8fd868e/image.webp "HTTP/1.1 200 OK"
-2026-05-08 08:52:53,901 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
-2026-05-08 08:52:53,901 INFO backend.segmentation: [JOB c4b00bfba3cd41d8a99b995eb5a3f820] saving_masks progress=92
-2026-05-08 08:52:54,078 INFO backend.segmentation: [JOB c4b00bfba3cd41d8a99b995eb5a3f820] segments_meta saved (63 segments)
-2026-05-08 08:52:54,078 INFO backend.segmentation: [JOB c4b00bfba3cd41d8a99b995eb5a3f820] done mask_count=63
-2026-05-08 08:52:54,079 INFO backend.segmentation: [UPLOAD_BG] DONE 25.297s at 2026-05-08T14:52:54.079206+00:00
-2026-05-08 08:52:54,079 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-08 08:52:56,515 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fdf8c86fe8a54546e7c789, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fdf8c86fe8a54546e7c789"}, "remainingTimeMS": 30}
-2026-05-08 08:53:03,328 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T14:53:03.328974+00:00
-2026-05-08 08:53:03,423 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-08 08:53:03,443 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 08:53:03,763 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.435s at 2026-05-08T14:53:03.763882+00:00
-2026-05-08 08:54:39,084 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T14:54:39.084466+00:00
-2026-05-08 08:54:39,183 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
-2026-05-08 08:54:39,211 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 08:54:39,457 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.373s at 2026-05-08T14:54:39.457395+00:00
-2026-05-08 08:59:40,007 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T14:59:40.007652+00:00
-2026-05-08 08:59:40,151 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-08 08:59:40,169 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 08:59:40,385 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.378s at 2026-05-08T14:59:40.385462+00:00
-2026-05-08 08:59:42,685 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T14:59:42.685637+00:00
-2026-05-08 08:59:42,813 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-08 08:59:42,832 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 08:59:43,046 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.361s at 2026-05-08T14:59:43.046868+00:00
-2026-05-08 08:59:49,536 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-08 08:59:49,552 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-08 08:59:50,331 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-08 08:59:50,348 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-08 09:00:00,500 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:00:00.500104+00:00
-2026-05-08 09:00:00,618 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
-2026-05-08 09:00:00,637 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:00:00,990 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.490s at 2026-05-08T15:00:00.990494+00:00
-2026-05-08 09:00:03,599 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:00:03.599883+00:00
-2026-05-08 09:00:03,681 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:00:03,924 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.324s at 2026-05-08T15:00:03.924300+00:00
-2026-05-08 09:00:06,073 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:00:06.073364+00:00
-2026-05-08 09:00:06,149 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:00:06,389 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.317s at 2026-05-08T15:00:06.389848+00:00
-2026-05-08 09:00:08,614 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:00:08.614656+00:00
-2026-05-08 09:00:08,694 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:00:08,933 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.319s at 2026-05-08T15:00:08.933579+00:00
-2026-05-08 09:00:15,087 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:00:15.087928+00:00
-2026-05-08 09:00:15,193 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-08 09:00:15,214 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:00:15,452 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.364s at 2026-05-08T15:00:15.452128+00:00
-2026-05-08 09:00:19,768 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:00:19.768251+00:00
-2026-05-08 09:00:20,270 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-08 09:00:20,289 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:00:20,508 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.740s at 2026-05-08T15:00:20.508968+00:00
-2026-05-08 09:01:38,338 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:01:38.338166+00:00
-2026-05-08 09:01:38,895 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
-2026-05-08 09:01:38,915 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:01:39,112 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.774s at 2026-05-08T15:01:39.112500+00:00
-2026-05-08 09:01:42,636 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:01:42.636107+00:00
-2026-05-08 09:01:42,973 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-08 09:01:42,992 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:01:43,212 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.577s at 2026-05-08T15:01:43.212843+00:00
-2026-05-08 09:01:45,698 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:01:45.698783+00:00
-2026-05-08 09:01:46,444 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-08 09:01:46,465 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:01:46,680 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.982s at 2026-05-08T15:01:46.680378+00:00
-2026-05-08 09:01:50,327 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:01:50.326916+00:00
-2026-05-08 09:01:50,647 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
-2026-05-08 09:01:50,666 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:01:50,880 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.552s at 2026-05-08T15:01:50.879093+00:00
-2026-05-08 09:01:57,091 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-08 09:01:57,117 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-08 09:01:57,294 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:01:57.294276+00:00
-2026-05-08 09:01:57,340 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:01:57,569 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.275s at 2026-05-08T15:01:57.569889+00:00
-2026-05-08 09:02:01,866 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:02:01.866951+00:00
-2026-05-08 09:02:01,933 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:02:02,153 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.287s at 2026-05-08T15:02:02.153188+00:00
-2026-05-08 09:02:04,075 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:02:04.075842+00:00
-2026-05-08 09:02:04,140 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:02:04,356 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.280s at 2026-05-08T15:02:04.356528+00:00
-2026-05-08 09:02:07,755 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:02:07.755321+00:00
-2026-05-08 09:02:07,822 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:02:08,037 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.282s at 2026-05-08T15:02:08.037106+00:00
-2026-05-08 09:02:11,723 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:02:11.723542+00:00
-2026-05-08 09:02:11,786 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:02:12,003 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.280s at 2026-05-08T15:02:12.003104+00:00
-2026-05-08 09:02:13,461 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:02:13.461067+00:00
-2026-05-08 09:02:13,526 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:02:13,743 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.283s at 2026-05-08T15:02:13.743819+00:00
-2026-05-08 09:02:17,645 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-08T15:02:17.645808+00:00
-2026-05-08 09:02:17,709 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
-2026-05-08 09:02:17,928 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.283s at 2026-05-08T15:02:17.928622+00:00
-2026-05-08 09:02:22,278 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fdfafe6c3fdb5646f67bd7, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fdfafe6c3fdb5646f67bd7"}, "remainingTimeMS": 30}
-2026-05-10 23:50:21,193 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-10 23:50:21,209 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-10 23:52:32,876 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a016ea02da1a3ba929adb9d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a016ea02da1a3ba929adb9d"}, "remainingTimeMS": 30}
-2026-05-10 23:52:36,476 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a016ea42da1a3ba929adb9e, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a016ea42da1a3ba929adb9e"}, "remainingTimeMS": 30}
-2026-05-10 23:55:43,460 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-10 23:55:43,478 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-10 23:55:50,353 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T05:55:50.353980+00:00
-2026-05-10 23:55:50,353 INFO backend.segmentation: [JOB 50532667d23b42dc9499151b792fc9be] preparing_image progress=12
-2026-05-10 23:55:50,403 INFO backend.segmentation: [JOB 50532667d23b42dc9499151b792fc9be] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-10 23:55:50,404 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-10 23:55:54,216 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-10 23:55:56,411 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-10 23:55:56,414 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-10 23:55:56,414 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-10 23:55:57,205 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-10 23:55:58,767 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/82464de0-3009-48e0-8256-dabefa0f9b77 "HTTP/1.1 200 OK"
-2026-05-10 23:58:37,808 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-10 23:58:38,440 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-10 23:58:38,988 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-10 23:58:39,041 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/19141e4f-3688-4e28-b4dd-a1f90267278f "HTTP/1.1 200 OK"
-2026-05-10 23:58:39,207 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-10 23:58:39,935 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-10 23:58:40,471 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=19141e4f-3688-4e28-b4dd-a1f90267278f "HTTP/1.1 200 OK"
-2026-05-11 00:02:34,264 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0170fae955d66f478a478e, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0170fae955d66f478a478e"}, "remainingTimeMS": 30}
-2026-05-11 00:02:41,231 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/file=/tmp/gradio/6c61c4453525a0cc97a55213f8ab16e24157b02ad4d2cba459d14b95c79ac6ab/image.webp "HTTP/1.1 200 OK"
-2026-05-11 00:02:41,371 INFO services.gradio_client_service: Gradio Space segmentation: entorno=cpu motor=SAM Auto (CPU) mask_count=61
-2026-05-11 00:02:41,371 INFO backend.segmentation: [JOB 50532667d23b42dc9499151b792fc9be] saving_masks progress=92
-2026-05-11 00:02:41,545 INFO backend.segmentation: [JOB 50532667d23b42dc9499151b792fc9be] segments_meta saved (61 segments)
-2026-05-11 00:02:41,545 INFO backend.segmentation: [JOB 50532667d23b42dc9499151b792fc9be] done mask_count=61
-2026-05-11 00:02:41,545 INFO backend.segmentation: [UPLOAD_BG] DONE 411.192s at 2026-05-11T06:02:41.545306+00:00
-2026-05-11 00:02:41,545 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 00:05:57,228 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7861
-2026-05-11 00:05:57,248 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 00:06:01,186 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0171c9cf34de01f7f36598, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0171c9cf34de01f7f36598"}, "remainingTimeMS": 30}
-2026-05-11 00:06:11,507 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T06:06:11.507814+00:00
-2026-05-11 00:06:11,507 INFO backend.segmentation: [JOB 1f4f3f9e44d3493ea86190e1c30a9fdd] preparing_image progress=12
-2026-05-11 00:06:11,556 INFO backend.segmentation: [JOB 1f4f3f9e44d3493ea86190e1c30a9fdd] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 00:06:11,556 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7861
-2026-05-11 00:06:14,167 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 00:06:16,365 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 00:06:17,144 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 00:06:18,683 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/20b82a1d-db47-495c-b48f-4921056f7df8 "HTTP/1.1 200 OK"
-2026-05-11 00:06:18,685 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 00:06:20,907 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 00:06:23,133 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=20b82a1d-db47-495c-b48f-4921056f7df8 "HTTP/1.1 200 OK"
-2026-05-11 00:07:29,155 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\fdba6c817445c957bf57f0f37d255298685625d2847381414fb08306405b69d3\image.webp "HTTP/1.1 200 OK"
-2026-05-11 00:07:29,169 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=61
-2026-05-11 00:07:29,170 INFO backend.segmentation: [JOB 1f4f3f9e44d3493ea86190e1c30a9fdd] saving_masks progress=92
-2026-05-11 00:07:29,294 INFO backend.segmentation: [JOB 1f4f3f9e44d3493ea86190e1c30a9fdd] segments_meta saved (61 segments)
-2026-05-11 00:07:29,294 INFO backend.segmentation: [JOB 1f4f3f9e44d3493ea86190e1c30a9fdd] done mask_count=61
-2026-05-11 00:07:29,294 INFO backend.segmentation: [UPLOAD_BG] DONE 77.786s at 2026-05-11T06:07:29.294219+00:00
-2026-05-11 00:07:29,294 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 00:07:30,391 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a017222cf34de01f7f36599, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a017222cf34de01f7f36599"}, "remainingTimeMS": 30}
-2026-05-11 00:08:14,893 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T06:08:14.893447+00:00
-2026-05-11 00:08:15,380 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 00:08:15,598 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.704s at 2026-05-11T06:08:15.598673+00:00
-2026-05-11 00:51:27,451 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7861
-2026-05-11 00:51:27,474 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 00:53:21,328 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a017ce16ec57028978ccf90, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a017ce16ec57028978ccf90"}, "remainingTimeMS": 30}
-2026-05-11 00:53:38,590 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T06:53:38.590375+00:00
-2026-05-11 00:53:38,591 INFO backend.segmentation: [JOB 8b7706cec4fb4c95b959cf35c8a37258] preparing_image progress=12
-2026-05-11 00:53:38,710 INFO backend.segmentation: [JOB 8b7706cec4fb4c95b959cf35c8a37258] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 00:53:38,711 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7861
-2026-05-11 00:53:42,759 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 00:53:44,976 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 00:53:45,852 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 00:53:47,365 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/1416991c-29e3-460c-b632-eb0401ae0d7b "HTTP/1.1 200 OK"
-2026-05-11 00:53:47,401 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 00:53:49,676 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 00:53:51,904 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=1416991c-29e3-460c-b632-eb0401ae0d7b "HTTP/1.1 200 OK"
-2026-05-11 00:54:57,193 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\fdba6c817445c957bf57f0f37d255298685625d2847381414fb08306405b69d3\image.webp "HTTP/1.1 200 OK"
-2026-05-11 00:54:57,211 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=61
-2026-05-11 00:54:57,211 INFO backend.segmentation: [JOB 8b7706cec4fb4c95b959cf35c8a37258] saving_masks progress=92
-2026-05-11 00:54:57,393 INFO backend.segmentation: [JOB 8b7706cec4fb4c95b959cf35c8a37258] segments_meta saved (61 segments)
-2026-05-11 00:54:57,393 INFO backend.segmentation: [JOB 8b7706cec4fb4c95b959cf35c8a37258] done mask_count=61
-2026-05-11 00:54:57,393 INFO backend.segmentation: [UPLOAD_BG] DONE 78.803s at 2026-05-11T06:54:57.393436+00:00
-2026-05-11 00:54:57,393 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 00:55:00,244 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a017d446ec57028978ccf91, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a017d446ec57028978ccf91"}, "remainingTimeMS": 30}
-2026-05-11 00:59:39,555 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7861
-2026-05-11 00:59:39,579 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 00:59:40,470 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7861
-2026-05-11 00:59:40,489 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 00:59:40,500 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T06:59:40.500380+00:00
-2026-05-11 00:59:44,733 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 00:59:46,960 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 00:59:47,683 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 00:59:49,313 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/dfe3d93e-bb61-4ec9-a8f0-c028f671768d "HTTP/1.1 200 OK"
-2026-05-11 00:59:49,315 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 00:59:51,671 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 00:59:53,909 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=dfe3d93e-bb61-4ec9-a8f0-c028f671768d "HTTP/1.1 200 OK"
-2026-05-11 00:59:58,487 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a017e6eb594a05c6412d9b7, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a017e6eb594a05c6412d9b7"}, "remainingTimeMS": 30}
-2026-05-11 00:59:58,935 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a017e6eb594a05c6412d9b8, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a017e6eb594a05c6412d9b8"}, "remainingTimeMS": 30}
-2026-05-11 01:00:01,269 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:00:01.269120+00:00
-2026-05-11 01:00:06,217 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:00:06,576 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\6fccbecf855f58faeb9c353aa676bbc1217a2f78a3531d0266304a8da20e5470\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:00:06,583 ERROR backend.segmentation: Failed to save rendered image from Gradio Space
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\texture_service.py", line 727, in apply_local_texture_sync
-    img_to_save = Image.open(io.BytesIO(rendered_img_np))
-                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
-TypeError: a bytes-like object is required, not 'str'
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\texture_service.py", line 729, in apply_local_texture_sync
-    raise RuntimeError("Unsupported rendered image type from Gradio Space")
-RuntimeError: Unsupported rendered image type from Gradio Space
-2026-05-11 01:00:06,585 ERROR backend.segmentation: Error during remote render integration (continuing local flow)
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\texture_service.py", line 727, in apply_local_texture_sync
-    img_to_save = Image.open(io.BytesIO(rendered_img_np))
-                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
-TypeError: a bytes-like object is required, not 'str'
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\texture_service.py", line 729, in apply_local_texture_sync
-    raise RuntimeError("Unsupported rendered image type from Gradio Space")
-RuntimeError: Unsupported rendered image type from Gradio Space
-2026-05-11 01:00:06,942 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 01:00:07,163 INFO backend.segmentation: [APPLY_TEXTURE] DONE 26.663s at 2026-05-11T07:00:07.163579+00:00
-2026-05-11 01:00:08,434 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:00:08,866 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:00:10,719 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/4f697b34-1aa2-41df-bfd1-f19982489f24 "HTTP/1.1 200 OK"
-2026-05-11 01:00:10,737 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:00:13,075 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:00:15,289 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=4f697b34-1aa2-41df-bfd1-f19982489f24 "HTTP/1.1 200 OK"
-2026-05-11 01:00:25,135 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\6fccbecf855f58faeb9c353aa676bbc1217a2f78a3531d0266304a8da20e5470\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:00:25,144 ERROR backend.segmentation: Failed to save rendered image from Gradio Space
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\texture_service.py", line 727, in apply_local_texture_sync
-    img_to_save = Image.open(io.BytesIO(rendered_img_np))
-                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
-TypeError: a bytes-like object is required, not 'str'
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\texture_service.py", line 729, in apply_local_texture_sync
-    raise RuntimeError("Unsupported rendered image type from Gradio Space")
-RuntimeError: Unsupported rendered image type from Gradio Space
-2026-05-11 01:00:25,145 ERROR backend.segmentation: Error during remote render integration (continuing local flow)
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\texture_service.py", line 727, in apply_local_texture_sync
-    img_to_save = Image.open(io.BytesIO(rendered_img_np))
-                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
-TypeError: a bytes-like object is required, not 'str'
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\texture_service.py", line 729, in apply_local_texture_sync
-    raise RuntimeError("Unsupported rendered image type from Gradio Space")
-RuntimeError: Unsupported rendered image type from Gradio Space
-2026-05-11 01:00:25,508 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 01:00:25,634 INFO backend.segmentation: [APPLY_TEXTURE] DONE 24.365s at 2026-05-11T07:00:25.634920+00:00
-2026-05-11 01:01:58,589 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7861
-2026-05-11 01:01:58,609 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 01:02:22,178 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7861
-2026-05-11 01:02:22,198 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 01:02:51,769 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a017f1bad7663b910938dbd, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a017f1bad7663b910938dbd"}, "remainingTimeMS": 30}
-2026-05-11 01:02:55,731 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:02:55.731211+00:00
-2026-05-11 01:02:59,246 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:03:01,470 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:03:02,157 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:03:03,788 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/f72e320f-3dd3-495b-8cb0-2aa97d6ec2c9 "HTTP/1.1 200 OK"
-2026-05-11 01:03:03,790 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:03:06,063 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:03:08,281 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=f72e320f-3dd3-495b-8cb0-2aa97d6ec2c9 "HTTP/1.1 200 OK"
-2026-05-11 01:03:18,072 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\a0241ac3d66d043389ee63208cf8e598c5bc14a88f1ef0c0ba1204972c9b8f5b\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:03:18,112 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.382s at 2026-05-11T07:03:18.112675+00:00
-2026-05-11 01:03:28,574 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:03:28.574697+00:00
-2026-05-11 01:03:31,794 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:03:34,004 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:03:34,436 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:03:36,294 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/5c32843d-f6f9-460a-8e54-d92cbde9f493 "HTTP/1.1 200 OK"
-2026-05-11 01:03:36,298 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:03:38,567 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:03:40,815 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=5c32843d-f6f9-460a-8e54-d92cbde9f493 "HTTP/1.1 200 OK"
-2026-05-11 01:03:50,473 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\a36f7f6ce561ff2da1d9b2cd19f3166ad95e0ea69bfa43c4cacd37d43e5f0baf\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:03:50,507 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.933s at 2026-05-11T07:03:50.507525+00:00
-2026-05-11 01:03:53,829 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:03:53.829203+00:00
-2026-05-11 01:03:57,076 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:03:59,329 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:03:59,834 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:04:01,620 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/0f966dad-edde-44bb-a9ef-2facb570ff26 "HTTP/1.1 200 OK"
-2026-05-11 01:04:01,623 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:04:03,890 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:04:06,134 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=0f966dad-edde-44bb-a9ef-2facb570ff26 "HTTP/1.1 200 OK"
-2026-05-11 01:04:14,611 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\fdb10066803e396b080246b5d53f1444b85ab32ce2f8adc8055ac70779eda6c7\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:04:14,643 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.815s at 2026-05-11T07:04:14.643822+00:00
-2026-05-11 01:04:31,068 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:04:31.068679+00:00
-2026-05-11 01:04:34,297 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:04:36,522 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:04:36,916 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:04:38,792 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/41a45a3b-dea6-401b-a961-a43d9eeef146 "HTTP/1.1 200 OK"
-2026-05-11 01:04:38,812 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:04:41,051 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:04:43,255 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=41a45a3b-dea6-401b-a961-a43d9eeef146 "HTTP/1.1 200 OK"
-2026-05-11 01:04:53,175 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\c90fa2a168435724e938bd973efa0671ee7b1e14a32cfe2953cccdcddaeed9bd\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:04:53,208 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.139s at 2026-05-11T07:04:53.208514+00:00
-2026-05-11 01:05:04,897 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:05:04.897914+00:00
-2026-05-11 01:05:08,149 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:05:10,379 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:05:10,869 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:05:12,635 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:05:12,646 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/7f5b04fc-b432-4af7-b397-2093bc848196 "HTTP/1.1 200 OK"
-2026-05-11 01:05:14,897 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:05:17,124 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=7f5b04fc-b432-4af7-b397-2093bc848196 "HTTP/1.1 200 OK"
-2026-05-11 01:05:26,777 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\b800eda83c12f620804b3039c42adc116f1df79b420071d9a18c7e119021b832\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:05:26,810 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.913s at 2026-05-11T07:05:26.810808+00:00
-2026-05-11 01:06:12,011 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:06:12.011565+00:00
-2026-05-11 01:06:17,137 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:06:19,606 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:06:20,093 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:06:22,130 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/f6d57324-aa5d-428e-9a3c-6ceb59836305 "HTTP/1.1 200 OK"
-2026-05-11 01:06:22,133 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:06:24,805 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:06:27,208 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=f6d57324-aa5d-428e-9a3c-6ceb59836305 "HTTP/1.1 200 OK"
-2026-05-11 01:06:45,355 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\8f50dc9664f9587eae53015e1509b997c04fa98036c9290e6187367512d5da02\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:06:45,416 INFO backend.segmentation: [APPLY_TEXTURE] DONE 33.406s at 2026-05-11T07:06:45.416640+00:00
-2026-05-11 01:07:09,613 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:07:09.613619+00:00
-2026-05-11 01:07:13,446 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:07:15,702 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:07:16,128 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:07:17,980 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/e84e78f6-9732-4236-a1bf-7e9cc1a9b774 "HTTP/1.1 200 OK"
-2026-05-11 01:07:17,997 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:07:20,296 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:07:22,537 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=e84e78f6-9732-4236-a1bf-7e9cc1a9b774 "HTTP/1.1 200 OK"
-2026-05-11 01:07:32,944 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\6227d070ade7cde210e2e9d7df63c2d27989256a412e8ea36974e0a59a13015e\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:07:32,984 INFO backend.segmentation: [APPLY_TEXTURE] DONE 23.370s at 2026-05-11T07:07:32.984168+00:00
-2026-05-11 01:07:48,931 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:07:48.931971+00:00
-2026-05-11 01:07:52,682 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:07:54,896 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:07:55,375 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:07:57,190 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:07:57,201 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/96094a24-9182-483a-8561-4e4e55af553b "HTTP/1.1 200 OK"
-2026-05-11 01:07:59,536 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:08:01,765 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=96094a24-9182-483a-8561-4e4e55af553b "HTTP/1.1 200 OK"
-2026-05-11 01:08:10,238 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\1c41a512aed2c50d7f0c6d4ea72379809f2a3f46e105a41f0f9e38565785841d\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:08:10,282 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.350s at 2026-05-11T07:08:10.282480+00:00
-2026-05-11 01:08:38,560 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:08:38.560140+00:00
-2026-05-11 01:08:42,343 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:08:44,570 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:08:45,003 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:08:46,839 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/f8529758-c796-4224-be4c-2294112a68b7 "HTTP/1.1 200 OK"
-2026-05-11 01:08:46,841 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:08:49,157 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:08:51,365 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=f8529758-c796-4224-be4c-2294112a68b7 "HTTP/1.1 200 OK"
-2026-05-11 01:09:00,651 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\15f80783b48749ce17b32cc0aa708fd16e5c3c4952e7baa88b58688069e2372f\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:09:00,686 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.127s at 2026-05-11T07:09:00.686616+00:00
-2026-05-11 01:09:14,687 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:09:14.687785+00:00
-2026-05-11 01:09:18,535 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:09:20,758 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:09:21,287 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:09:23,032 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/f0604982-22f5-4b8b-b79c-d21ea5d2c527 "HTTP/1.1 200 OK"
-2026-05-11 01:09:23,051 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:09:25,370 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:09:27,610 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=f0604982-22f5-4b8b-b79c-d21ea5d2c527 "HTTP/1.1 200 OK"
-2026-05-11 01:09:36,614 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\37c1f8856b784b099916f708990bea28fe50688285c475371b20d242b5fbf0a6\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:09:36,662 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.974s at 2026-05-11T07:09:36.662611+00:00
-2026-05-11 01:09:47,181 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:09:47.181137+00:00
-2026-05-11 01:09:50,937 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:09:53,178 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:09:53,603 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:09:55,458 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/8a3b75ca-572e-4915-be54-edf2e0ae0929 "HTTP/1.1 200 OK"
-2026-05-11 01:09:55,460 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:09:57,802 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:10:00,032 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=8a3b75ca-572e-4915-be54-edf2e0ae0929 "HTTP/1.1 200 OK"
-2026-05-11 01:10:09,202 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:10:09,238 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar), trying CPU fallback...
-2026-05-11 01:10:09,879 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 01:10:10,458 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:10:10,527 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7861): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 01:10:10,942 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:10:10,996 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 01:10:11,006 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/327144cd-fa09-4141-b0bb-37f9c05564a8 "HTTP/1.1 200 OK"
-2026-05-11 01:10:11,380 INFO backend.segmentation: [APPLY_TEXTURE] DONE 24.200s at 2026-05-11T07:10:11.380471+00:00
-2026-05-11 01:10:44,673 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:10:44.673006+00:00
-2026-05-11 01:10:48,706 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:10:50,923 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:10:51,405 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:10:53,196 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/60ad61fc-6e8a-4f70-a9cf-0326c71edd29 "HTTP/1.1 200 OK"
-2026-05-11 01:10:53,214 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:10:55,575 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:10:57,809 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=60ad61fc-6e8a-4f70-a9cf-0326c71edd29 "HTTP/1.1 200 OK"
-2026-05-11 01:11:07,574 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\809563183a76c7f74f9f6ea49fc9595d2a95fa1bcfe5985fa4450dc8dffbe6e7\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:11:07,609 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.936s at 2026-05-11T07:11:07.609355+00:00
-2026-05-11 01:11:37,447 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:11:37.447764+00:00
-2026-05-11 01:11:41,514 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:11:43,748 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:11:44,151 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:11:46,044 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/926557a0-6f74-4161-9a0a-49d0f9ec5923 "HTTP/1.1 200 OK"
-2026-05-11 01:11:46,048 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:11:48,400 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:11:50,602 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=926557a0-6f74-4161-9a0a-49d0f9ec5923 "HTTP/1.1 200 OK"
-2026-05-11 01:11:59,284 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\503643d8a558a4c61557d2f2c7cdb8ad6d7f9d88fe3d57d119821583a0acfb15\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:11:59,319 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.871s at 2026-05-11T07:11:59.319274+00:00
-2026-05-11 01:12:24,802 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:12:24.802666+00:00
-2026-05-11 01:12:28,874 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:12:31,118 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:12:32,344 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:12:33,430 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/aa4ce6a4-a3b8-48d4-b8a2-aae8b10bc2b2 "HTTP/1.1 200 OK"
-2026-05-11 01:12:33,434 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:12:35,777 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:12:38,002 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=aa4ce6a4-a3b8-48d4-b8a2-aae8b10bc2b2 "HTTP/1.1 200 OK"
-2026-05-11 01:12:47,307 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\0dab17a794d09e675c5ecbabf7e0aa9b84acce9db17be10ee180bca4497b7945\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:12:47,344 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.542s at 2026-05-11T07:12:47.344700+00:00
-2026-05-11 01:12:58,776 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:12:58.776347+00:00
-2026-05-11 01:13:02,833 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:13:05,204 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:13:05,637 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:13:07,486 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/5128ebf4-bef1-4557-887f-9c1d62bef7e3 "HTTP/1.1 200 OK"
-2026-05-11 01:13:07,488 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:13:09,774 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:13:11,988 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=5128ebf4-bef1-4557-887f-9c1d62bef7e3 "HTTP/1.1 200 OK"
-2026-05-11 01:13:23,874 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\774616f6c0df92ecd7c74569be071f234650be2c0b86f09160baec998dfd5c90\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:13:23,908 INFO backend.segmentation: [APPLY_TEXTURE] DONE 25.132s at 2026-05-11T07:13:23.908609+00:00
-2026-05-11 01:13:35,636 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:13:35.636648+00:00
-2026-05-11 01:13:39,412 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:13:41,649 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:13:42,161 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:13:43,959 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/683cce21-955f-4df7-ae78-2a94dd251026 "HTTP/1.1 200 OK"
-2026-05-11 01:13:43,960 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:13:46,266 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:13:48,491 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=683cce21-955f-4df7-ae78-2a94dd251026 "HTTP/1.1 200 OK"
-2026-05-11 01:14:00,798 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\24655a4c5a1c05a05c0d28ce9352f9d0b7a3aa2f81a2edea9cf9417691adc9a3\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:14:00,832 INFO backend.segmentation: [APPLY_TEXTURE] DONE 25.196s at 2026-05-11T07:14:00.832652+00:00
-2026-05-11 01:14:10,101 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0181c2ad7663b910938dbe, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0181c2ad7663b910938dbe"}, "remainingTimeMS": 30}
-2026-05-11 01:14:15,444 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T07:14:15.444171+00:00
-2026-05-11 01:14:15,445 INFO backend.segmentation: [JOB 9c35bdf672b24aa8ab2f8c7d741909d6] preparing_image progress=12
-2026-05-11 01:14:15,480 INFO backend.segmentation: [JOB 9c35bdf672b24aa8ab2f8c7d741909d6] segmenting_with_sam2 progress=30 estimated_seconds=94.01599999999999
-2026-05-11 01:14:15,480 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7861
-2026-05-11 01:14:17,755 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:14:19,987 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:14:20,404 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:14:22,250 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/fe34eec8-6368-444c-b506-e7d57c0b670b "HTTP/1.1 200 OK"
-2026-05-11 01:14:22,269 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:14:24,498 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:14:26,739 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=fe34eec8-6368-444c-b506-e7d57c0b670b "HTTP/1.1 200 OK"
-2026-05-11 01:15:38,919 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\56758f540e1c547de434b369fae158810fde033fe3650199c54eecf9fd68ac46\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:15:38,938 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=58
-2026-05-11 01:15:38,939 INFO backend.segmentation: [JOB 9c35bdf672b24aa8ab2f8c7d741909d6] saving_masks progress=92
-2026-05-11 01:15:39,189 INFO backend.segmentation: [JOB 9c35bdf672b24aa8ab2f8c7d741909d6] segments_meta saved (58 segments)
-2026-05-11 01:15:39,189 INFO backend.segmentation: [JOB 9c35bdf672b24aa8ab2f8c7d741909d6] done mask_count=58
-2026-05-11 01:15:39,189 INFO backend.segmentation: [UPLOAD_BG] DONE 83.745s at 2026-05-11T07:15:39.189518+00:00
-2026-05-11 01:15:39,189 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 01:15:48,737 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:15:48.737247+00:00
-2026-05-11 01:15:49,707 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:15:49.707744+00:00
-2026-05-11 01:15:52,680 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:15:53,631 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:15:54,911 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:15:55,468 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:15:55,845 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:15:56,044 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:15:57,202 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/4a705aa0-f689-46ea-97f5-15863d8baec8 "HTTP/1.1 200 OK"
-2026-05-11 01:15:57,203 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:15:58,124 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/a2c2c118-eaf6-434d-a743-2fe1deddff99 "HTTP/1.1 200 OK"
-2026-05-11 01:15:58,127 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:15:59,497 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:16:00,430 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:16:01,745 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=4a705aa0-f689-46ea-97f5-15863d8baec8 "HTTP/1.1 200 OK"
-2026-05-11 01:16:02,667 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=a2c2c118-eaf6-434d-a743-2fe1deddff99 "HTTP/1.1 200 OK"
-2026-05-11 01:16:12,415 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\9931b16150cffe4276187d82f98d6d26f2e65768a9a5e29c4841a0cd0ace8c43\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:16:12,476 INFO backend.segmentation: [APPLY_TEXTURE] DONE 23.739s at 2026-05-11T07:16:12.476106+00:00
-2026-05-11 01:16:22,102 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\9931b16150cffe4276187d82f98d6d26f2e65768a9a5e29c4841a0cd0ace8c43\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:16:22,141 INFO backend.segmentation: [APPLY_TEXTURE] DONE 32.434s at 2026-05-11T07:16:22.141876+00:00
-2026-05-11 01:16:34,010 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:16:34.010080+00:00
-2026-05-11 01:16:38,027 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:16:40,260 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:16:40,735 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:16:42,572 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:16:42,584 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/931da22b-6ab6-43e4-bbb1-7f28e8bed3df "HTTP/1.1 200 OK"
-2026-05-11 01:16:44,939 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:16:47,207 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=931da22b-6ab6-43e4-bbb1-7f28e8bed3df "HTTP/1.1 200 OK"
-2026-05-11 01:16:56,571 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\89f7e761e614acc1ce7980f1bc3a57c44c02acffdf1327e62d01abf19e7ac3dd\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:16:56,618 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.608s at 2026-05-11T07:16:56.618223+00:00
-2026-05-11 01:17:21,863 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:17:21.863478+00:00
-2026-05-11 01:17:25,635 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:17:27,850 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:17:28,328 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:17:30,124 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/78467926-f639-4fff-b594-b22e73a4e796 "HTTP/1.1 200 OK"
-2026-05-11 01:17:30,127 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:17:32,444 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:17:34,654 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=78467926-f639-4fff-b594-b22e73a4e796 "HTTP/1.1 200 OK"
-2026-05-11 01:17:43,596 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:17:43,600 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 102, in render
-    canvas = self._tile_texture(texture, tiles_x, tiles_y)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio), trying CPU fallback...
-2026-05-11 01:17:44,204 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 01:17:44,752 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:17:44,814 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7861): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 102, in render
-    canvas = self._tile_texture(texture, tiles_x, tiles_y)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 01:17:45,194 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-11 01:17:45,236 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:17:45,299 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/91179f12-20de-4391-a947-92fac749b4a8 "HTTP/1.1 200 OK"
-2026-05-11 01:17:45,490 INFO backend.segmentation: [APPLY_TEXTURE] DONE 23.628s at 2026-05-11T07:17:45.490550+00:00
-2026-05-11 01:18:02,698 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:18:02.698716+00:00
-2026-05-11 01:18:06,674 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:18:08,930 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:18:09,363 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:18:11,211 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/72669362-1cf1-469d-83d1-9b080846fd90 "HTTP/1.1 200 OK"
-2026-05-11 01:18:11,228 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:18:13,530 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:18:15,794 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=72669362-1cf1-469d-83d1-9b080846fd90 "HTTP/1.1 200 OK"
-2026-05-11 01:18:25,648 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:18:25,652 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 102, in render
-    canvas = self._tile_texture(texture, tiles_x, tiles_y)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio), trying CPU fallback...
-2026-05-11 01:18:26,163 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 01:18:26,695 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:18:26,760 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7861): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 102, in render
-    canvas = self._tile_texture(texture, tiles_x, tiles_y)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 01:18:27,097 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-11 01:18:27,167 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:18:27,244 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/e3493f6c-8216-4b3c-ad23-6be8bfee608c "HTTP/1.1 200 OK"
-2026-05-11 01:18:27,350 INFO backend.segmentation: [APPLY_TEXTURE] DONE 24.652s at 2026-05-11T07:18:27.350458+00:00
-2026-05-11 01:19:25,431 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:19:25.430391+00:00
-2026-05-11 01:19:31,260 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:19:33,529 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:19:34,187 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:19:36,012 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/219efbdb-1ac5-4065-ab0a-4961533a75b8 "HTTP/1.1 200 OK"
-2026-05-11 01:19:36,041 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:19:38,405 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:19:40,673 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=219efbdb-1ac5-4065-ab0a-4961533a75b8 "HTTP/1.1 200 OK"
-2026-05-11 01:19:56,234 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\fa7fc0fa70fe0bd04e4a677d0ff7567cb5e73db42518b2f94804471cb2f180a3\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:19:56,347 INFO backend.segmentation: [APPLY_TEXTURE] DONE 30.917s at 2026-05-11T07:19:56.347937+00:00
-2026-05-11 01:21:43,185 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T07:21:43.185923+00:00
-2026-05-11 01:21:46,987 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
-2026-05-11 01:21:49,209 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:21:49,685 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:21:51,506 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/8ef4194a-039a-4899-abbe-ed9c2a60cef3 "HTTP/1.1 200 OK"
-2026-05-11 01:21:51,512 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 01:21:53,789 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 01:21:55,997 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=8ef4194a-039a-4899-abbe-ed9c2a60cef3 "HTTP/1.1 200 OK"
-2026-05-11 01:22:11,314 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 01:22:11,322 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 102, in render
-    canvas = self._tile_texture(texture, tiles_x, tiles_y)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio), trying CPU fallback...
-2026-05-11 01:22:11,894 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 01:22:12,458 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 01:22:12,524 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7861): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 102, in render
-    canvas = self._tile_texture(texture, tiles_x, tiles_y)
-             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 01:22:12,912 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
-2026-05-11 01:22:12,938 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 01:22:13,030 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/284ba0cb-0966-4791-889d-4043f7997679 "HTTP/1.1 200 OK"
-2026-05-11 01:22:13,210 INFO backend.segmentation: [APPLY_TEXTURE] DONE 30.024s at 2026-05-11T07:22:13.210393+00:00
-2026-05-11 07:13:12,698 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7861
-2026-05-11 07:13:12,725 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 07:13:50,328 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a01d60ed81163beadabb83e, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a01d60ed81163beadabb83e"}, "remainingTimeMS": 30}
-2026-05-11 07:13:58,568 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a01d616d81163beadabb83f, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a01d616d81163beadabb83f"}, "remainingTimeMS": 30}
-2026-05-11 07:15:33,988 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 07:15:34,010 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 07:15:45,946 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:15:45.946655+00:00
-2026-05-11 07:15:50,295 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:15:52,507 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:15:53,306 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:15:54,828 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/a11ee22c-36e3-4b24-981b-db3d93d99bea "HTTP/1.1 200 OK"
-2026-05-11 07:15:54,847 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:15:57,142 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:15:59,380 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=a11ee22c-36e3-4b24-981b-db3d93d99bea "HTTP/1.1 200 OK"
-2026-05-11 07:16:09,721 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\729d40f29feb319d3a68ae2b4fea5c683335ec7a103e3d78bd6a9d1387940f36\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:16:09,783 INFO backend.segmentation: [APPLY_TEXTURE] DONE 23.837s at 2026-05-11T13:16:09.783095+00:00
-2026-05-11 07:17:13,338 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:17:13.338368+00:00
-2026-05-11 07:17:18,532 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:17:20,901 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:17:21,366 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:17:23,344 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/f6e2a1f3-2f5d-4db3-b90b-44c39de26562 "HTTP/1.1 200 OK"
-2026-05-11 07:17:23,378 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:17:25,720 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:17:28,103 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=f6e2a1f3-2f5d-4db3-b90b-44c39de26562 "HTTP/1.1 200 OK"
-2026-05-11 07:17:41,263 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\675d61dd04d77c05fa3d52350471a44ad72ba1d471483f3a9aed39ed7a39af6a\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:17:41,323 INFO backend.segmentation: [APPLY_TEXTURE] DONE 27.985s at 2026-05-11T13:17:41.323349+00:00
-2026-05-11 07:17:55,935 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:17:55.935240+00:00
-2026-05-11 07:18:01,174 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:18:03,556 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:18:03,975 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:18:05,991 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:18:06,001 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/c29c2207-1ec3-4503-8893-9012e86a29e1 "HTTP/1.1 200 OK"
-2026-05-11 07:18:08,513 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:18:10,864 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=c29c2207-1ec3-4503-8893-9012e86a29e1 "HTTP/1.1 200 OK"
-2026-05-11 07:18:24,554 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\ccbb8ca6c7e4be2509d23cfc58038fb418eb8cd45d3d4d98a6d8775a3b07f85a\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:18:24,627 INFO backend.segmentation: [APPLY_TEXTURE] DONE 28.693s at 2026-05-11T13:18:24.627719+00:00
-2026-05-11 07:18:33,797 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:18:33.797526+00:00
-2026-05-11 07:18:39,002 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:18:41,357 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:18:41,968 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:18:43,632 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/8ad846f5-30d0-476f-80e2-c217afbf0803 "HTTP/1.1 200 OK"
-2026-05-11 07:18:43,635 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:18:46,182 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:18:48,596 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=8ad846f5-30d0-476f-80e2-c217afbf0803 "HTTP/1.1 200 OK"
-2026-05-11 07:19:01,667 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28a68084867dd6206a2dc79b6123ec746f4a27cb24d83120172efbf07f8dd75\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:19:01,731 INFO backend.segmentation: [APPLY_TEXTURE] DONE 27.934s at 2026-05-11T13:19:01.731818+00:00
-2026-05-11 07:19:18,283 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:19:18.283374+00:00
-2026-05-11 07:19:23,498 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:19:25,870 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:19:26,324 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:19:28,331 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/7c18efe0-2aa1-4a8c-b4de-45ff5ed748d0 "HTTP/1.1 200 OK"
-2026-05-11 07:19:28,335 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:19:30,917 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:19:33,358 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=7c18efe0-2aa1-4a8c-b4de-45ff5ed748d0 "HTTP/1.1 200 OK"
-2026-05-11 07:19:48,011 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\22e6a58307d452f4902fa2fb6a95d27241b0ee925497e2ea8e996c57055a5054\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:19:48,073 INFO backend.segmentation: [APPLY_TEXTURE] DONE 29.790s at 2026-05-11T13:19:48.073114+00:00
-2026-05-11 07:21:10,171 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a01d7c64751e61bdffcd21f, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a01d7c64751e61bdffcd21f"}, "remainingTimeMS": 30}
-2026-05-11 07:21:11,111 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a01d7c74751e61bdffcd220, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a01d7c74751e61bdffcd220"}, "remainingTimeMS": 30}
-2026-05-11 07:21:20,560 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:21:20.560364+00:00
-2026-05-11 07:21:20,666 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:21:21,019 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.459s at 2026-05-11T13:21:21.019762+00:00
-2026-05-11 07:27:15,633 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:27:15.633288+00:00
-2026-05-11 07:27:18,221 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:27:20,612 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:27:21,121 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:27:23,064 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:27:23,090 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/325c2bf9-7929-4ac4-8a3d-9b33144e56b7 "HTTP/1.1 200 OK"
-2026-05-11 07:27:25,397 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:27:27,782 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=325c2bf9-7929-4ac4-8a3d-9b33144e56b7 "HTTP/1.1 200 OK"
-2026-05-11 07:27:42,623 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f8362e21088d5fd20e87ed36619f4fe1d0e0a2bc6ab13bdd8b4706d6b235624c\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:27:42,670 INFO backend.segmentation: [APPLY_TEXTURE] DONE 27.038s at 2026-05-11T13:27:42.670991+00:00
-2026-05-11 07:27:49,357 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 07:27:49,376 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 07:27:50,356 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 07:27:50,373 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 07:27:50,535 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:27:50.535701+00:00
-2026-05-11 07:27:53,100 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:27:55,364 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:27:56,034 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:27:57,702 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/937d3390-5a64-49f4-8474-ccf21a7b6729 "HTTP/1.1 200 OK"
-2026-05-11 07:27:57,704 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:27:59,916 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:28:02,136 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=937d3390-5a64-49f4-8474-ccf21a7b6729 "HTTP/1.1 200 OK"
-2026-05-11 07:28:09,421 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\110d2842ccb4068c48b39f1b64f6346b8d4250df6032fb5fcd0702f592783ada\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:28:09,461 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.926s at 2026-05-11T13:28:09.461663+00:00
-2026-05-11 07:28:25,643 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:28:25.643454+00:00
-2026-05-11 07:28:27,945 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:28:30,179 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:28:30,670 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:28:32,504 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/cc5f45a1-db87-4c3f-bb12-92f9dd7a18d9 "HTTP/1.1 200 OK"
-2026-05-11 07:28:32,523 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:28:34,759 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:28:37,032 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=cc5f45a1-db87-4c3f-bb12-92f9dd7a18d9 "HTTP/1.1 200 OK"
-2026-05-11 07:28:44,468 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\71a2029e9d632f4b23f28f463bbc5aa1c286b2dee733c22db45bd5e1efaf8736\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:28:44,509 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.866s at 2026-05-11T13:28:44.509013+00:00
-2026-05-11 07:29:09,586 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:29:09.585246+00:00
-2026-05-11 07:29:11,883 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:29:14,093 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:29:14,652 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:29:16,350 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/bc41025f-ff7c-473a-99a4-e2866e146d8f "HTTP/1.1 200 OK"
-2026-05-11 07:29:16,369 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:29:18,602 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:29:20,825 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=bc41025f-ff7c-473a-99a4-e2866e146d8f "HTTP/1.1 200 OK"
-2026-05-11 07:29:28,367 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\71a2029e9d632f4b23f28f463bbc5aa1c286b2dee733c22db45bd5e1efaf8736\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:29:28,407 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.822s at 2026-05-11T13:29:28.407606+00:00
-2026-05-11 07:29:43,030 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:29:43.029505+00:00
-2026-05-11 07:29:45,332 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:29:47,555 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:29:48,053 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:29:49,850 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9b7c17df-0072-4385-8c82-f8409904d2c0 "HTTP/1.1 200 OK"
-2026-05-11 07:29:49,867 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:29:52,080 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:29:54,315 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9b7c17df-0072-4385-8c82-f8409904d2c0 "HTTP/1.1 200 OK"
-2026-05-11 07:30:01,480 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\25f8fa5117371da311a2a13bd9132fa18bd3932b0e211851a8ae1228ddc2fce9\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:30:01,520 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.491s at 2026-05-11T13:30:01.520860+00:00
-2026-05-11 07:33:43,650 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:33:43.650065+00:00
-2026-05-11 07:33:43,719 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:33:43,984 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.334s at 2026-05-11T13:33:43.984042+00:00
-2026-05-11 07:33:50,055 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 07:33:50,072 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 07:33:50,909 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 07:33:50,928 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 07:33:55,052 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:33:55.052005+00:00
-2026-05-11 07:33:55,120 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:33:55,356 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.304s at 2026-05-11T13:33:55.356129+00:00
-2026-05-11 07:34:02,218 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:34:02.218913+00:00
-2026-05-11 07:34:02,283 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:34:02,430 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.211s at 2026-05-11T13:34:02.430738+00:00
-2026-05-11 07:34:18,953 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 07:34:18,970 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 07:34:59,144 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:34:59.144946+00:00
-2026-05-11 07:34:59,206 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:34:59,450 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.305s at 2026-05-11T13:34:59.450085+00:00
-2026-05-11 07:35:06,472 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:35:06.472072+00:00
-2026-05-11 07:35:06,536 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:35:06,689 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.217s at 2026-05-11T13:35:06.689925+00:00
-2026-05-11 07:35:09,562 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:35:09.562481+00:00
-2026-05-11 07:35:09,621 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:35:09,776 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.214s at 2026-05-11T13:35:09.775774+00:00
-2026-05-11 07:35:16,445 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:35:16.445541+00:00
-2026-05-11 07:35:18,941 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:35:21,128 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:35:21,947 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:35:23,459 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e4b31458-bd8a-4287-ae80-b3088c6194e8 "HTTP/1.1 200 OK"
-2026-05-11 07:35:23,477 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:35:25,713 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:35:27,923 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e4b31458-bd8a-4287-ae80-b3088c6194e8 "HTTP/1.1 200 OK"
-2026-05-11 07:35:34,823 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\0338ca15cb59376406f9703a5fafbe1d16bce8078421b9b5f070f58ae0e1ddf3\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:35:34,864 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.419s at 2026-05-11T13:35:34.864504+00:00
-2026-05-11 07:35:41,607 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:35:41.607751+00:00
-2026-05-11 07:35:41,661 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:35:41,798 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.191s at 2026-05-11T13:35:41.798823+00:00
-2026-05-11 07:36:11,418 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:36:11.418408+00:00
-2026-05-11 07:36:11,482 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:36:11,630 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.212s at 2026-05-11T13:36:11.630491+00:00
-2026-05-11 07:38:10,674 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:38:10.674971+00:00
-2026-05-11 07:38:10,733 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:38:10,874 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.199s at 2026-05-11T13:38:10.874147+00:00
-2026-05-11 07:38:14,602 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:38:14.602624+00:00
-2026-05-11 07:38:14,659 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:38:14,788 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.186s at 2026-05-11T13:38:14.788434+00:00
-2026-05-11 07:38:16,586 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:38:16.586749+00:00
-2026-05-11 07:38:16,638 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:38:16,775 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.189s at 2026-05-11T13:38:16.775439+00:00
-2026-05-11 07:38:22,824 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 07:38:22,841 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 07:38:23,729 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 07:38:23,748 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 07:38:24,732 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:38:24.732831+00:00
-2026-05-11 07:38:27,246 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:38:29,471 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:38:30,373 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:38:31,820 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/0bde684e-9409-42df-85ba-a06b9ce26f5d "HTTP/1.1 200 OK"
-2026-05-11 07:38:31,823 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:38:34,067 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:38:36,312 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=0bde684e-9409-42df-85ba-a06b9ce26f5d "HTTP/1.1 200 OK"
-2026-05-11 07:38:44,753 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\14adfeb89efc350fed4c091a1c2a36b9963f8f02c3b0acdab1a057c2491bd08b\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:38:44,789 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.057s at 2026-05-11T13:38:44.789504+00:00
-2026-05-11 07:38:51,084 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:38:51.084073+00:00
-2026-05-11 07:38:53,437 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:38:55,654 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:38:56,151 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:38:57,952 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/fcddc33f-ce6c-4a1a-b8e7-e15271bb8b28 "HTTP/1.1 200 OK"
-2026-05-11 07:38:57,956 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:39:00,194 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:39:02,430 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=fcddc33f-ce6c-4a1a-b8e7-e15271bb8b28 "HTTP/1.1 200 OK"
-2026-05-11 07:39:09,990 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\3f7673441243a20fb8c1c1296c0604d6add78c532f3b43713dc33c6f5b01c01d\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:39:10,290 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.207s at 2026-05-11T13:39:10.290307+00:00
-2026-05-11 07:39:38,492 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:39:38.492111+00:00
-2026-05-11 07:39:40,832 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:39:43,049 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:39:43,532 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:39:45,309 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9089d9d6-6621-45d6-8f79-0cad62b5e02e "HTTP/1.1 200 OK"
-2026-05-11 07:39:45,327 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:39:47,563 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:39:49,790 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9089d9d6-6621-45d6-8f79-0cad62b5e02e "HTTP/1.1 200 OK"
-2026-05-11 07:39:57,349 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\edf2f53c824ca65974f0828fb3ec04b4f927ff2b9e1d15f34452a0c9c692c6c1\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:39:57,388 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.897s at 2026-05-11T13:39:57.388992+00:00
-2026-05-11 07:40:32,684 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:40:32.684097+00:00
-2026-05-11 07:40:34,989 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:40:37,204 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:40:37,643 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:40:39,445 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9309607a-78df-4850-b4ed-d11d8ce128dc "HTTP/1.1 200 OK"
-2026-05-11 07:40:39,479 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:40:41,701 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:40:43,917 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9309607a-78df-4850-b4ed-d11d8ce128dc "HTTP/1.1 200 OK"
-2026-05-11 07:40:51,589 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\93a293fc5f8b3f7ca4a901325b2a8043caa52a8e718eb3f3aaf5e7af683c761e\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:40:51,625 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.941s at 2026-05-11T13:40:51.625392+00:00
-2026-05-11 07:41:13,398 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:41:13.398449+00:00
-2026-05-11 07:41:15,759 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:41:18,011 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:41:18,516 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:41:20,297 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/99b73b62-ad71-4c2b-bd87-9c72f216d0e0 "HTTP/1.1 200 OK"
-2026-05-11 07:41:20,299 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:41:22,508 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:41:24,718 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=99b73b62-ad71-4c2b-bd87-9c72f216d0e0 "HTTP/1.1 200 OK"
-2026-05-11 07:41:32,501 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e939b9878a8afdfede728393e1124bcaf1e59cb72b45f15f0000cf7073ba5417\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:41:32,537 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.139s at 2026-05-11T13:41:32.537339+00:00
-2026-05-11 07:41:59,745 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:41:59.745741+00:00
-2026-05-11 07:42:02,074 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:42:04,321 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:42:04,758 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:42:06,589 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/cba0e5ca-e1fb-4dba-adad-98257d2209d2 "HTTP/1.1 200 OK"
-2026-05-11 07:42:06,591 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:42:08,826 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:42:11,070 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=cba0e5ca-e1fb-4dba-adad-98257d2209d2 "HTTP/1.1 200 OK"
-2026-05-11 07:42:18,732 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7cb0ccfd38250adde7e4e1bbd7e0c134e715b997602e6ae1d49a345e3def99ff\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:42:18,771 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.026s at 2026-05-11T13:42:18.771536+00:00
-2026-05-11 07:42:51,522 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:42:51.522667+00:00
-2026-05-11 07:42:53,886 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:42:56,101 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:42:56,624 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:42:58,399 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:42:58,411 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/6392e3d4-2343-4057-a9f3-4266c304696d "HTTP/1.1 200 OK"
-2026-05-11 07:43:00,667 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:43:02,915 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=6392e3d4-2343-4057-a9f3-4266c304696d "HTTP/1.1 200 OK"
-2026-05-11 07:43:10,561 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\12042b72b3e1b7eb8bc40f86c07a6b00feaa7c6496facdea8517ff6d5906573b\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:43:10,596 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.075s at 2026-05-11T13:43:10.596965+00:00
-2026-05-11 07:43:37,234 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:43:37.234198+00:00
-2026-05-11 07:43:39,565 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:43:41,794 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:43:42,228 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:43:44,077 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:43:44,090 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9faceb92-08d2-469d-bba5-65a235389397 "HTTP/1.1 200 OK"
-2026-05-11 07:43:46,307 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:43:48,512 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9faceb92-08d2-469d-bba5-65a235389397 "HTTP/1.1 200 OK"
-2026-05-11 07:43:56,081 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:43:56,090 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar), trying CPU fallback...
-2026-05-11 07:43:56,692 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 07:43:58,256 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:43:58,334 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7860): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 07:43:58,384 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:43:58,605 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.372s at 2026-05-11T13:43:58.605602+00:00
-2026-05-11 07:43:58,819 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/31d3bf51-d166-46d7-b293-3bed8d7168e2 "HTTP/1.1 200 OK"
-2026-05-11 07:43:58,876 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:44:19,811 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:44:19.811326+00:00
-2026-05-11 07:44:22,182 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:44:24,421 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:44:24,819 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:44:26,702 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:44:26,713 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e0d0c951-cf23-41f4-ae41-1737485e6342 "HTTP/1.1 200 OK"
-2026-05-11 07:44:28,952 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:44:31,175 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e0d0c951-cf23-41f4-ae41-1737485e6342 "HTTP/1.1 200 OK"
-2026-05-11 07:44:38,763 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\0daad28c16c3efda612bf1756d7fa4ca142964f11f7d46b2f28cd63398fcf7f5\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:44:38,807 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.996s at 2026-05-11T13:44:38.807439+00:00
-2026-05-11 07:45:14,328 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:45:14.328987+00:00
-2026-05-11 07:45:16,655 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:45:18,887 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:45:19,378 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:45:21,178 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e9e8492e-0e98-40fc-9b78-5d6a8f089986 "HTTP/1.1 200 OK"
-2026-05-11 07:45:21,180 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:45:23,442 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:45:25,653 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e9e8492e-0e98-40fc-9b78-5d6a8f089986 "HTTP/1.1 200 OK"
-2026-05-11 07:45:33,036 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:45:33,040 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar), trying CPU fallback...
-2026-05-11 07:45:33,595 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 07:45:34,139 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:45:34,205 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7860): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 07:45:34,251 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:45:34,383 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.055s at 2026-05-11T13:45:34.383184+00:00
-2026-05-11 07:45:34,629 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:45:34,706 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/1564da95-6ba7-4dcd-b803-181c06a794ff "HTTP/1.1 200 OK"
-2026-05-11 07:46:33,928 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:46:33.928213+00:00
-2026-05-11 07:46:36,364 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:46:38,648 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:46:39,057 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:46:41,001 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/a00f5788-7a02-4625-a39f-678676469771 "HTTP/1.1 200 OK"
-2026-05-11 07:46:41,003 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:46:43,263 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:46:45,512 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=a00f5788-7a02-4625-a39f-678676469771 "HTTP/1.1 200 OK"
-2026-05-11 07:46:53,902 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\4d35dd1da300e912d4594e91f1dd8e7800f9691a6c461c1feaf24c4f1a84e6b2\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:46:53,937 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.010s at 2026-05-11T13:46:53.937355+00:00
-2026-05-11 07:47:24,918 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:47:24.918247+00:00
-2026-05-11 07:47:27,312 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:47:29,573 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:47:29,998 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:47:31,912 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/357fd497-f65c-4b01-b191-ac1d988235e2 "HTTP/1.1 200 OK"
-2026-05-11 07:47:31,913 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:47:34,171 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:47:36,414 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=357fd497-f65c-4b01-b191-ac1d988235e2 "HTTP/1.1 200 OK"
-2026-05-11 07:47:44,980 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:47:44,989 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar), trying CPU fallback...
-2026-05-11 07:47:45,614 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 07:47:46,162 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:47:46,232 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7860): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 07:47:46,286 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:47:46,442 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.524s at 2026-05-11T13:47:46.442982+00:00
-2026-05-11 07:47:46,714 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:47:46,814 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/1f91b04c-d094-4ee1-a145-a4b4e6ae6f77 "HTTP/1.1 200 OK"
-2026-05-11 07:47:51,353 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:47:51.353332+00:00
-2026-05-11 07:47:53,787 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:47:56,074 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:47:56,491 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:47:58,489 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9041175c-8b0a-4ec9-8f88-9908152bf966 "HTTP/1.1 200 OK"
-2026-05-11 07:47:58,491 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:48:00,774 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:48:03,043 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9041175c-8b0a-4ec9-8f88-9908152bf966 "HTTP/1.1 200 OK"
-2026-05-11 07:48:11,807 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:48:11,811 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar), trying CPU fallback...
-2026-05-11 07:48:12,417 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 07:48:12,978 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:48:13,047 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7860): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 07:48:13,100 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:48:13,255 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.901s at 2026-05-11T13:48:13.255523+00:00
-2026-05-11 07:48:13,470 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:48:13,570 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/86a5d70d-fa66-4e77-b00d-c6aba4296bf8 "HTTP/1.1 200 OK"
-2026-05-11 07:48:30,424 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:48:30.424562+00:00
-2026-05-11 07:48:32,748 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:48:34,991 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:48:35,404 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:48:37,281 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/7619bfd6-9537-43ba-8ffc-2e81c5538505 "HTTP/1.1 200 OK"
-2026-05-11 07:48:37,296 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:48:39,544 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:48:41,758 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=7619bfd6-9537-43ba-8ffc-2e81c5538505 "HTTP/1.1 200 OK"
-2026-05-11 07:48:50,375 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:48:50,379 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar), trying CPU fallback...
-2026-05-11 07:48:50,938 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 07:48:51,496 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:48:51,567 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7860): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    warped = cv2.warpPerspective(
-             ^^^^^^^^^^^^^^^^^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwar
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 07:48:51,612 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:48:51,740 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.315s at 2026-05-11T13:48:51.740122+00:00
-2026-05-11 07:48:52,074 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/a00d1f87-e3ec-4e12-8e9c-2996de163879 "HTTP/1.1 200 OK"
-2026-05-11 07:48:52,074 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:49:23,980 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:49:23.980415+00:00
-2026-05-11 07:49:26,360 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:49:28,599 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:49:29,020 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:49:30,925 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/304091ec-fab3-47d9-96ec-fe167949a362 "HTTP/1.1 200 OK"
-2026-05-11 07:49:30,927 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:49:33,143 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:49:35,383 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=304091ec-fab3-47d9-96ec-fe167949a362 "HTTP/1.1 200 OK"
-2026-05-11 07:49:44,261 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\00613741eaeb077b298a6d4d93d8e4bf259c3ef854e9bcf70f1512004c8aa153\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:49:44,308 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.327s at 2026-05-11T13:49:44.308139+00:00
-2026-05-11 07:50:14,097 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:50:14.097240+00:00
-2026-05-11 07:50:16,435 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:50:18,683 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:50:19,176 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:50:21,006 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:50:21,020 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e9f3e165-c3d5-4f55-aa69-0df03df96edb "HTTP/1.1 200 OK"
-2026-05-11 07:50:23,258 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:50:25,482 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e9f3e165-c3d5-4f55-aa69-0df03df96edb "HTTP/1.1 200 OK"
-2026-05-11 07:50:33,149 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\4b50605c21544baded31f810e531e694fac79169d17d82135ea782303cd12fb4\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:50:33,185 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.088s at 2026-05-11T13:50:33.185866+00:00
-2026-05-11 07:52:34,828 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:52:34.828499+00:00
-2026-05-11 07:52:37,264 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:52:39,566 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:52:40,098 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:52:41,933 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/f4f3cbfa-3f67-4632-81cb-329bb225e919 "HTTP/1.1 200 OK"
-2026-05-11 07:52:41,936 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:52:44,186 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:52:46,470 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=f4f3cbfa-3f67-4632-81cb-329bb225e919 "HTTP/1.1 200 OK"
-2026-05-11 07:52:54,457 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\f28ee25e6084ff886854b49e0a422f18c0c201eb54c115542d6e3da8ae1bff12\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:52:54,460 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    H_use = H
-         ^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwarp.cpp:1603: error: (-215:Assertion faile), trying CPU fallback...
-2026-05-11 07:52:55,149 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 07:52:55,689 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:52:55,759 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (http://localhost:7860): Gradio Space render error: Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\gradio-space\App-que si funciona\app.py", line 346, in render_for_backend
-    result = renderer.render(
-             ^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Generandor de texturas\pipeline\renderer.py", line 114, in render
-    H_use = H
-         ^^^^
-cv2.error: OpenCV(4.13.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\imgwarp.cpp:1603: error: (-215:Assertion faile
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 07:52:55,807 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 07:52:55,946 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.118s at 2026-05-11T13:52:55.946206+00:00
-2026-05-11 07:52:56,178 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:52:56,265 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/9c024d3c-af3e-45de-b8fc-f75c52365214 "HTTP/1.1 200 OK"
-2026-05-11 07:58:14,024 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:58:14.024477+00:00
-2026-05-11 07:58:16,411 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:58:18,656 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:58:19,099 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:58:20,950 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/d6909bc3-d587-4923-b9cc-fea28e2c8d28 "HTTP/1.1 200 OK"
-2026-05-11 07:58:20,952 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:58:23,172 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:58:25,403 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=d6909bc3-d587-4923-b9cc-fea28e2c8d28 "HTTP/1.1 200 OK"
-2026-05-11 07:58:33,857 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\987159a827f379f87e9c995518d269a518dfc37c640f16eff273692570e80f2a\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:58:33,890 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.866s at 2026-05-11T13:58:33.890680+00:00
-2026-05-11 07:58:39,628 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:58:39.628872+00:00
-2026-05-11 07:58:42,010 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:58:44,244 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:58:44,677 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:58:46,514 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/546d7635-9190-4e6a-8700-3eeb733c62ec "HTTP/1.1 200 OK"
-2026-05-11 07:58:46,517 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:58:48,734 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:58:50,947 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=546d7635-9190-4e6a-8700-3eeb733c62ec "HTTP/1.1 200 OK"
-2026-05-11 07:58:58,709 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\1490927a61f8d8b34eec3b75cb02ef5d43f3b033f6d87ef87cfc26e65134ede6\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:58:58,747 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.120s at 2026-05-11T13:58:58.747902+00:00
-2026-05-11 07:59:05,334 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:59:05.334329+00:00
-2026-05-11 07:59:07,668 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:59:09,896 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:59:10,389 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:59:12,207 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:59:12,250 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/cc7231ca-ad09-4302-8f4f-6a5b3e8f7f48 "HTTP/1.1 200 OK"
-2026-05-11 07:59:14,441 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:59:16,674 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=cc7231ca-ad09-4302-8f4f-6a5b3e8f7f48 "HTTP/1.1 200 OK"
-2026-05-11 07:59:24,158 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\dbb87bc0ebe7e1ac10869ea5eaf4e0d0967caea93684547220068a8b63f78b18\image.webp "HTTP/1.1 200 OK"
-2026-05-11 07:59:24,195 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.861s at 2026-05-11T13:59:24.195698+00:00
-2026-05-11 07:59:46,877 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T13:59:46.876668+00:00
-2026-05-11 07:59:49,210 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 07:59:51,442 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 07:59:51,837 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 07:59:53,724 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/2ee1d35a-5d2e-4286-bee5-254903ec06db "HTTP/1.1 200 OK"
-2026-05-11 07:59:53,742 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 07:59:55,977 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 07:59:58,201 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=2ee1d35a-5d2e-4286-bee5-254903ec06db "HTTP/1.1 200 OK"
-2026-05-11 08:00:06,702 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\96c46a348b2065bb96f156676c26da6d1cdd056b209721019eca14fd25aa9084\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:00:06,740 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.864s at 2026-05-11T14:00:06.740786+00:00
-2026-05-11 08:00:34,547 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:00:34.547538+00:00
-2026-05-11 08:00:36,904 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:00:39,110 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:00:39,625 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:00:41,406 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:00:41,419 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/a01577fb-f880-4ee3-981e-3523977c1b8f "HTTP/1.1 200 OK"
-2026-05-11 08:00:43,642 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:00:45,881 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=a01577fb-f880-4ee3-981e-3523977c1b8f "HTTP/1.1 200 OK"
-2026-05-11 08:00:54,201 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\987159a827f379f87e9c995518d269a518dfc37c640f16eff273692570e80f2a\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:00:54,241 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.694s at 2026-05-11T14:00:54.241384+00:00
-2026-05-11 08:01:26,566 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:01:26.566374+00:00
-2026-05-11 08:01:28,909 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:01:31,121 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:01:31,535 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:01:33,408 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/890ae067-0b8f-489c-9092-de4d752fa564 "HTTP/1.1 200 OK"
-2026-05-11 08:01:33,410 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:01:35,686 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:01:37,910 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=890ae067-0b8f-489c-9092-de4d752fa564 "HTTP/1.1 200 OK"
-2026-05-11 08:01:46,590 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\987159a827f379f87e9c995518d269a518dfc37c640f16eff273692570e80f2a\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:01:46,624 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.059s at 2026-05-11T14:01:46.624359+00:00
-2026-05-11 08:05:00,704 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:05:00.704661+00:00
-2026-05-11 08:05:03,047 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:05:05,262 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:05:05,747 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:05:07,565 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/2db5d1bc-826f-4608-a63c-f1cda9a1d15b "HTTP/1.1 200 OK"
-2026-05-11 08:05:07,568 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:05:09,761 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:05:11,989 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=2db5d1bc-826f-4608-a63c-f1cda9a1d15b "HTTP/1.1 200 OK"
-2026-05-11 08:05:20,990 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\4dfeaf8db13e7e9ba4d4b373bcbd933917786b8c7251bc842c08f6d35f84e9b6\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:05:21,025 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.320s at 2026-05-11T14:05:21.025114+00:00
-2026-05-11 08:05:27,461 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 08:05:27,481 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 08:05:28,299 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 08:05:28,319 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 08:05:43,358 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:05:43.358604+00:00
-2026-05-11 08:05:46,015 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:05:48,276 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:05:48,995 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:05:50,631 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/38af6323-4f6a-4a33-9a0d-b5be47122b67 "HTTP/1.1 200 OK"
-2026-05-11 08:05:50,651 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:05:52,883 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:05:55,107 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=38af6323-4f6a-4a33-9a0d-b5be47122b67 "HTTP/1.1 200 OK"
-2026-05-11 08:06:06,052 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\144b6b0df63f1387ed840eceafe5d2b8f7db1b54609abf7d9a9daa6146354b23\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:06:06,092 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.734s at 2026-05-11T14:06:06.092403+00:00
-2026-05-11 08:07:29,154 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:07:29.154213+00:00
-2026-05-11 08:07:31,494 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:07:33,741 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:07:34,288 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:07:36,021 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/78566e56-129d-40a1-a82c-c9cc572a7804 "HTTP/1.1 200 OK"
-2026-05-11 08:07:36,023 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:07:38,257 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:07:40,458 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=78566e56-129d-40a1-a82c-c9cc572a7804 "HTTP/1.1 200 OK"
-2026-05-11 08:07:50,381 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\987159a827f379f87e9c995518d269a518dfc37c640f16eff273692570e80f2a\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:07:50,417 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.263s at 2026-05-11T14:07:50.417306+00:00
-2026-05-11 08:08:10,461 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:08:10.461199+00:00
-2026-05-11 08:08:12,832 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:08:15,036 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:08:15,501 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:08:17,307 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/888913d0-8e69-4520-8597-cbad16ea3cd7 "HTTP/1.1 200 OK"
-2026-05-11 08:08:17,326 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:08:19,538 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:08:21,759 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=888913d0-8e69-4520-8597-cbad16ea3cd7 "HTTP/1.1 200 OK"
-2026-05-11 08:08:32,468 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7e6ff7bf200d28e66c23d75766cb649fc9597f09a8241b45d687be838bfa1085\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:08:32,507 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.047s at 2026-05-11T14:08:32.507337+00:00
-2026-05-11 08:08:54,411 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:08:54.411551+00:00
-2026-05-11 08:08:56,721 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:08:58,939 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:08:59,460 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:09:01,233 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:09:01,245 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/4896be72-16b2-4506-91d4-02a27828afaa "HTTP/1.1 200 OK"
-2026-05-11 08:09:03,498 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:09:05,729 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=4896be72-16b2-4506-91d4-02a27828afaa "HTTP/1.1 200 OK"
-2026-05-11 08:09:14,723 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\af4f3fa044a7204adb2c57ef603ef360e3362f85ed00457b04e34a491ec666e8\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:09:14,762 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.351s at 2026-05-11T14:09:14.762425+00:00
-2026-05-11 08:09:22,534 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:09:22.534016+00:00
-2026-05-11 08:09:24,926 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:09:27,143 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:09:27,537 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:09:29,474 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:09:29,486 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/fdf76cc5-d79f-46f3-b7db-ca3a2caaf6e3 "HTTP/1.1 200 OK"
-2026-05-11 08:09:31,704 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:09:33,945 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=fdf76cc5-d79f-46f3-b7db-ca3a2caaf6e3 "HTTP/1.1 200 OK"
-2026-05-11 08:09:44,576 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\4ae185acfa96321252f6fbee0b0c47d2ec48d2eb2d8c75a32c9484328757be0a\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:09:44,617 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.084s at 2026-05-11T14:09:44.617998+00:00
-2026-05-11 08:23:54,106 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:23:54.106236+00:00
-2026-05-11 08:23:56,479 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:23:58,721 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:23:59,155 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:24:00,999 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/b27941ee-5963-4362-87b3-9d3fb7816292 "HTTP/1.1 200 OK"
-2026-05-11 08:24:01,017 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:24:03,224 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:24:05,462 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=b27941ee-5963-4362-87b3-9d3fb7816292 "HTTP/1.1 200 OK"
-2026-05-11 08:24:14,422 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\8971bd447e4d858b88a21e46216b5cac4da8a62df09b03a0bf9f69414bbfbc3f\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:24:14,459 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.353s at 2026-05-11T14:24:14.459186+00:00
-2026-05-11 08:24:40,154 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:24:40.154067+00:00
-2026-05-11 08:24:42,526 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:24:44,739 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:24:45,274 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:24:47,037 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/8b632d65-db4b-43c5-9d5b-176d77682b4d "HTTP/1.1 200 OK"
-2026-05-11 08:24:47,040 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:24:49,310 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:24:51,551 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=8b632d65-db4b-43c5-9d5b-176d77682b4d "HTTP/1.1 200 OK"
-2026-05-11 08:24:59,555 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\61c0bae5452a847a8eec8000fa86bbc92f38895c21cdff51293077db52049b47\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:24:59,609 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.455s at 2026-05-11T14:24:59.609461+00:00
-2026-05-11 08:25:13,535 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:25:13.535983+00:00
-2026-05-11 08:25:15,895 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:25:18,148 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:25:18,574 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:25:20,421 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/372a9de1-06ff-452e-a7b3-83db429db718 "HTTP/1.1 200 OK"
-2026-05-11 08:25:20,439 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:25:22,688 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:25:24,900 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=372a9de1-06ff-452e-a7b3-83db429db718 "HTTP/1.1 200 OK"
-2026-05-11 08:25:32,277 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\9f26aae03ee10ee70ed27a8dc4c77d335fdbc500fe706220a08fe067ac89b5b6\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:25:32,315 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.780s at 2026-05-11T14:25:32.315471+00:00
-2026-05-11 08:25:58,203 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:25:58.203693+00:00
-2026-05-11 08:26:00,549 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:26:02,797 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:26:03,350 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:26:05,122 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/32903b23-f36f-4d06-9872-5d0c4d5bfcc3 "HTTP/1.1 200 OK"
-2026-05-11 08:26:05,125 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:26:07,340 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:26:09,559 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=32903b23-f36f-4d06-9872-5d0c4d5bfcc3 "HTTP/1.1 200 OK"
-2026-05-11 08:26:17,125 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\bc2165e8db99168984496b0614c2e4d8acc3643d455b108fc45ea30816fdb1dc\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:26:17,174 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.970s at 2026-05-11T14:26:17.174476+00:00
-2026-05-11 08:26:31,042 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:26:31.041862+00:00
-2026-05-11 08:26:33,420 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:26:35,669 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:26:36,113 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:26:37,943 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/35433313-44fe-474d-ac2c-baae2bd6b83c "HTTP/1.1 200 OK"
-2026-05-11 08:26:37,944 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:26:40,182 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:26:42,407 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=35433313-44fe-474d-ac2c-baae2bd6b83c "HTTP/1.1 200 OK"
-2026-05-11 08:26:50,028 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\13d6ad76d05f5ab9405eb3cc735976accdd554831cb3965e518f5807fd200d0f\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:26:50,065 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.023s at 2026-05-11T14:26:50.065448+00:00
-2026-05-11 08:27:11,335 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:27:11.333972+00:00
-2026-05-11 08:27:13,771 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:27:16,029 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:27:16,580 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:27:18,321 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/4211851c-0dc2-4655-b683-f49ec03d8ac9 "HTTP/1.1 200 OK"
-2026-05-11 08:27:18,323 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:27:20,591 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:27:22,812 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=4211851c-0dc2-4655-b683-f49ec03d8ac9 "HTTP/1.1 200 OK"
-2026-05-11 08:27:30,852 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\d8411de62edcb305f56a0419285ff045890bac7da16c9e9ede06c82d82745b0a\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:27:30,893 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.558s at 2026-05-11T14:27:30.893186+00:00
-2026-05-11 08:27:51,862 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:27:51.862857+00:00
-2026-05-11 08:27:54,224 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:27:56,451 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:27:56,857 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:27:58,745 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/527a694d-cb75-4325-87f2-650065362349 "HTTP/1.1 200 OK"
-2026-05-11 08:27:58,765 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:28:00,999 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:28:03,231 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=527a694d-cb75-4325-87f2-650065362349 "HTTP/1.1 200 OK"
-2026-05-11 08:28:10,922 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\dcff331be98568e3944f8891d2773167cc5ba35c0d80ebb3f7ccadd3ae7143b8\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:28:10,979 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.116s at 2026-05-11T14:28:10.979094+00:00
-2026-05-11 08:28:36,570 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:28:36.570999+00:00
-2026-05-11 08:28:38,940 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:28:41,158 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:28:41,673 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:28:43,459 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:28:43,473 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/6665df09-7e20-4692-8e06-b25a226b02e9 "HTTP/1.1 200 OK"
-2026-05-11 08:28:45,725 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:28:47,971 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=6665df09-7e20-4692-8e06-b25a226b02e9 "HTTP/1.1 200 OK"
-2026-05-11 08:28:55,196 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7e652a6d342a1acbbe68f5f4d23dd489bfe3a29e4600388234c84c71e17656f4\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:28:55,230 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.660s at 2026-05-11T14:28:55.230723+00:00
-2026-05-11 08:29:09,384 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:29:09.384232+00:00
-2026-05-11 08:29:11,748 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:29:13,956 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:29:14,366 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:29:16,238 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/1905794c-e373-4ead-a0d2-fc465a2f1e19 "HTTP/1.1 200 OK"
-2026-05-11 08:29:16,240 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:29:18,523 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:29:20,797 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=1905794c-e373-4ead-a0d2-fc465a2f1e19 "HTTP/1.1 200 OK"
-2026-05-11 08:29:28,204 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7e652a6d342a1acbbe68f5f4d23dd489bfe3a29e4600388234c84c71e17656f4\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:29:28,241 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.857s at 2026-05-11T14:29:28.241322+00:00
-2026-05-11 08:30:13,740 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:30:13.740739+00:00
-2026-05-11 08:30:16,122 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:30:18,329 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:30:18,779 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:30:20,610 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e5d6c046-75e4-4939-9e10-3726e7fd8618 "HTTP/1.1 200 OK"
-2026-05-11 08:30:20,626 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:30:22,858 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:30:25,099 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e5d6c046-75e4-4939-9e10-3726e7fd8618 "HTTP/1.1 200 OK"
-2026-05-11 08:30:33,721 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\83154e5b8e9edada63e73252bbc18818c0fe81e59aa4d5d99ade57189f3f6ecb\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:30:33,759 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.019s at 2026-05-11T14:30:33.759490+00:00
-2026-05-11 08:31:45,375 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:31:45.375338+00:00
-2026-05-11 08:31:47,767 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:31:49,996 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:31:50,484 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:31:52,277 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:31:52,291 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e8b5cc64-7b14-408c-b7a4-9a0e737fafbb "HTTP/1.1 200 OK"
-2026-05-11 08:31:54,499 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:31:56,704 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e8b5cc64-7b14-408c-b7a4-9a0e737fafbb "HTTP/1.1 200 OK"
-2026-05-11 08:32:04,546 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7e652a6d342a1acbbe68f5f4d23dd489bfe3a29e4600388234c84c71e17656f4\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:32:04,583 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.208s at 2026-05-11T14:32:04.583431+00:00
-2026-05-11 08:36:55,499 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:36:55.499185+00:00
-2026-05-11 08:36:57,817 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:37:00,047 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:37:00,610 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:37:02,336 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/1ee9b9f4-3788-440b-8a09-56d6d45b1ebb "HTTP/1.1 200 OK"
-2026-05-11 08:37:02,370 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:37:04,704 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:37:06,917 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=1ee9b9f4-3788-440b-8a09-56d6d45b1ebb "HTTP/1.1 200 OK"
-2026-05-11 08:37:14,472 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7e652a6d342a1acbbe68f5f4d23dd489bfe3a29e4600388234c84c71e17656f4\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:37:14,506 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.007s at 2026-05-11T14:37:14.506589+00:00
-2026-05-11 08:37:47,793 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:37:47.793918+00:00
-2026-05-11 08:37:50,139 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:37:52,351 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:37:52,777 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:37:54,618 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/1623e3e9-f0e5-421b-a669-9a00ed197b79 "HTTP/1.1 200 OK"
-2026-05-11 08:37:54,636 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:37:56,882 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:37:59,130 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=1623e3e9-f0e5-421b-a669-9a00ed197b79 "HTTP/1.1 200 OK"
-2026-05-11 08:38:06,584 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\dcff331be98568e3944f8891d2773167cc5ba35c0d80ebb3f7ccadd3ae7143b8\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:38:06,614 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.821s at 2026-05-11T14:38:06.614925+00:00
-2026-05-11 08:38:31,451 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:38:31.451279+00:00
-2026-05-11 08:38:33,782 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:38:36,013 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:38:36,647 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:38:38,335 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/34d35216-1db5-4a22-9acb-3a67e6aa0d17 "HTTP/1.1 200 OK"
-2026-05-11 08:38:38,337 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:38:40,583 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:38:42,800 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=34d35216-1db5-4a22-9acb-3a67e6aa0d17 "HTTP/1.1 200 OK"
-2026-05-11 08:38:50,479 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\dcff331be98568e3944f8891d2773167cc5ba35c0d80ebb3f7ccadd3ae7143b8\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:38:50,514 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.064s at 2026-05-11T14:38:50.514463+00:00
-2026-05-11 08:39:30,751 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:39:30.751474+00:00
-2026-05-11 08:39:33,103 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:39:35,346 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:39:35,794 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:39:37,684 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/6f204c23-4dad-44b5-89c8-e786b0b6a7ee "HTTP/1.1 200 OK"
-2026-05-11 08:39:37,702 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:39:39,947 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:39:42,157 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=6f204c23-4dad-44b5-89c8-e786b0b6a7ee "HTTP/1.1 200 OK"
-2026-05-11 08:39:50,741 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\dcff331be98568e3944f8891d2773167cc5ba35c0d80ebb3f7ccadd3ae7143b8\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:39:50,777 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.026s at 2026-05-11T14:39:50.777556+00:00
-2026-05-11 08:40:14,350 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:40:14.350006+00:00
-2026-05-11 08:40:16,661 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:40:18,880 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:40:19,481 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:40:21,222 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:40:21,234 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/7246b853-d6c2-49c5-9647-4ed0ab6849cb "HTTP/1.1 200 OK"
-2026-05-11 08:40:23,494 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:40:25,725 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=7246b853-d6c2-49c5-9647-4ed0ab6849cb "HTTP/1.1 200 OK"
-2026-05-11 08:40:33,271 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\1dcd45ddeba2ebff9bd449c7a8338f6e454b7692f87377fe41d578071fb2bdaf\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:40:33,329 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.980s at 2026-05-11T14:40:33.329328+00:00
-2026-05-11 08:40:43,390 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:40:43.390829+00:00
-2026-05-11 08:40:45,711 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:40:47,924 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:40:48,359 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:40:50,199 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/4271eef2-7dfd-4511-be21-26af887b01d4 "HTTP/1.1 200 OK"
-2026-05-11 08:40:50,202 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:40:52,424 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:40:54,620 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=4271eef2-7dfd-4511-be21-26af887b01d4 "HTTP/1.1 200 OK"
-2026-05-11 08:41:02,503 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\5cd5e002d8fff69167b7957e92368cb8e97468efaa3bdd4c6e860e7819dcaac9\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:41:02,539 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.148s at 2026-05-11T14:41:02.539391+00:00
-2026-05-11 08:41:34,387 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:41:34.387746+00:00
-2026-05-11 08:41:37,636 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:41:39,853 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:41:40,352 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:41:42,141 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/c3a6cd96-4566-4c39-932b-14ac11dc7a35 "HTTP/1.1 200 OK"
-2026-05-11 08:41:42,143 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:41:44,426 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:41:46,641 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=c3a6cd96-4566-4c39-932b-14ac11dc7a35 "HTTP/1.1 200 OK"
-2026-05-11 08:41:54,021 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\2d2f2f38366272d46f09704fba6cb8174362aa3b5b6cbba1e41367673524af8f\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:41:54,053 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.666s at 2026-05-11T14:41:54.053833+00:00
-2026-05-11 08:42:14,063 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:42:14.063192+00:00
-2026-05-11 08:42:17,270 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:42:19,473 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:42:19,909 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:42:21,750 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/fc9e49b4-003c-41a0-ae9c-b1ee6ea478d8 "HTTP/1.1 200 OK"
-2026-05-11 08:42:21,769 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:42:24,018 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:42:26,271 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=fc9e49b4-003c-41a0-ae9c-b1ee6ea478d8 "HTTP/1.1 200 OK"
-2026-05-11 08:42:33,865 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\79ee19af39aca7f0770059713359c1222bef67ba2dfa40219dc5ed09bc6a1bbf\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:42:33,899 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.835s at 2026-05-11T14:42:33.899026+00:00
-2026-05-11 08:42:55,777 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:42:55.777571+00:00
-2026-05-11 08:42:59,934 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:43:02,165 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:43:02,667 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:43:04,456 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/c5d546a8-fd90-4335-bcc4-721cd1ade7d7 "HTTP/1.1 200 OK"
-2026-05-11 08:43:04,457 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:43:06,765 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:43:08,990 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=c5d546a8-fd90-4335-bcc4-721cd1ade7d7 "HTTP/1.1 200 OK"
-2026-05-11 08:43:17,157 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\2f4d6d785e964920a977ba3b7450fd8272b489b92b55b4c53bfa0530117ba48d\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:43:17,194 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.417s at 2026-05-11T14:43:17.194197+00:00
-2026-05-11 08:43:32,204 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:43:32.204958+00:00
-2026-05-11 08:43:36,317 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:43:38,560 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:43:38,993 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:43:40,830 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:43:40,874 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9c477ff2-4fe2-49b0-a082-680fb13eaa2f "HTTP/1.1 200 OK"
-2026-05-11 08:43:43,189 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:43:45,428 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9c477ff2-4fe2-49b0-a082-680fb13eaa2f "HTTP/1.1 200 OK"
-2026-05-11 08:43:53,271 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\2f4d6d785e964920a977ba3b7450fd8272b489b92b55b4c53bfa0530117ba48d\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:43:53,308 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.104s at 2026-05-11T14:43:53.308454+00:00
-2026-05-11 08:44:02,706 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:44:02.706352+00:00
-2026-05-11 08:44:06,505 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:44:08,730 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:44:09,239 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:44:10,993 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/80f646be-2f3c-49fc-8960-5d4ccdc14d16 "HTTP/1.1 200 OK"
-2026-05-11 08:44:10,995 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:44:13,322 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:44:15,541 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=80f646be-2f3c-49fc-8960-5d4ccdc14d16 "HTTP/1.1 200 OK"
-2026-05-11 08:44:23,169 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\8898e235f41c3cd8f4a1c7945b36700a650cd05fd3638c36fc6f121eb57ef1c1\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:44:23,199 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.493s at 2026-05-11T14:44:23.199524+00:00
-2026-05-11 08:44:33,949 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:44:33.949552+00:00
-2026-05-11 08:44:37,648 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:44:39,892 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:44:40,338 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:44:42,176 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:44:42,189 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/1f820435-9611-4a1c-9379-5285d215750e "HTTP/1.1 200 OK"
-2026-05-11 08:44:44,484 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:44:46,717 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=1f820435-9611-4a1c-9379-5285d215750e "HTTP/1.1 200 OK"
-2026-05-11 08:44:54,137 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\1a4569321d5e6d439a93f05d4ca2972301cb8078dd1216659fa38c87da091446\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:44:54,167 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.217s at 2026-05-11T14:44:54.167079+00:00
-2026-05-11 08:45:22,200 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:45:22.200930+00:00
-2026-05-11 08:45:24,547 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:45:26,775 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:45:28,298 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:45:29,087 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:45:29,100 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/149a4d14-b4ab-4b7b-aa79-bbba3d15aaf9 "HTTP/1.1 200 OK"
-2026-05-11 08:45:31,372 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:45:33,608 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=149a4d14-b4ab-4b7b-aa79-bbba3d15aaf9 "HTTP/1.1 200 OK"
-2026-05-11 08:45:41,573 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\081aa45b7d139bf0925e3aef23b1bdb109de5d3ca4c1b7f0dfd21959b6002d38\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:45:41,621 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.421s at 2026-05-11T14:45:41.621940+00:00
-2026-05-11 08:46:03,424 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:46:03.424997+00:00
-2026-05-11 08:46:05,770 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:46:08,045 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:46:08,450 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:46:10,422 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/b4d726ca-cfbc-4833-aba1-0e79f08db999 "HTTP/1.1 200 OK"
-2026-05-11 08:46:10,424 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:46:12,685 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:46:14,942 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=b4d726ca-cfbc-4833-aba1-0e79f08db999 "HTTP/1.1 200 OK"
-2026-05-11 08:46:22,847 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\081aa45b7d139bf0925e3aef23b1bdb109de5d3ca4c1b7f0dfd21959b6002d38\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:46:22,882 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.458s at 2026-05-11T14:46:22.882967+00:00
-2026-05-11 08:50:47,465 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:50:47.465466+00:00
-2026-05-11 08:50:49,827 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:50:52,047 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:50:52,561 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:50:54,370 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:50:54,384 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/a239d19f-01e6-47df-b239-4d967ade84f2 "HTTP/1.1 200 OK"
-2026-05-11 08:50:56,627 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:50:58,849 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=a239d19f-01e6-47df-b239-4d967ade84f2 "HTTP/1.1 200 OK"
-2026-05-11 08:51:06,774 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\5486932d4813c760e4bd4a21404adf59b93a077c9f5009a3111680cb12dfb668\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:51:06,805 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.340s at 2026-05-11T14:51:06.805516+00:00
-2026-05-11 08:51:18,641 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:51:18.641886+00:00
-2026-05-11 08:51:21,018 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:51:23,241 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:51:23,656 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:51:25,496 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:51:25,509 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/f5edb8a3-3489-43ed-83e7-d57a70c15206 "HTTP/1.1 200 OK"
-2026-05-11 08:51:27,726 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:51:29,974 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=f5edb8a3-3489-43ed-83e7-d57a70c15206 "HTTP/1.1 200 OK"
-2026-05-11 08:51:37,230 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\43d6c985beaa52aa9f547d5cad18c47ac5ad1aad074537262134fb3ee33f6f30\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:51:37,265 INFO backend.segmentation: [APPLY_TEXTURE] DONE 18.624s at 2026-05-11T14:51:37.265824+00:00
-2026-05-11 08:51:49,441 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T14:51:49.441371+00:00
-2026-05-11 08:51:51,748 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 08:51:53,992 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 08:51:54,494 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 08:51:56,313 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/7bb87fda-5972-465a-9c5b-ff8cbe9f8658 "HTTP/1.1 200 OK"
-2026-05-11 08:51:56,316 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 08:51:58,542 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 08:52:00,803 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=7bb87fda-5972-465a-9c5b-ff8cbe9f8658 "HTTP/1.1 200 OK"
-2026-05-11 08:52:09,282 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\16c245147932b16e84272f485aa1e64a205303e1669fe3192f4040c5211bfe65\image.webp "HTTP/1.1 200 OK"
-2026-05-11 08:52:09,330 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.889s at 2026-05-11T14:52:09.330236+00:00
-2026-05-11 08:53:23,170 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a01ed63ac1ef105a6100284, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a01ed63ac1ef105a6100284"}, "remainingTimeMS": 30}
-2026-05-11 08:59:34,053 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-11 08:59:34,078 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 08:59:56,934 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a01eeec350249fbce1c5550, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a01eeec350249fbce1c5550"}, "remainingTimeMS": 30}
-2026-05-11 09:00:03,790 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T15:00:03.790265+00:00
-2026-05-11 09:00:03,790 INFO backend.segmentation: [JOB 3f36b79482d04fdba69fa180e8d82b55] preparing_image progress=12
-2026-05-11 09:00:03,941 INFO backend.segmentation: [JOB 3f36b79482d04fdba69fa180e8d82b55] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 09:00:03,941 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
-2026-05-11 09:00:06,608 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 09:00:07,171 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:00:07,919 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/ac77bcfc-7232-4a63-8604-25d45c813fcc "HTTP/1.1 200 OK"
-2026-05-11 09:00:08,152 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:00:08,179 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:00:08,707 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:00:09,377 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=ac77bcfc-7232-4a63-8604-25d45c813fcc "HTTP/1.1 200 OK"
-2026-05-11 09:00:28,367 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/b1c58c6503edaf5fcdc01526aef97fe3d82c533e6dd5a577bdcf26f56d685366/image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:00:28,505 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=61
-2026-05-11 09:00:28,507 INFO backend.segmentation: [JOB 3f36b79482d04fdba69fa180e8d82b55] saving_masks progress=92
-2026-05-11 09:00:28,643 INFO backend.segmentation: [JOB 3f36b79482d04fdba69fa180e8d82b55] segments_meta saved (61 segments)
-2026-05-11 09:00:28,643 INFO backend.segmentation: [JOB 3f36b79482d04fdba69fa180e8d82b55] done mask_count=61
-2026-05-11 09:00:28,643 INFO backend.segmentation: [UPLOAD_BG] DONE 24.854s at 2026-05-11T15:00:28.643926+00:00
-2026-05-11 09:00:28,643 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 09:00:30,184 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a01ef0e350249fbce1c5551, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a01ef0e350249fbce1c5551"}, "remainingTimeMS": 30}
-2026-05-11 09:00:38,461 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:00:38.461550+00:00
-2026-05-11 09:00:41,507 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 09:00:42,158 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:00:42,658 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:00:42,805 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/f0a07ce3-8ce5-479c-8a9b-581234198f5c "HTTP/1.1 200 OK"
-2026-05-11 09:00:42,967 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:01:03,284 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:01:03,918 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=f0a07ce3-8ce5-479c-8a9b-581234198f5c "HTTP/1.1 200 OK"
-2026-05-11 09:01:04,561 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/23314345710bf7dd21e8b07d1fa654a32440adfbed83aaf2feef6dab22f1a1ca/image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:01:04,701 WARNING services.gradio_client_service: GPU Space render failed (Gradio Space render error: import_failed), trying CPU fallback...
-2026-05-11 09:01:05,471 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 09:01:06,197 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:01:06,263 WARNING backend.segmentation: Remote render via Gradio failed, falling back to local: Both Gradio Spaces render failed.
-  GPU (https://eduardo4547-hyper-reality-sam2-gpu.hf.space): Gradio Space render error: import_failed
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Cannot find a function with `api_name`: /render.
-2026-05-11 09:01:06,697 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:01:06,790 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\hyper-reality-1778254222964.jpg
-2026-05-11 09:01:06,889 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/7549c987-8bbe-4e41-8da5-e08804270246 "HTTP/1.1 200 OK"
-2026-05-11 09:01:07,106 INFO backend.segmentation: [APPLY_TEXTURE] DONE 28.645s at 2026-05-11T15:01:07.106365+00:00
-2026-05-11 09:02:27,357 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 09:02:27,381 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 09:02:55,966 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:02:55.966358+00:00
-2026-05-11 09:02:58,857 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:03:01,243 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:03:02,224 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:03:03,744 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/65b7a704-e4c5-4883-a51e-20f4487db3f8 "HTTP/1.1 200 OK"
-2026-05-11 09:03:03,778 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:03:06,155 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:03:08,583 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=65b7a704-e4c5-4883-a51e-20f4487db3f8 "HTTP/1.1 200 OK"
-2026-05-11 09:03:18,771 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\dee0b06b7f3205e519abee75a0fd781fbc1d05fe893f21dc1d9562e0934ee509\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:03:18,848 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.883s at 2026-05-11T15:03:18.848958+00:00
-2026-05-11 09:04:16,293 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:04:16.293028+00:00
-2026-05-11 09:04:18,844 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:04:21,221 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:04:21,710 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:04:23,638 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:04:23,649 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/76dab94b-b9d8-44a8-b036-03e15f1fe2bd "HTTP/1.1 200 OK"
-2026-05-11 09:04:25,990 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:04:28,339 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=76dab94b-b9d8-44a8-b036-03e15f1fe2bd "HTTP/1.1 200 OK"
-2026-05-11 09:04:43,718 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\29aec395f88d98858911bde6acc6466dbf45da9fc592b83acb5a57d64ec466c4\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:04:43,757 INFO backend.segmentation: [APPLY_TEXTURE] DONE 27.465s at 2026-05-11T15:04:43.757815+00:00
-2026-05-11 09:05:26,410 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:05:26.410908+00:00
-2026-05-11 09:05:28,958 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:05:31,343 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:05:31,834 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:05:33,794 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:05:33,805 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/5d38c3f7-4809-4b8a-b019-e5e4282ccf57 "HTTP/1.1 200 OK"
-2026-05-11 09:05:36,147 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:05:38,539 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=5d38c3f7-4809-4b8a-b019-e5e4282ccf57 "HTTP/1.1 200 OK"
-2026-05-11 09:05:47,129 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\1eb839c12f77649f31745595b80bfae381ebbfe625276d80619558c27fc4100c\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:05:47,169 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.759s at 2026-05-11T15:05:47.169527+00:00
-2026-05-11 09:07:00,832 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:07:00.832585+00:00
-2026-05-11 09:07:03,220 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:07:05,487 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:07:05,958 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:07:07,823 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/d9226b2c-d5c9-4753-831e-11b179671135 "HTTP/1.1 200 OK"
-2026-05-11 09:07:07,825 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:07:10,066 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:07:12,331 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=d9226b2c-d5c9-4753-831e-11b179671135 "HTTP/1.1 200 OK"
-2026-05-11 09:07:21,277 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\0c7b3464bcf12e33aeec3d97d77559a8c2e926abb18ebf01ce372c31ed7c3bd1\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:07:21,316 INFO backend.segmentation: [APPLY_TEXTURE] DONE 20.485s at 2026-05-11T15:07:21.316788+00:00
-2026-05-11 09:07:39,324 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a01f0bbb29f424d7c4dde31, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a01f0bbb29f424d7c4dde31"}, "remainingTimeMS": 30}
-2026-05-11 09:07:56,182 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T15:07:56.182552+00:00
-2026-05-11 09:07:56,182 INFO backend.segmentation: [JOB b454dca58f474e8aaed0a05b80f7f04c] preparing_image progress=12
-2026-05-11 09:07:56,226 INFO backend.segmentation: [JOB b454dca58f474e8aaed0a05b80f7f04c] segmenting_with_sam2 progress=30 estimated_seconds=94.01599999999999
-2026-05-11 09:07:56,227 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 09:07:58,573 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:08:00,842 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:08:01,274 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:08:03,206 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/7763e966-1bc8-4a49-87f8-9d780f488054 "HTTP/1.1 200 OK"
-2026-05-11 09:08:03,210 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:08:05,435 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:08:07,659 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=7763e966-1bc8-4a49-87f8-9d780f488054 "HTTP/1.1 200 OK"
-2026-05-11 09:10:17,025 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\56758f540e1c547de434b369fae158810fde033fe3650199c54eecf9fd68ac46\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:10:17,041 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=58
-2026-05-11 09:10:17,043 INFO backend.segmentation: [JOB b454dca58f474e8aaed0a05b80f7f04c] saving_masks progress=92
-2026-05-11 09:10:17,288 INFO backend.segmentation: [JOB b454dca58f474e8aaed0a05b80f7f04c] segments_meta saved (58 segments)
-2026-05-11 09:10:17,288 INFO backend.segmentation: [JOB b454dca58f474e8aaed0a05b80f7f04c] done mask_count=58
-2026-05-11 09:10:17,288 INFO backend.segmentation: [UPLOAD_BG] DONE 141.106s at 2026-05-11T15:10:17.288427+00:00
-2026-05-11 09:10:17,288 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 09:10:20,270 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a01f15cb29f424d7c4dde32, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a01f15cb29f424d7c4dde32"}, "remainingTimeMS": 30}
-2026-05-11 09:10:34,161 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:10:34.161901+00:00
-2026-05-11 09:10:38,153 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:10:40,400 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:10:40,914 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:10:42,826 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/5de7167f-1177-4093-ab8e-02c57efd6725 "HTTP/1.1 200 OK"
-2026-05-11 09:10:42,829 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:10:45,122 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:10:47,370 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=5de7167f-1177-4093-ab8e-02c57efd6725 "HTTP/1.1 200 OK"
-2026-05-11 09:10:55,340 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\08d0c8382b41a8cb1afd5ca2933402871534ace900c8c25dbc04dfb0c7fac838\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:10:55,382 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.221s at 2026-05-11T15:10:55.382977+00:00
-2026-05-11 09:11:14,068 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:11:14.068589+00:00
-2026-05-11 09:11:18,054 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:11:20,338 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:11:20,755 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:11:22,681 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/aa5ffe1e-cf6f-4a59-8b5d-9f8f844ccf35 "HTTP/1.1 200 OK"
-2026-05-11 09:11:22,685 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:11:25,069 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:11:27,403 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=aa5ffe1e-cf6f-4a59-8b5d-9f8f844ccf35 "HTTP/1.1 200 OK"
-2026-05-11 09:11:37,029 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\0d515bdb32e656b506e326f168d5fb2ca05cba9bc53cb511e42dd260d62301f7\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:11:37,090 INFO backend.segmentation: [APPLY_TEXTURE] DONE 23.022s at 2026-05-11T15:11:37.090970+00:00
-2026-05-11 09:11:49,760 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:11:49.760016+00:00
-2026-05-11 09:11:53,744 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:11:56,074 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:11:56,569 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:11:58,419 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/859f6de7-07f6-480e-9492-6d73356bbf4c "HTTP/1.1 200 OK"
-2026-05-11 09:11:58,437 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:12:00,755 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:12:03,037 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=859f6de7-07f6-480e-9492-6d73356bbf4c "HTTP/1.1 200 OK"
-2026-05-11 09:12:11,490 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\b849e3480a5febb83d4fb8ebb52ed500f40df99c6d5f8a20108eed00ab315153\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:12:11,536 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.777s at 2026-05-11T15:12:11.536831+00:00
-2026-05-11 09:12:37,043 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:12:37.042144+00:00
-2026-05-11 09:12:41,791 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:12:44,105 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:12:44,550 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:12:46,524 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/3deaf637-5ada-4a54-b02b-6b588dec87a5 "HTTP/1.1 200 OK"
-2026-05-11 09:12:46,572 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:12:48,966 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:12:51,228 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=3deaf637-5ada-4a54-b02b-6b588dec87a5 "HTTP/1.1 200 OK"
-2026-05-11 09:13:00,100 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\25d12f1c2a9c336c1b887ee7e0398b601b42b7565509d9dfaf16f582b2ca907a\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:13:00,146 INFO backend.segmentation: [APPLY_TEXTURE] DONE 23.104s at 2026-05-11T15:13:00.146803+00:00
-2026-05-11 09:13:10,087 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:13:10.087403+00:00
-2026-05-11 09:13:14,037 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:13:16,298 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:13:16,857 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:13:18,704 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/f345958a-a52f-4849-b880-ca96676d7386 "HTTP/1.1 200 OK"
-2026-05-11 09:13:18,707 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:13:21,027 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:13:23,316 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=f345958a-a52f-4849-b880-ca96676d7386 "HTTP/1.1 200 OK"
-2026-05-11 09:13:33,722 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\08d0c8382b41a8cb1afd5ca2933402871534ace900c8c25dbc04dfb0c7fac838\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:13:33,775 INFO backend.segmentation: [APPLY_TEXTURE] DONE 23.688s at 2026-05-11T15:13:33.775460+00:00
-2026-05-11 09:14:26,391 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:14:26.391654+00:00
-2026-05-11 09:14:30,328 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:14:32,580 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:14:33,093 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:14:34,893 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/71de3a6c-9c39-4178-83cd-abe0743e32ba "HTTP/1.1 200 OK"
-2026-05-11 09:14:34,911 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:14:37,273 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:14:39,540 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=71de3a6c-9c39-4178-83cd-abe0743e32ba "HTTP/1.1 200 OK"
-2026-05-11 09:14:47,492 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\29b96e9889e909ab544c7e84938cfd34a01f8b5169111b550e573aa6b0b57b67\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:14:47,538 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.146s at 2026-05-11T15:14:47.538602+00:00
-2026-05-11 09:15:04,802 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:15:04.802101+00:00
-2026-05-11 09:15:09,381 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:15:11,700 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:15:12,871 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:15:14,058 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:15:14,069 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/94003c7a-84a3-4b8f-a66a-5460381f8d8b "HTTP/1.1 200 OK"
-2026-05-11 09:15:16,401 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:15:18,674 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=94003c7a-84a3-4b8f-a66a-5460381f8d8b "HTTP/1.1 200 OK"
-2026-05-11 09:15:30,091 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\ccbd80baf8b8064609e97da4a8f97ee6947813f3ee88f8e9057e58426278046d\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:15:30,167 INFO backend.segmentation: [APPLY_TEXTURE] DONE 25.366s at 2026-05-11T15:15:30.167665+00:00
-2026-05-11 09:15:54,665 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T15:15:54.665708+00:00
-2026-05-11 09:15:54,666 INFO backend.segmentation: [JOB 14bc0a9c8c784733b22bee657e4a131f] preparing_image progress=12
-2026-05-11 09:15:55,008 INFO backend.segmentation: [JOB 14bc0a9c8c784733b22bee657e4a131f] segmenting_with_sam2 progress=30 estimated_seconds=105.8432
-2026-05-11 09:15:55,008 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 09:15:57,374 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:15:59,723 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:16:00,285 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:16:02,177 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9897633b-f106-45fb-b9a4-78e34f8ccf0f "HTTP/1.1 200 OK"
-2026-05-11 09:16:02,181 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:16:04,558 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:16:07,298 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9897633b-f106-45fb-b9a4-78e34f8ccf0f "HTTP/1.1 200 OK"
-2026-05-11 09:18:04,401 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\fe7e296f49e3953b396fc8aeb7f4885b83ba4201a8d3f8d451ff0339d7391c52\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:18:04,415 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=74
-2026-05-11 09:18:04,415 INFO backend.segmentation: [JOB 14bc0a9c8c784733b22bee657e4a131f] saving_masks progress=92
-2026-05-11 09:18:04,694 INFO backend.segmentation: [JOB 14bc0a9c8c784733b22bee657e4a131f] segments_meta saved (74 segments)
-2026-05-11 09:18:04,694 INFO backend.segmentation: [JOB 14bc0a9c8c784733b22bee657e4a131f] done mask_count=74
-2026-05-11 09:18:04,694 INFO backend.segmentation: [UPLOAD_BG] DONE 130.029s at 2026-05-11T15:18:04.694806+00:00
-2026-05-11 09:18:04,694 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 09:18:14,220 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:18:14.220091+00:00
-2026-05-11 09:18:18,813 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:18:21,048 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:18:21,523 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:18:23,424 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/772ed342-ed42-4191-8bab-4d187a9eedab "HTTP/1.1 200 OK"
-2026-05-11 09:18:23,426 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:18:25,820 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:18:28,063 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=772ed342-ed42-4191-8bab-4d187a9eedab "HTTP/1.1 200 OK"
-2026-05-11 09:18:36,513 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\0bf73bbc2dfb1dfdbce2bd6f148711a867920edab77a04c28005b7b51bec563e\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:18:36,580 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.361s at 2026-05-11T15:18:36.580363+00:00
-2026-05-11 09:18:51,861 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:18:51.861615+00:00
-2026-05-11 09:18:56,659 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:18:58,950 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:18:59,388 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:19:01,288 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:19:01,301 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/02aba9f9-2d22-411e-ada8-d1649e5bf879 "HTTP/1.1 200 OK"
-2026-05-11 09:19:03,716 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:19:05,979 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=02aba9f9-2d22-411e-ada8-d1649e5bf879 "HTTP/1.1 200 OK"
-2026-05-11 09:19:15,134 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\6b114b0f1869c839104ad71d04efe8b1c42c2ada6548a24dd01c0f1195554552\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:19:15,204 INFO backend.segmentation: [APPLY_TEXTURE] DONE 23.342s at 2026-05-11T15:19:15.204045+00:00
-2026-05-11 09:19:25,506 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T15:19:25.506664+00:00
-2026-05-11 09:19:25,506 INFO backend.segmentation: [JOB 306b039e65b146b69dd8b75ba05c88b9] preparing_image progress=12
-2026-05-11 09:19:25,535 INFO backend.segmentation: [JOB 306b039e65b146b69dd8b75ba05c88b9] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 09:19:25,536 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 09:19:27,881 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:19:30,133 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:19:30,690 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:19:32,418 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/8b3cfccf-fbce-49ba-9886-7e60d3a4f9e5 "HTTP/1.1 200 OK"
-2026-05-11 09:19:32,420 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:19:34,631 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:19:36,913 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=8b3cfccf-fbce-49ba-9886-7e60d3a4f9e5 "HTTP/1.1 200 OK"
-2026-05-11 09:21:11,357 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\fdba6c817445c957bf57f0f37d255298685625d2847381414fb08306405b69d3\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:21:11,374 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=61
-2026-05-11 09:21:11,374 INFO backend.segmentation: [JOB 306b039e65b146b69dd8b75ba05c88b9] saving_masks progress=92
-2026-05-11 09:21:11,543 INFO backend.segmentation: [JOB 306b039e65b146b69dd8b75ba05c88b9] segments_meta saved (61 segments)
-2026-05-11 09:21:11,545 INFO backend.segmentation: [JOB 306b039e65b146b69dd8b75ba05c88b9] done mask_count=61
-2026-05-11 09:21:11,545 INFO backend.segmentation: [UPLOAD_BG] DONE 106.039s at 2026-05-11T15:21:11.545131+00:00
-2026-05-11 09:21:11,545 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 09:21:23,322 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:21:23.322567+00:00
-2026-05-11 09:21:29,196 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:21:31,524 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:21:32,195 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:21:33,987 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:21:34,012 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/39c2dd92-8c58-4707-8071-1e597e73530f "HTTP/1.1 200 OK"
-2026-05-11 09:21:36,542 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:21:38,902 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=39c2dd92-8c58-4707-8071-1e597e73530f "HTTP/1.1 200 OK"
-2026-05-11 09:21:55,622 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\0e52d54170d30b6d09308ddfb46b306d2afc5dfc6e4026ae5f907d07f6ed6436\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:21:55,666 INFO backend.segmentation: [APPLY_TEXTURE] DONE 32.343s at 2026-05-11T15:21:55.666246+00:00
-2026-05-11 09:22:14,587 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:22:14.587711+00:00
-2026-05-11 09:22:19,127 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:22:21,368 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:22:21,771 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:22:23,686 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/40e6db7c-cb8a-4621-8be5-28c640b19c75 "HTTP/1.1 200 OK"
-2026-05-11 09:22:23,705 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:22:26,139 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:22:28,393 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=40e6db7c-cb8a-4621-8be5-28c640b19c75 "HTTP/1.1 200 OK"
-2026-05-11 09:22:37,108 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\61825b19b734baf326a7a6a6d9a5f9ff601d6f3413738e4bb22c0a882ef83af7\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:22:37,145 INFO backend.segmentation: [APPLY_TEXTURE] DONE 22.557s at 2026-05-11T15:22:37.145209+00:00
-2026-05-11 09:22:45,279 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:22:45.279333+00:00
-2026-05-11 09:22:49,178 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:22:51,446 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:22:51,982 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:22:53,829 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/d7b9735a-6e78-4fe3-8a42-109575b316a7 "HTTP/1.1 200 OK"
-2026-05-11 09:22:53,830 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:22:56,146 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:22:58,396 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=d7b9735a-6e78-4fe3-8a42-109575b316a7 "HTTP/1.1 200 OK"
-2026-05-11 09:23:06,755 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\9d8eab6a52e56697cb95b20e61dcc73246f45f3e0c14549e980ea1d8ab5411db\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:23:06,791 INFO backend.segmentation: [APPLY_TEXTURE] DONE 21.513s at 2026-05-11T15:23:06.791913+00:00
-2026-05-11 09:23:26,777 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-11T15:23:26.777258+00:00
-2026-05-11 09:23:29,185 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 09:23:31,437 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 09:23:31,854 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 09:23:33,733 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/28c290d8-f558-42f2-9807-2eb9a8ee03aa "HTTP/1.1 200 OK"
-2026-05-11 09:23:33,753 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 09:23:36,010 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 09:23:38,255 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=28c290d8-f558-42f2-9807-2eb9a8ee03aa "HTTP/1.1 200 OK"
-2026-05-11 09:23:46,257 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\dee0b06b7f3205e519abee75a0fd781fbc1d05fe893f21dc1d9562e0934ee509\image.webp "HTTP/1.1 200 OK"
-2026-05-11 09:23:46,296 INFO backend.segmentation: [APPLY_TEXTURE] DONE 19.519s at 2026-05-11T15:23:46.296656+00:00
-2026-05-11 15:49:44,491 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 15:49:44,515 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:05:50,322 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:05:50,344 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:05:51,265 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:05:51,287 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:06:23,124 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0252df14d88316415be4cb, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0252df14d88316415be4cb"}, "remainingTimeMS": 30}
-2026-05-11 16:06:28,118 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T22:06:28.118464+00:00
-2026-05-11 16:06:28,119 INFO backend.segmentation: [JOB 4209423fe883434baa0fc2b4775b34d6] preparing_image progress=12
-2026-05-11 16:06:28,171 INFO backend.segmentation: [JOB 4209423fe883434baa0fc2b4775b34d6] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 16:06:28,171 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 16:06:30,746 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 16:06:32,996 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 16:06:33,002 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-11 16:06:33,003 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 16:06:33,744 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 16:06:33,787 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 16:06:34,375 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 16:06:34,641 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 16:06:35,061 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/4139b1e8-0885-4eda-aa82-fd71c176ecae "HTTP/1.1 200 OK"
-2026-05-11 16:06:35,253 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 16:06:35,340 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/cedee08b-ac8c-488b-8942-f0fa0569e68f "HTTP/1.1 200 OK"
-2026-05-11 16:06:35,781 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 16:06:36,314 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=4139b1e8-0885-4eda-aa82-fd71c176ecae "HTTP/1.1 200 OK"
-2026-05-11 16:09:43,045 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/file=/tmp/gradio/6c61c4453525a0cc97a55213f8ab16e24157b02ad4d2cba459d14b95c79ac6ab/image.webp "HTTP/1.1 200 OK"
-2026-05-11 16:09:43,192 INFO services.gradio_client_service: Gradio Space segmentation: entorno=cpu motor=SAM Auto (CPU) mask_count=61
-2026-05-11 16:09:43,192 INFO backend.segmentation: [JOB 4209423fe883434baa0fc2b4775b34d6] saving_masks progress=92
-2026-05-11 16:09:43,346 INFO backend.segmentation: [JOB 4209423fe883434baa0fc2b4775b34d6] segments_meta saved (61 segments)
-2026-05-11 16:09:43,346 INFO backend.segmentation: [JOB 4209423fe883434baa0fc2b4775b34d6] done mask_count=61
-2026-05-11 16:09:43,347 INFO backend.segmentation: [UPLOAD_BG] DONE 195.229s at 2026-05-11T22:09:43.347393+00:00
-2026-05-11 16:09:43,347 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 16:10:57,618 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:10:57,643 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:11:03,882 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T22:11:03.882445+00:00
-2026-05-11 16:11:03,882 INFO backend.segmentation: [JOB 180176892d89444989453d181df30ddb] preparing_image progress=12
-2026-05-11 16:11:03,911 INFO backend.segmentation: [JOB 180176892d89444989453d181df30ddb] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 16:11:03,912 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 16:11:06,418 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
-2026-05-11 16:11:08,689 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 16:11:08,691 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
-2026-05-11 16:11:08,691 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 16:11:09,507 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 16:11:09,518 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
-2026-05-11 16:11:10,059 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
-2026-05-11 16:11:10,323 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
-2026-05-11 16:11:10,728 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/e5da0f2d-1f57-48c5-bb1e-66e9f7fec1b0 "HTTP/1.1 200 OK"
-2026-05-11 16:11:10,911 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
-2026-05-11 16:11:11,012 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e58b3da1-7be9-42cf-81f6-8c546e39f4be "HTTP/1.1 200 OK"
-2026-05-11 16:11:11,463 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
-2026-05-11 16:11:12,023 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=e5da0f2d-1f57-48c5-bb1e-66e9f7fec1b0 "HTTP/1.1 200 OK"
-2026-05-11 16:11:16,110 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a025404a5cb3b148eec3621, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a025404a5cb3b148eec3621"}, "remainingTimeMS": 30}
-2026-05-11 16:11:16,115 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a025404a5cb3b148eec3621, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a025404a5cb3b148eec3621"}, "remainingTimeMS": 30}
-2026-05-11 16:14:13,810 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/file=/tmp/gradio/6c61c4453525a0cc97a55213f8ab16e24157b02ad4d2cba459d14b95c79ac6ab/image.webp "HTTP/1.1 200 OK"
-2026-05-11 16:14:14,003 INFO services.gradio_client_service: Gradio Space segmentation: entorno=cpu motor=SAM Auto (CPU) mask_count=61
-2026-05-11 16:14:14,004 INFO backend.segmentation: [JOB 180176892d89444989453d181df30ddb] saving_masks progress=92
-2026-05-11 16:14:14,147 INFO backend.segmentation: [JOB 180176892d89444989453d181df30ddb] segments_meta saved (61 segments)
-2026-05-11 16:14:14,147 INFO backend.segmentation: [JOB 180176892d89444989453d181df30ddb] done mask_count=61
-2026-05-11 16:14:14,148 INFO backend.segmentation: [UPLOAD_BG] DONE 190.266s at 2026-05-11T22:14:14.148092+00:00
-2026-05-11 16:14:14,148 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 16:14:15,680 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:14:15,699 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:14:16,643 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:14:16,662 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:14:16,931 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0254b8ea5401b51d0278a3, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0254b8ea5401b51d0278a3"}, "remainingTimeMS": 30}
-2026-05-11 16:14:16,932 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0254b8ea5401b51d0278a3, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0254b8ea5401b51d0278a3"}, "remainingTimeMS": 30}
-2026-05-11 16:14:49,311 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:14:49,337 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:15:23,879 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0254fbaa6db1d011b1e697, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0254fbaa6db1d011b1e697"}, "remainingTimeMS": 30}
-2026-05-11 16:15:24,106 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0254fcaa6db1d011b1e698, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0254fcaa6db1d011b1e698"}, "remainingTimeMS": 30}
-2026-05-11 16:15:24,108 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0254fcaa6db1d011b1e698, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0254fcaa6db1d011b1e698"}, "remainingTimeMS": 30}
-2026-05-11 16:27:59,753 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=(not set — using local SAM2)
-2026-05-11 16:27:59,757 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=(not set — using local SAM2)
-2026-05-11 16:27:59,758 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=(not set — using local SAM2)
-2026-05-11 16:27:59,806 INFO backend.segmentation: [SAM2] Checking model paths:
-2026-05-11 16:27:59,806 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,807 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,807 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,807 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,808 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,808 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,809 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,809 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,809 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,809 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,810 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,810 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,810 INFO backend.segmentation: [SAM2] Checking model paths:
-2026-05-11 16:27:59,810 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,811 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,811 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,811 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,811 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,811 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,811 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,811 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,811 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,812 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,812 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,812 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,812 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,812 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,812 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,812 INFO backend.segmentation: [SAM2] Checking model paths:
-ve\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,813 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,813 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,813 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,813 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,813 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,813 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,813 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2_hiera_large.pt | exists=False
+2026-04-29 20:12:40,375 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-29 20:13:22,434 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69f2bac20e0544b45d45e6f1, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69f2bac20e0544b45d45e6f1"}, "remainingTimeMS": 30}
+2026-04-29 20:13:53,491 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:13:53.491443+00:00
+2026-04-29 20:13:53,492 INFO backend.segmentation: [JOB 667a8562af1044a6926d53449b625dd6] preparing_image progress=12
+2026-04-29 20:13:53,743 INFO backend.segmentation: [JOB 667a8562af1044a6926d53449b625dd6] segmenting_with_sam2 progress=30 estimated_seconds=51.939840000000004
+2026-04-29 20:13:56,153 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-29 20:13:56,625 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-29 20:13:56,675 WARNING services.gradio_client_service: Gradio Space call failed, falling back to local SAM2: Cannot find a function with `api_name`: /segment.
+2026-04-29 20:13:56,675 INFO backend.segmentation: [SAM2_GENERATE] START at 2026-04-30T02:13:56.675848+00:00
+2026-04-29 20:13:56,687 INFO backend.segmentation: [SAM2] Mask generator not loaded; attempting on-demand load.
+2026-04-29 20:13:56,687 WARNING backend.segmentation: [SAM2] torch not installed — SAM2 unavailable (using Gradio Space)
+2026-04-29 20:13:56,687 ERROR backend.segmentation: [JOB 667a8562af1044a6926d53449b625dd6] failed: 500: torch not installed — SAM2 unavailable (using Gradio Space)
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 145, in run_upload_job
+    label_map, mask_count = generate_label_map(image_rgb)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\scene_service.py", line 134, in generate_label_map
+    generator = get_sam2_mask_generator()
+                ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\sam2_service.py", line 184, in get_sam2_mask_generator
+    raise HTTPException(status_code=500, detail=detail)
+fastapi.exceptions.HTTPException: 500: torch not installed — SAM2 unavailable (using Gradio Space)
+2026-04-29 20:13:56,689 INFO backend.segmentation: [UPLOAD_BG] DONE 3.196s at 2026-04-30T02:13:56.689353+00:00
+2026-04-29 20:13:56,689 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-29 20:13:57,044 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-29 20:13:57,163 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/68121945-8a97-442e-8cbb-59cd817f9df3 "HTTP/1.1 200 OK"
+2026-04-29 20:16:38,951 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-29 20:16:55,032 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:16:55.032702+00:00
+2026-04-29 20:16:55,032 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] preparing_image progress=12
+2026-04-29 20:16:55,089 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] segmenting_with_sam2 progress=30 estimated_seconds=51.939840000000004
+2026-04-29 20:16:57,866 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-04-29 20:17:00,098 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-29 20:17:00,613 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-29 20:17:02,540 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/06d3302a-135c-423c-8294-e950bff0a17a "HTTP/1.1 200 OK"
+2026-04-29 20:17:02,542 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-29 20:17:04,774 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-29 20:17:07,079 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=06d3302a-135c-423c-8294-e950bff0a17a "HTTP/1.1 200 OK"
+2026-04-29 20:17:26,593 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\b17b68f6472ad2c6c0bb7499f231e242c50b344237d319bd3b45d56ef2d488aa\image.webp "HTTP/1.1 200 OK"
+2026-04-29 20:17:26,607 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🌳 Terraza / Patio / Jardín motor=Híbrido Arquitectura (Cityscapes Grande + DINO Pequeño) mask_count=20
+2026-04-29 20:17:26,607 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] saving_masks progress=92
+2026-04-29 20:17:26,690 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] segments_meta saved (20 segments)
+2026-04-29 20:17:26,690 INFO backend.segmentation: [JOB 50d2907ecb844a3fafc2f8a5247620ea] done mask_count=20
+2026-04-29 20:17:26,691 INFO backend.segmentation: [UPLOAD_BG] DONE 31.658s at 2026-04-30T02:17:26.691033+00:00
+2026-04-29 20:17:26,691 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-29 20:17:45,867 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:17:45.867306+00:00
+2026-04-29 20:17:46,402 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
+2026-04-29 20:17:46,702 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.835s at 2026-04-30T02:17:46.702156+00:00
+2026-04-29 20:17:50,496 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:17:50.496976+00:00
+2026-04-29 20:17:50,819 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
+2026-04-29 20:17:50,985 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.488s at 2026-04-30T02:17:50.985122+00:00
+2026-04-29 20:17:54,307 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:17:54.307539+00:00
+2026-04-29 20:17:54,768 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
+2026-04-29 20:17:54,931 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.624s at 2026-04-30T02:17:54.931489+00:00
+2026-04-29 20:17:56,247 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:17:56.247254+00:00
+2026-04-29 20:17:56,728 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
+2026-04-29 20:17:56,898 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.651s at 2026-04-30T02:17:56.898353+00:00
+2026-04-29 20:18:00,146 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:00.146989+00:00
+2026-04-29 20:18:00,616 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
+2026-04-29 20:18:00,782 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.636s at 2026-04-30T02:18:00.782444+00:00
+2026-04-29 20:18:05,560 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:05.560412+00:00
+2026-04-29 20:18:06,116 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
+2026-04-29 20:18:06,272 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.712s at 2026-04-30T02:18:06.272748+00:00
+2026-04-29 20:18:11,868 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:18:11.868080+00:00
+2026-04-29 20:18:11,868 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] preparing_image progress=12
+2026-04-29 20:18:11,941 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-29 20:18:14,341 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-04-29 20:18:16,543 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-29 20:18:16,695 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-29 20:18:18,825 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e332d34b-376c-4071-9631-656973e262a0 "HTTP/1.1 200 OK"
+2026-04-29 20:18:18,828 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-29 20:18:21,032 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-29 20:18:23,304 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e332d34b-376c-4071-9631-656973e262a0 "HTTP/1.1 200 OK"
+2026-04-29 20:18:36,010 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7b5a7a453887652d3284bb9eabe628e95982e15d5e0f16ff718d22beb5ed2a72\image.webp "HTTP/1.1 200 OK"
+2026-04-29 20:18:36,020 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
+2026-04-29 20:18:36,021 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] saving_masks progress=92
+2026-04-29 20:18:36,063 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] segments_meta saved (14 segments)
+2026-04-29 20:18:36,063 INFO backend.segmentation: [JOB 6897b1b65f7c4201ab0a5c35bf18b368] done mask_count=18
+2026-04-29 20:18:36,063 INFO backend.segmentation: [UPLOAD_BG] DONE 24.195s at 2026-04-30T02:18:36.063054+00:00
+2026-04-29 20:18:36,063 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-29 20:18:44,885 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:44.885155+00:00
+2026-04-29 20:18:45,431 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:18:45,591 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.706s at 2026-04-30T02:18:45.591016+00:00
+2026-04-29 20:18:49,898 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:49.898853+00:00
+2026-04-29 20:18:50,427 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:18:50,573 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.674s at 2026-04-30T02:18:50.573101+00:00
+2026-04-29 20:18:52,643 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:52.643494+00:00
+2026-04-29 20:18:53,101 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:18:53,259 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.615s at 2026-04-30T02:18:53.259095+00:00
+2026-04-29 20:18:55,884 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:55.884791+00:00
+2026-04-29 20:18:56,336 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:18:56,483 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.599s at 2026-04-30T02:18:56.483159+00:00
+2026-04-29 20:18:58,689 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:18:58.689702+00:00
+2026-04-29 20:18:59,139 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:18:59,285 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.596s at 2026-04-30T02:18:59.285688+00:00
+2026-04-29 20:19:01,587 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:01.587113+00:00
+2026-04-29 20:19:02,057 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:19:02,202 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.616s at 2026-04-30T02:19:02.202912+00:00
+2026-04-29 20:19:08,881 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:08.881813+00:00
+2026-04-29 20:19:09,450 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:19:09,598 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.716s at 2026-04-30T02:19:09.598660+00:00
+2026-04-29 20:19:14,081 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:14.081047+00:00
+2026-04-29 20:19:14,613 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:19:14,765 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.684s at 2026-04-30T02:19:14.765513+00:00
+2026-04-29 20:19:20,588 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:20.588691+00:00
+2026-04-29 20:19:21,001 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:19:21,148 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.560s at 2026-04-30T02:19:21.148963+00:00
+2026-04-29 20:19:26,717 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:19:26.717015+00:00
+2026-04-29 20:19:26,717 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] preparing_image progress=12
+2026-04-29 20:19:26,784 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-29 20:19:29,222 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-04-29 20:19:31,597 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-29 20:19:31,734 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-29 20:19:34,073 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/19c5143b-64ec-4b5d-942b-098f7096a07d "HTTP/1.1 200 OK"
+2026-04-29 20:19:34,076 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-29 20:19:36,338 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-29 20:19:38,618 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=19c5143b-64ec-4b5d-942b-098f7096a07d "HTTP/1.1 200 OK"
+2026-04-29 20:19:50,817 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\627367a96ce0d7cea77d51e3b57be3a803ddd9b06e2c8a9547129f322756dd05\image.webp "HTTP/1.1 200 OK"
+2026-04-29 20:19:50,828 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=13
+2026-04-29 20:19:50,828 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] saving_masks progress=92
+2026-04-29 20:19:50,860 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] segments_meta saved (13 segments)
+2026-04-29 20:19:50,861 INFO backend.segmentation: [JOB 0e77f0bbab294a828b0dbfbb826c3805] done mask_count=13
+2026-04-29 20:19:50,861 INFO backend.segmentation: [UPLOAD_BG] DONE 24.145s at 2026-04-30T02:19:50.861597+00:00
+2026-04-29 20:19:50,861 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-29 20:19:58,632 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:19:58.632422+00:00
+2026-04-29 20:19:58,950 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:19:59,096 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.464s at 2026-04-30T02:19:59.096073+00:00
+2026-04-29 20:20:03,025 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:20:03.025850+00:00
+2026-04-29 20:20:03,491 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:20:03,640 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.615s at 2026-04-30T02:20:03.640105+00:00
+2026-04-29 20:20:20,501 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:20:20.501928+00:00
+2026-04-29 20:20:21,076 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:20:21,227 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.727s at 2026-04-30T02:20:21.227737+00:00
+2026-04-29 20:20:28,266 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:20:28.266563+00:00
+2026-04-29 20:20:28,768 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:20:28,935 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.669s at 2026-04-30T02:20:28.935807+00:00
+2026-04-29 20:20:35,728 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:20:35.728058+00:00
+2026-04-29 20:20:35,729 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] preparing_image progress=12
+2026-04-29 20:20:35,790 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-29 20:20:38,252 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-04-29 20:20:40,610 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-29 20:20:40,810 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-29 20:20:43,106 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/31bdf8c4-3e85-4561-b055-cb540bff6222 "HTTP/1.1 200 OK"
+2026-04-29 20:20:43,110 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-29 20:20:45,435 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-29 20:20:47,968 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=31bdf8c4-3e85-4561-b055-cb540bff6222 "HTTP/1.1 200 OK"
+2026-04-29 20:21:09,199 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\de39b2da096587a3b0e0d7fb57541b12755192b377f4914a8047c40356bfbf4a\image.webp "HTTP/1.1 200 OK"
+2026-04-29 20:21:09,216 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=30
+2026-04-29 20:21:09,217 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] saving_masks progress=92
+2026-04-29 20:21:09,330 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] segments_meta saved (18 segments)
+2026-04-29 20:21:09,330 INFO backend.segmentation: [JOB f44cfa950b0546ffbcd7fa090bad49db] done mask_count=30
+2026-04-29 20:21:09,331 INFO backend.segmentation: [UPLOAD_BG] DONE 33.603s at 2026-04-30T02:21:09.331315+00:00
+2026-04-29 20:21:09,331 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-29 20:21:19,563 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:21:19.563482+00:00
+2026-04-29 20:21:19,875 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:21:20,037 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.474s at 2026-04-30T02:21:20.037544+00:00
+2026-04-29 20:21:27,716 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:21:27.716717+00:00
+2026-04-29 20:21:28,240 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:21:28,388 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.671s at 2026-04-30T02:21:28.388007+00:00
+2026-04-29 20:21:33,770 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:21:33.770053+00:00
+2026-04-29 20:21:34,297 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:21:34,445 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.676s at 2026-04-30T02:21:34.445668+00:00
+2026-04-29 20:21:45,556 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:21:45.556315+00:00
+2026-04-29 20:21:46,063 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:21:46,214 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.658s at 2026-04-30T02:21:46.214366+00:00
+2026-04-29 20:21:54,885 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:21:54.885450+00:00
+2026-04-29 20:21:54,886 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] preparing_image progress=12
+2026-04-29 20:21:55,003 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] segmenting_with_sam2 progress=30 estimated_seconds=138.4576
+2026-04-29 20:21:57,389 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-04-29 20:21:59,757 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-29 20:21:59,891 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-29 20:22:02,312 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-29 20:22:02,322 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/3f8ed7a1-4b28-46c2-9e01-7e4358b38e76 "HTTP/1.1 200 OK"
+2026-04-29 20:22:04,682 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-29 20:22:07,179 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=3f8ed7a1-4b28-46c2-9e01-7e4358b38e76 "HTTP/1.1 200 OK"
+2026-04-29 20:22:33,186 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\80421cbcd599451a04044e3ece45f375843574c97db6199cd4e3f022f90b9311\image.webp "HTTP/1.1 200 OK"
+2026-04-29 20:22:33,213 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=16
+2026-04-29 20:22:33,214 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] saving_masks progress=92
+2026-04-29 20:22:33,419 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] segments_meta saved (16 segments)
+2026-04-29 20:22:33,419 INFO backend.segmentation: [JOB ec618977b0b7478ca5d30d251fa15945] done mask_count=16
+2026-04-29 20:22:33,419 INFO backend.segmentation: [UPLOAD_BG] DONE 38.534s at 2026-04-30T02:22:33.419503+00:00
+2026-04-29 20:22:33,420 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-29 20:22:38,594 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:22:38.593824+00:00
+2026-04-29 20:22:38,977 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:22:39,402 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.808s at 2026-04-30T02:22:39.402689+00:00
+2026-04-29 20:22:44,189 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:22:44.189800+00:00
+2026-04-29 20:22:44,726 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:22:45,179 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.990s at 2026-04-30T02:22:45.179303+00:00
+2026-04-29 20:22:50,087 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:22:50.087424+00:00
+2026-04-29 20:22:50,751 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-29 20:22:51,466 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.379s at 2026-04-30T02:22:51.466435+00:00
+2026-04-29 20:26:39,065 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-29 20:26:39,964 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-29 20:33:56,025 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-29 20:34:02,828 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T02:34:02.828129+00:00
+2026-04-29 20:34:02,830 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] preparing_image progress=12
+2026-04-29 20:34:02,900 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] segmenting_with_sam2 progress=30 estimated_seconds=51.939840000000004
+2026-04-29 20:34:04,067 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-29 20:34:04,727 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-29 20:34:05,153 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-29 20:34:05,258 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/b306737b-bf28-4f02-8963-83b74032d449 "HTTP/1.1 200 OK"
+2026-04-29 20:34:05,354 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-29 20:34:05,788 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-29 20:34:06,344 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=b306737b-bf28-4f02-8963-83b74032d449 "HTTP/1.1 200 OK"
+2026-04-29 20:34:24,624 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/edcd82066c73a2359a9133192b4091c873fb9fca768c0f377a7a519aeb9f9b3a/image.webp "HTTP/1.1 200 OK"
+2026-04-29 20:34:24,678 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🌳 Terraza / Patio / Jardín motor=Híbrido Arquitectura (Cityscapes Grande + DINO Pequeño) mask_count=20
+2026-04-29 20:34:24,684 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] saving_masks progress=92
+2026-04-29 20:34:24,781 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] segments_meta saved (20 segments)
+2026-04-29 20:34:24,782 INFO backend.segmentation: [JOB ccecb5fbdf744d9eae57eb2b04e0af13] done mask_count=20
+2026-04-29 20:34:24,782 INFO backend.segmentation: [UPLOAD_BG] DONE 21.955s at 2026-04-30T02:34:24.782746+00:00
+2026-04-29 20:34:24,783 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-29 20:34:27,987 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T02:34:27.987941+00:00
+2026-04-29 20:34:28,292 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\proyecto-White-Houses.jpg
+2026-04-29 20:34:28,570 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.582s at 2026-04-30T02:34:28.570140+00:00
+2026-04-30 11:28:10,082 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 11:28:10,113 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-30 11:28:44,116 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T17:28:44.116002+00:00
+2026-04-30 11:28:44,117 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] preparing_image progress=12
+2026-04-30 11:28:44,411 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-30 11:28:44,411 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 11:28:47,099 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-30 11:28:47,585 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-30 11:28:48,272 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-30 11:28:48,363 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/7d7be152-f5b8-4924-8c4d-1a0b61711e8f "HTTP/1.1 200 OK"
+2026-04-30 11:28:48,476 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-30 11:28:48,934 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-30 11:28:49,386 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=7d7be152-f5b8-4924-8c4d-1a0b61711e8f "HTTP/1.1 200 OK"
+2026-04-30 11:29:08,489 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
+2026-04-30 11:29:08,588 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
+2026-04-30 11:29:08,590 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] saving_masks progress=92
+2026-04-30 11:29:08,688 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] segments_meta saved (14 segments)
+2026-04-30 11:29:08,688 INFO backend.segmentation: [JOB 9a15bbfe68f84bde8bdac60a8be4da9e] done mask_count=18
+2026-04-30 11:29:08,689 INFO backend.segmentation: [UPLOAD_BG] DONE 24.573s at 2026-04-30T17:29:08.689489+00:00
+2026-04-30 11:29:08,689 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-30 11:34:31,212 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 11:34:31,227 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-30 11:35:20,079 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 11:35:20,093 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-30 11:35:28,226 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T17:35:28.226030+00:00
+2026-04-30 11:35:28,227 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] preparing_image progress=12
+2026-04-30 11:35:28,315 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-30 11:35:28,316 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 11:35:29,381 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-30 11:35:29,927 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-30 11:35:30,567 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-30 11:35:30,680 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/846ae43c-81a8-48af-97ee-8292d522cc64 "HTTP/1.1 200 OK"
+2026-04-30 11:35:30,784 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-30 11:35:31,388 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-30 11:35:31,964 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=846ae43c-81a8-48af-97ee-8292d522cc64 "HTTP/1.1 200 OK"
+2026-04-30 11:35:43,682 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
+2026-04-30 11:35:43,788 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
+2026-04-30 11:35:43,788 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] saving_masks progress=92
+2026-04-30 11:35:43,874 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] segments_meta saved (14 segments)
+2026-04-30 11:35:43,875 INFO backend.segmentation: [JOB 48baf3b40f2f45d190f44cd2761c709e] done mask_count=18
+2026-04-30 11:35:43,875 INFO backend.segmentation: [UPLOAD_BG] DONE 15.650s at 2026-04-30T17:35:43.875230+00:00
+2026-04-30 11:35:43,876 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-30 11:37:18,311 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:18.311528+00:00
+2026-04-30 11:37:18,787 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:37:19,025 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.714s at 2026-04-30T17:37:19.025433+00:00
+2026-04-30 11:37:22,720 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:22.720207+00:00
+2026-04-30 11:37:23,223 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:37:23,371 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.651s at 2026-04-30T17:37:23.371172+00:00
+2026-04-30 11:37:27,040 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:27.040137+00:00
+2026-04-30 11:37:27,461 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:37:27,615 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.576s at 2026-04-30T17:37:27.615284+00:00
+2026-04-30 11:37:32,588 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T17:37:32.588150+00:00
+2026-04-30 11:37:32,589 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] preparing_image progress=12
+2026-04-30 11:37:32,652 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-30 11:37:32,653 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 11:37:33,265 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-30 11:37:33,854 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-30 11:37:34,045 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-30 11:37:34,638 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-30 11:37:35,300 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-30 11:37:35,353 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/f3fac27d-4abe-4757-a29c-4cc301d3c520 "HTTP/1.1 200 OK"
+2026-04-30 11:37:35,860 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=f3fac27d-4abe-4757-a29c-4cc301d3c520 "HTTP/1.1 200 OK"
+2026-04-30 11:37:45,344 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/525c342e2500d48137e90e793b9f3884aa3deedaa44ac6a6178e85433dde68ed/image.webp "HTTP/1.1 200 OK"
+2026-04-30 11:37:45,399 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=19
+2026-04-30 11:37:45,400 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] saving_masks progress=92
+2026-04-30 11:37:45,496 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] segments_meta saved (19 segments)
+2026-04-30 11:37:45,496 INFO backend.segmentation: [JOB 5a04157791ee46708b9659b06abc01cd] done mask_count=19
+2026-04-30 11:37:45,497 INFO backend.segmentation: [UPLOAD_BG] DONE 12.909s at 2026-04-30T17:37:45.497768+00:00
+2026-04-30 11:37:45,497 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-30 11:37:51,411 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:51.411336+00:00
+2026-04-30 11:37:51,902 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:37:52,048 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.637s at 2026-04-30T17:37:52.048476+00:00
+2026-04-30 11:37:54,874 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:54.874358+00:00
+2026-04-30 11:37:55,381 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:37:55,525 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.652s at 2026-04-30T17:37:55.525845+00:00
+2026-04-30 11:37:59,388 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:37:59.388707+00:00
+2026-04-30 11:37:59,889 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.05 < 0.35, skip perspective)
+2026-04-30 11:37:59,903 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:38:00,058 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.670s at 2026-04-30T17:38:00.058226+00:00
+2026-04-30 11:38:04,419 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:04.419644+00:00
+2026-04-30 11:38:04,939 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:38:05,083 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.664s at 2026-04-30T17:38:05.083669+00:00
+2026-04-30 11:38:09,485 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:09.485185+00:00
+2026-04-30 11:38:10,004 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:38:10,164 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.679s at 2026-04-30T17:38:10.164696+00:00
+2026-04-30 11:38:14,863 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:14.863574+00:00
+2026-04-30 11:38:15,447 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:38:15,612 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.750s at 2026-04-30T17:38:15.612415+00:00
+2026-04-30 11:38:18,118 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:18.118131+00:00
+2026-04-30 11:38:18,776 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:38:18,995 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.879s at 2026-04-30T17:38:18.995927+00:00
+2026-04-30 11:38:22,037 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:22.037510+00:00
+2026-04-30 11:38:22,686 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:38:22,873 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.835s at 2026-04-30T17:38:22.873532+00:00
+2026-04-30 11:38:25,520 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:25.520184+00:00
+2026-04-30 11:38:26,145 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:38:26,334 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.815s at 2026-04-30T17:38:26.334641+00:00
+2026-04-30 11:38:28,140 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:28.140486+00:00
+2026-04-30 11:38:28,847 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:38:29,023 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.882s at 2026-04-30T17:38:29.023363+00:00
+2026-04-30 11:38:35,098 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:38:35.098342+00:00
+2026-04-30 11:38:35,824 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:38:36,028 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.930s at 2026-04-30T17:38:36.028300+00:00
+2026-04-30 11:41:41,140 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T17:41:41.140015+00:00
+2026-04-30 11:41:41,149 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] preparing_image progress=12
+2026-04-30 11:41:41,245 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-30 11:41:41,246 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 11:41:41,911 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-30 11:41:42,462 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-30 11:41:42,643 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-30 11:41:43,175 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/3aef8110-e818-4b0d-b6eb-ea6e1e3f6d26 "HTTP/1.1 200 OK"
+2026-04-30 11:41:43,286 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-30 11:41:43,879 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-30 11:41:44,473 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=3aef8110-e818-4b0d-b6eb-ea6e1e3f6d26 "HTTP/1.1 200 OK"
+2026-04-30 11:41:54,142 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/be028661dd9bac57589c50374ec81fba3f6d33d75c68656f138199c7ecd043d5/image.webp "HTTP/1.1 200 OK"
+2026-04-30 11:41:54,248 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=13
+2026-04-30 11:41:54,250 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] saving_masks progress=92
+2026-04-30 11:41:54,306 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] segments_meta saved (13 segments)
+2026-04-30 11:41:54,307 INFO backend.segmentation: [JOB a63a4a48e2114d2a8a8ce7342d8b8443] done mask_count=13
+2026-04-30 11:41:54,307 INFO backend.segmentation: [UPLOAD_BG] DONE 13.167s at 2026-04-30T17:41:54.307037+00:00
+2026-04-30 11:41:54,308 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-30 11:43:18,472 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:43:18.472363+00:00
+2026-04-30 11:43:19,016 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:43:19,160 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.688s at 2026-04-30T17:43:19.160192+00:00
+2026-04-30 11:43:30,372 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:43:30.372475+00:00
+2026-04-30 11:43:30,954 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:43:31,098 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.727s at 2026-04-30T17:43:31.098668+00:00
+2026-04-30 11:47:34,143 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:47:34.143047+00:00
+2026-04-30 11:47:34,404 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:47:34,532 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.389s at 2026-04-30T17:47:34.532555+00:00
+2026-04-30 11:47:55,089 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T17:47:55.089325+00:00
+2026-04-30 11:47:55,583 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 11:47:55,730 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.641s at 2026-04-30T17:47:55.730378+00:00
+2026-04-30 12:04:38,148 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 12:04:38,173 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-30 12:09:38,204 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 12:09:38,219 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-30 12:13:52,707 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T18:13:52.707043+00:00
+2026-04-30 12:13:52,707 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] preparing_image progress=12
+2026-04-30 12:13:52,799 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-30 12:13:52,799 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 12:13:53,878 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-30 12:13:54,504 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-30 12:13:55,176 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-30 12:13:55,270 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/41cb0056-465a-425e-83c0-301658311ea8 "HTTP/1.1 200 OK"
+2026-04-30 12:13:55,368 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-30 12:13:55,904 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-30 12:13:56,487 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=41cb0056-465a-425e-83c0-301658311ea8 "HTTP/1.1 200 OK"
+2026-04-30 12:14:07,019 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
+2026-04-30 12:14:07,128 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
+2026-04-30 12:14:07,129 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] saving_masks progress=92
+2026-04-30 12:14:07,214 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] segments_meta saved (14 segments)
+2026-04-30 12:14:07,214 INFO backend.segmentation: [JOB 1df6118ebf3b4825b6acf36a62eb382b] done mask_count=18
+2026-04-30 12:14:07,215 INFO backend.segmentation: [UPLOAD_BG] DONE 14.509s at 2026-04-30T18:14:07.215535+00:00
+2026-04-30 12:14:07,216 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-30 12:15:26,031 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:26.031154+00:00
+2026-04-30 12:15:26,320 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 12:15:26,583 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.552s at 2026-04-30T18:15:26.583372+00:00
+2026-04-30 12:15:31,474 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:31.474416+00:00
+2026-04-30 12:15:31,999 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 12:15:32,141 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.667s at 2026-04-30T18:15:32.141076+00:00
+2026-04-30 12:15:37,533 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:37.533421+00:00
+2026-04-30 12:15:38,003 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 12:15:38,148 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.615s at 2026-04-30T18:15:38.148131+00:00
+2026-04-30 12:15:43,112 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:43.112106+00:00
+2026-04-30 12:15:43,495 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 12:15:43,639 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.528s at 2026-04-30T18:15:43.639421+00:00
+2026-04-30 12:15:48,170 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:15:48.170441+00:00
+2026-04-30 12:15:48,545 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 12:15:48,688 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.518s at 2026-04-30T18:15:48.688355+00:00
+2026-04-30 12:21:38,766 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T18:21:38.766212+00:00
+2026-04-30 12:21:38,766 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] preparing_image progress=12
+2026-04-30 12:21:38,838 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-30 12:21:38,838 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 12:21:39,938 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-30 12:21:41,143 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-30 12:21:41,334 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-30 12:21:41,668 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/a637527a-5267-4a6e-acc0-e57a7de5119a "HTTP/1.1 200 OK"
+2026-04-30 12:21:41,761 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-30 12:21:42,216 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-30 12:21:42,820 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=a637527a-5267-4a6e-acc0-e57a7de5119a "HTTP/1.1 200 OK"
+2026-04-30 12:21:50,974 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
+2026-04-30 12:21:51,074 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
+2026-04-30 12:21:51,074 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] saving_masks progress=92
+2026-04-30 12:21:51,145 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] segments_meta saved (14 segments)
+2026-04-30 12:21:51,146 INFO backend.segmentation: [JOB b99cc22c206c4e0380d3b2fe2e24ffc6] done mask_count=18
+2026-04-30 12:21:51,147 INFO backend.segmentation: [UPLOAD_BG] DONE 12.381s at 2026-04-30T18:21:51.147398+00:00
+2026-04-30 12:21:51,147 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-30 12:22:28,223 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:22:28.223162+00:00
+2026-04-30 12:22:28,488 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 12:22:28,633 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.410s at 2026-04-30T18:22:28.633219+00:00
+2026-04-30 12:23:38,541 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:23:38.541894+00:00
+2026-04-30 12:23:39,059 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.28 < 0.35, skip perspective)
+2026-04-30 12:23:39,078 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 12:23:39,224 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.682s at 2026-04-30T18:23:39.224901+00:00
+2026-04-30 12:23:47,739 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T18:23:47.739936+00:00
+2026-04-30 12:23:48,234 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.29 < 0.35, skip perspective)
+2026-04-30 12:23:48,249 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 12:23:48,393 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.654s at 2026-04-30T18:23:48.393543+00:00
+2026-04-30 12:35:04,237 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T18:35:04.237929+00:00
+2026-04-30 12:35:04,237 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] preparing_image progress=12
+2026-04-30 12:35:04,252 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] segmenting_with_sam2 progress=30 estimated_seconds=28.89164
+2026-04-30 12:35:04,252 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 12:35:04,919 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-30 12:35:05,542 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-30 12:35:05,767 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-30 12:35:06,228 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/e02fbff5-268c-40cf-bacf-e1c35bcf4346 "HTTP/1.1 200 OK"
+2026-04-30 12:35:06,341 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-30 12:35:06,892 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-30 12:35:07,458 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=e02fbff5-268c-40cf-bacf-e1c35bcf4346 "HTTP/1.1 200 OK"
+2026-04-30 12:35:29,382 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/75fa9ee4d8e3aa2f3926aa662e35acdfbaa3f94163e61a68527474a5a60675c3/image.webp "HTTP/1.1 200 OK"
+2026-04-30 12:35:29,438 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🏙️ Fachada / Exterior motor=Híbrido Arquitectura (Cityscapes Grande + DINO Pequeño) mask_count=12
+2026-04-30 12:35:29,439 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] saving_masks progress=92
+2026-04-30 12:35:29,463 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] segments_meta saved (11 segments)
+2026-04-30 12:35:29,463 INFO backend.segmentation: [JOB 0e62f0415d394dc8b28fae3fdce6ac1d] done mask_count=12
+2026-04-30 12:35:29,463 INFO backend.segmentation: [UPLOAD_BG] DONE 25.226s at 2026-04-30T18:35:29.463948+00:00
+2026-04-30 12:35:29,464 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-30 15:39:34,392 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 15:39:34,422 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-04-30 15:40:07,782 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69f3cc370fe929ed6cff073d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69f3cc370fe929ed6cff073d"}, "remainingTimeMS": 30}
+2026-04-30 15:40:18,856 INFO backend.segmentation: [UPLOAD_BG] START at 2026-04-30T21:40:18.856487+00:00
+2026-04-30 15:40:18,856 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] preparing_image progress=12
+2026-04-30 15:40:19,134 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-04-30 15:40:19,134 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-04-30 15:40:21,980 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-04-30 15:40:22,624 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-04-30 15:40:23,391 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-04-30 15:40:23,497 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/314c6a15-7cd5-4d38-88c5-58a08df1fad6 "HTTP/1.1 200 OK"
+2026-04-30 15:40:23,607 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-04-30 15:40:24,238 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-04-30 15:40:24,860 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=314c6a15-7cd5-4d38-88c5-58a08df1fad6 "HTTP/1.1 200 OK"
+2026-04-30 15:40:33,216 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d71a861910d02311782c5f826bb80cc1fd74d6f6086844534a04a02edf930180/image.webp "HTTP/1.1 200 OK"
+2026-04-30 15:40:33,324 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛁 Baño / Cocina motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=18
+2026-04-30 15:40:33,325 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] saving_masks progress=92
+2026-04-30 15:40:33,428 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] segments_meta saved (14 segments)
+2026-04-30 15:40:33,428 INFO backend.segmentation: [JOB 65636043fc364d5bba59fca718f4eb87] done mask_count=18
+2026-04-30 15:40:33,429 INFO backend.segmentation: [UPLOAD_BG] DONE 14.573s at 2026-04-30T21:40:33.429138+00:00
+2026-04-30 15:40:33,429 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-04-30 15:40:38,479 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T21:40:38.479968+00:00
+2026-04-30 15:40:38,976 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 15:40:39,252 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.773s at 2026-04-30T21:40:39.252883+00:00
+2026-04-30 16:21:48,502 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-04-30T22:21:48.502651+00:00
+2026-04-30 16:21:49,012 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-04-30 16:21:49,158 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.656s at 2026-04-30T22:21:49.158351+00:00
+2026-05-06 18:02:51,635 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-06 18:02:51,663 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 18:03:05,661 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fbd6b9d024dc8e891e4555, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fbd6b9d024dc8e891e4555"}, "remainingTimeMS": 30}
+2026-05-06 18:03:54,118 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:03:54.118398+00:00
+2026-05-06 18:03:54,119 INFO backend.segmentation: [JOB e0df636678f746dc9b2d4a29256ab769] preparing_image progress=12
+2026-05-06 18:03:54,441 INFO backend.segmentation: [JOB e0df636678f746dc9b2d4a29256ab769] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
+2026-05-06 18:03:54,441 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 18:03:59,802 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:04:02,031 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:04:02,051 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:04:02,051 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7860
+2026-05-06 18:04:02,487 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:04:04,382 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:04:04,396 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/07a1a8b9-03be-4f34-9425-2b264489eb61 "HTTP/1.1 200 OK"
+2026-05-06 18:04:06,807 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:04:06,810 ERROR backend.segmentation: [JOB e0df636678f746dc9b2d4a29256ab769] failed: cannot access local variable 'exc_gpu' where it is not associated with a value
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 89, in segment_via_gradio_sync
+    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
+    _overlay_file, combined_json_str = client.predict(
+                                       ^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 497, in predict
+    return self.submit(
+           ^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 543, in submit
+    inferred_fn_index = self._infer_fn_index(api_name, fn_index)
+                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 881, in _infer_fn_index
+    raise ValueError(error_message)
+ValueError: Cannot find a function with `api_name`: /segment.
 
-2026-05-11 16:27:59,813 ERROR backend.segmentation: [SAM2] ERROR: SAM 2 model file not found. Tried the following paths:
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2_hiera_large.pt
-Set SAM2_MODEL_PATH to the checkpoint location.
-2026-05-11 16:27:59,813 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,814 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,814 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,814 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,814 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,814 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,814 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large_fresh.pt | exists=False
-2026-05-11 16:27:59,814 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,814 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,815 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,815 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,815 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,815 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,815 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,815 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,815 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,815 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,816 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,816 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pt | exists=False
-2026-05-11 16:27:59,816 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,816 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,816 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,816 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,816 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,816 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,816 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,817 ERROR backend.segmentation: [SAM2] ERROR: SAM 2 model file not found. Tried the following paths:
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2_hiera_large.pt
-Set SAM2_MODEL_PATH to the checkpoint location.
-2026-05-11 16:27:59,817 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,817 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,817 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pth | exists=False
-2026-05-11 16:27:59,817 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,818 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,818 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,818 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,818 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,818 INFO backend.segmentation: [SAM2] - C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2_hiera_large.pt | exists=False
-2026-05-11 16:27:59,818 ERROR backend.segmentation: [SAM2] ERROR: SAM 2 model file not found. Tried the following paths:
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large_fresh.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2.1_hiera_large.pth
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\models\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\models\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\modelo\sam2_hiera_large.pt
-- C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\modelo\sam2_hiera_large.pt
-Set SAM2_MODEL_PATH to the checkpoint location.
-2026-05-11 16:27:59,917 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 16:27:59,917 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 16:27:59,932 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 16:27:59,933 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 16:27:59,933 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 16:27:59,933 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 16:28:07,147 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:28:07,147 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:28:07,148 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:28:07,164 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:28:07,164 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:28:07,165 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:31:47,348 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:31:47,360 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:31:48,139 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:31:48,153 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:32:34,878 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:32:34,898 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:32:35,134 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:32:35,142 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:32:35,155 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:32:35,160 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:33:03,614 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:33:03,631 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:33:03,838 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:33:03,857 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:33:03,874 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:33:03,890 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:33:27,698 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:33:27,711 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:33:28,467 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:33:28,479 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:33:35,174 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:33:35,185 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:35:52,942 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:35:52,944 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:35:52,951 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:35:52,968 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:35:52,970 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:35:52,974 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:36:02,795 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:36:02,806 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:36:02,822 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:36:02,837 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:36:02,851 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:36:02,902 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:36:18,763 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:36:18,791 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:38:44,845 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:38:44,846 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:38:44,864 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:38:44,865 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:38:44,946 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:38:44,964 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:44:31,497 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:44:31,522 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:45:00,726 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T22:45:00.726193+00:00
-2026-05-11 16:45:00,726 INFO backend.segmentation: [JOB 9df754b89e794ddf81b412c1c417a64b] preparing_image progress=12
-2026-05-11 16:45:00,795 INFO backend.segmentation: [JOB 9df754b89e794ddf81b412c1c417a64b] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 16:45:00,795 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 16:45:01,032 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 16:45:01,032 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 16:45:01,033 ERROR backend.segmentation: [JOB 9df754b89e794ddf81b412c1c417a64b] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-    client = Client(space_url, httpx_kwargs={"timeout": 300.0})
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-    ...<3 lines>...
-    ) from exc_cpu
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 16:45:01,034 INFO backend.segmentation: [UPLOAD_BG] DONE 0.308s at 2026-05-11T22:45:01.034236+00:00
-2026-05-11 16:45:01,034 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 16:47:49,523 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T22:47:49.523811+00:00
-2026-05-11 16:47:49,524 INFO backend.segmentation: [JOB 0742c2f8d0c2446d8c7d8de8d4412464] preparing_image progress=12
-2026-05-11 16:47:49,543 INFO backend.segmentation: [JOB 0742c2f8d0c2446d8c7d8de8d4412464] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 16:47:49,543 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 16:47:49,543 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 16:47:49,543 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 16:47:49,544 ERROR backend.segmentation: [JOB 0742c2f8d0c2446d8c7d8de8d4412464] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-    client = Client(space_url, httpx_kwargs={"timeout": 300.0})
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-    ...<3 lines>...
-    ) from exc_cpu
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 16:47:49,545 INFO backend.segmentation: [UPLOAD_BG] DONE 0.022s at 2026-05-11T22:47:49.545319+00:00
-2026-05-11 16:47:49,545 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 16:47:55,620 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T22:47:55.620933+00:00
-2026-05-11 16:47:55,621 INFO backend.segmentation: [JOB 6441970dde1b47ca8bb3e489f5839c19] preparing_image progress=12
-2026-05-11 16:47:55,640 INFO backend.segmentation: [JOB 6441970dde1b47ca8bb3e489f5839c19] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 16:47:55,640 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 16:47:55,641 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 16:47:55,641 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 16:47:55,641 ERROR backend.segmentation: [JOB 6441970dde1b47ca8bb3e489f5839c19] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-    client = Client(space_url, httpx_kwargs={"timeout": 300.0})
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-    ...<3 lines>...
-    ) from exc_cpu
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 16:47:55,643 INFO backend.segmentation: [UPLOAD_BG] DONE 0.022s at 2026-05-11T22:47:55.643392+00:00
-2026-05-11 16:47:55,643 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 16:48:04,986 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:48:05,017 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:48:20,560 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T22:48:20.560278+00:00
-2026-05-11 16:48:20,560 INFO backend.segmentation: [JOB 926e56e3fb754b469dea9cbaf622e6d8] preparing_image progress=12
-2026-05-11 16:48:20,581 INFO backend.segmentation: [JOB 926e56e3fb754b469dea9cbaf622e6d8] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 16:48:20,581 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 16:48:20,581 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 16:48:20,581 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 16:48:20,582 ERROR backend.segmentation: [JOB 926e56e3fb754b469dea9cbaf622e6d8] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-    client = Client(space_url, httpx_kwargs={"timeout": 300.0})
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    label_map, mask_count = segment_via_gradio_sync(image_path)
-                            ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-    ...<3 lines>...
-    ) from exc_cpu
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 16:48:20,583 INFO backend.segmentation: [UPLOAD_BG] DONE 0.023s at 2026-05-11T22:48:20.583708+00:00
-2026-05-11 16:48:20,583 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 16:58:04,997 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:58:05,016 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 16:58:05,950 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 16:58:05,971 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 17:00:40,362 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:00:40.362157+00:00
-2026-05-11 17:00:40,362 INFO backend.segmentation: [JOB e08dc302227b460db3db112597ff63e2] preparing_image progress=12
-2026-05-11 17:00:40,388 INFO backend.segmentation: [JOB e08dc302227b460db3db112597ff63e2] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:00:40,389 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 17:00:40,389 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 17:00:40,389 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 17:00:40,389 ERROR backend.segmentation: [JOB e08dc302227b460db3db112597ff63e2] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-    client = Client(space_url, httpx_kwargs={"timeout": 300.0})
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    # We are simplifying the flow: skipping SAM 2 segmentation.
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-    ...<3 lines>...
-    ) from exc_cpu
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 17:00:40,393 INFO backend.segmentation: [UPLOAD_BG] DONE 0.031s at 2026-05-11T23:00:40.393043+00:00
-2026-05-11 17:00:40,393 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:01:51,772 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:01:51,792 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
-2026-05-11 17:01:52,577 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:01:52.577203+00:00
-2026-05-11 17:01:52,577 INFO backend.segmentation: [JOB b248488a436441c1af4769102b3e76a0] preparing_image progress=12
-2026-05-11 17:01:52,605 INFO backend.segmentation: [JOB b248488a436441c1af4769102b3e76a0] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:01:52,605 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 17:01:52,606 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 17:01:52,606 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 17:01:52,606 ERROR backend.segmentation: [JOB b248488a436441c1af4769102b3e76a0] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-    client = Client(space_url, httpx_kwargs={"timeout": 300.0})
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    # We are simplifying the flow: skipping SAM 2 segmentation.
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    raise RuntimeError(
-    ...<3 lines>...
-    ) from exc_cpu
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 17:01:52,608 INFO backend.segmentation: [UPLOAD_BG] DONE 0.032s at 2026-05-11T23:01:52.608875+00:00
-2026-05-11 17:01:52,609 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:05:12,352 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:05:12,378 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:05:12,379 WARNING backend.segmentation: Lifespan startup cancelled. Releasing resources.
-2026-05-11 17:05:12,380 INFO backend.segmentation: Releasing resources (full_unload=True)
-2026-05-11 17:05:12,418 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:05:12,419 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:05:15,614 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:05:15,643 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:05:22,954 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:05:22.954684+00:00
-2026-05-11 17:05:22,955 INFO backend.segmentation: [JOB 8c340c544ab84952bec7959289cecf9c] preparing_image progress=12
-2026-05-11 17:05:22,976 INFO backend.segmentation: [JOB 8c340c544ab84952bec7959289cecf9c] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:05:22,976 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 17:05:22,976 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 17:05:22,977 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 17:05:22,977 ERROR backend.segmentation: [JOB 8c340c544ab84952bec7959289cecf9c] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    # We are simplifying the flow: skipping SAM 2 segmentation.
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    try:
-    
-    ...<3 lines>...
-        raise RuntimeError(
-        ^^^^^^^^^^^^^^
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 17:05:22,979 INFO backend.segmentation: [UPLOAD_BG] DONE 0.025s at 2026-05-11T23:05:22.979381+00:00
-2026-05-11 17:05:22,979 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:07:10,779 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:07:10.779085+00:00
-2026-05-11 17:07:10,779 INFO backend.segmentation: [JOB 293b338a28b84ed4b5950719a8beecff] preparing_image progress=12
-2026-05-11 17:07:10,800 INFO backend.segmentation: [JOB 293b338a28b84ed4b5950719a8beecff] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:07:10,800 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 17:07:10,800 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 17:07:10,800 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 17:07:10,800 ERROR backend.segmentation: [JOB 293b338a28b84ed4b5950719a8beecff] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    # We are simplifying the flow: skipping SAM 2 segmentation.
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    try:
-    
-    ...<3 lines>...
-        raise RuntimeError(
-        ^^^^^^^^^^^^^^
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 17:07:10,802 INFO backend.segmentation: [UPLOAD_BG] DONE 0.023s at 2026-05-11T23:07:10.802362+00:00
-2026-05-11 17:07:10,802 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:07:52,210 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:07:52.210727+00:00
-2026-05-11 17:07:52,211 INFO backend.segmentation: [JOB a5fedf0501a94001b42fc9a71c7b75ca] preparing_image progress=12
-2026-05-11 17:07:52,230 INFO backend.segmentation: [JOB a5fedf0501a94001b42fc9a71c7b75ca] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:07:52,231 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 17:07:52,231 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 17:07:52,231 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 17:07:52,231 ERROR backend.segmentation: [JOB a5fedf0501a94001b42fc9a71c7b75ca] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    # We are simplifying the flow: skipping SAM 2 segmentation.
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    try:
-    
-    ...<3 lines>...
-        raise RuntimeError(
-        ^^^^^^^^^^^^^^
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 17:07:52,233 INFO backend.segmentation: [UPLOAD_BG] DONE 0.023s at 2026-05-11T23:07:52.233475+00:00
-2026-05-11 17:07:52,233 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:09:10,111 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:09:10.111062+00:00
-2026-05-11 17:09:10,111 INFO backend.segmentation: [JOB 0a7f381bf0964d229708409bc0c5bd3b] preparing_image progress=12
-2026-05-11 17:09:10,128 INFO backend.segmentation: [JOB 0a7f381bf0964d229708409bc0c5bd3b] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:09:10,129 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
-2026-05-11 17:09:10,129 WARNING services.gradio_client_service: GPU Space failed (Client.__init__() got an unexpected keyword argument 'httpx_kwargs'), trying CPU fallback...
-2026-05-11 17:09:10,129 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
-2026-05-11 17:09:10,129 ERROR backend.segmentation: [JOB 0a7f381bf0964d229708409bc0c5bd3b] failed: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
-    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 33, in _call_gradio_sync
-TypeError: Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
-    # We are simplifying the flow: skipping SAM 2 segmentation.
-  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
-    try:
-    
-    ...<3 lines>...
-        raise RuntimeError(
-        ^^^^^^^^^^^^^^
-RuntimeError: Both Gradio Spaces failed.
-  GPU (http://localhost:7860): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Client.__init__() got an unexpected keyword argument 'httpx_kwargs'
-2026-05-11 17:09:10,130 INFO backend.segmentation: [UPLOAD_BG] DONE 0.019s at 2026-05-11T23:09:10.130195+00:00
-2026-05-11 17:09:10,130 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:10:41,947 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:10:41,965 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:10:44,865 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0261f4b9a9473ac9483d03, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0261f4b9a9473ac9483d03"}, "remainingTimeMS": 30}
-2026-05-11 17:10:53,790 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:10:53.790345+00:00
-2026-05-11 17:10:53,790 INFO backend.segmentation: [JOB e7931cb747a044c0b5798ba3fd043246] preparing_image progress=12
-2026-05-11 17:10:53,918 INFO backend.segmentation: [JOB e7931cb747a044c0b5798ba3fd043246] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:10:53,919 INFO backend.segmentation: [JOB e7931cb747a044c0b5798ba3fd043246] done (simplified, 0 masks)
-2026-05-11 17:10:53,919 INFO backend.segmentation: [UPLOAD_BG] DONE 0.129s at 2026-05-11T23:10:53.919102+00:00
-2026-05-11 17:10:53,919 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:10:56,143 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a026200b9a9473ac9483d04, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026200b9a9473ac9483d04"}, "remainingTimeMS": 30}
-2026-05-11 17:10:58,808 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:10:58.808470+00:00
-2026-05-11 17:10:58,809 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.001s at 2026-05-11T23:10:58.809468+00:00
-2026-05-11 17:10:58,809 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:10:59,967 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:10:59.967490+00:00
-2026-05-11 17:10:59,967 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.001s at 2026-05-11T23:10:59.967490+00:00
-2026-05-11 17:10:59,968 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:11:13,886 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:11:13.886474+00:00
-2026-05-11 17:11:13,887 INFO backend.segmentation: [JOB 650975a38c7749568b7341423ad4d7d9] preparing_image progress=12
-2026-05-11 17:11:13,906 INFO backend.segmentation: [JOB 650975a38c7749568b7341423ad4d7d9] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:11:13,907 INFO backend.segmentation: [JOB 650975a38c7749568b7341423ad4d7d9] done (simplified, 0 masks)
-2026-05-11 17:11:13,907 INFO backend.segmentation: [UPLOAD_BG] DONE 0.021s at 2026-05-11T23:11:13.907778+00:00
-2026-05-11 17:11:13,907 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:11:28,374 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:11:28.374195+00:00
-2026-05-11 17:11:28,374 INFO backend.segmentation: [JOB 3f1f91ed35624099bffaf23f5c5badc3] preparing_image progress=12
-2026-05-11 17:11:28,400 INFO backend.segmentation: [JOB 3f1f91ed35624099bffaf23f5c5badc3] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:11:28,401 INFO backend.segmentation: [JOB 3f1f91ed35624099bffaf23f5c5badc3] done (simplified, 0 masks)
-2026-05-11 17:11:28,401 INFO backend.segmentation: [UPLOAD_BG] DONE 0.027s at 2026-05-11T23:11:28.401201+00:00
-2026-05-11 17:11:28,401 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:19:23,122 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:19:23,122 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:19:25,153 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:19:25,157 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:19:25,157 WARNING backend.segmentation: Lifespan startup cancelled. Releasing resources.
-2026-05-11 17:19:25,157 INFO backend.segmentation: Releasing resources (full_unload=True)
-2026-05-11 17:19:25,192 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:19:25,193 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:19:26,642 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:19:26,646 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:19:57,031 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:19:57,031 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:19:58,900 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:19:58,903 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:19:58,904 WARNING backend.segmentation: Lifespan startup cancelled. Releasing resources.
-2026-05-11 17:19:58,904 INFO backend.segmentation: Releasing resources (full_unload=True)
-2026-05-11 17:19:58,935 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:19:58,935 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:20:00,569 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:20:00,574 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:23:04,040 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:23:04,040 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:23:05,765 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:23:05,778 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:23:05,778 WARNING backend.segmentation: Lifespan startup cancelled. Releasing resources.
-2026-05-11 17:23:05,778 INFO backend.segmentation: Releasing resources (full_unload=True)
-2026-05-11 17:23:05,805 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:23:05,805 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:23:07,223 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:23:07,237 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:23:38,986 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0264fa2cee8192599ed7d0, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0264fa2cee8192599ed7d0"}, "remainingTimeMS": 30}
-2026-05-11 17:23:42,830 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-11T23:23:42.830320+00:00
-2026-05-11 17:23:42,831 INFO backend.segmentation: [JOB f67851b861634797a6d951fb8eb77d1c] preparing_image progress=12
-2026-05-11 17:23:42,987 INFO backend.segmentation: [JOB f67851b861634797a6d951fb8eb77d1c] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
-2026-05-11 17:23:42,988 INFO backend.segmentation: [JOB f67851b861634797a6d951fb8eb77d1c] done (simplified, 0 masks)
-2026-05-11 17:23:42,989 INFO backend.segmentation: [UPLOAD_BG] DONE 0.158s at 2026-05-11T23:23:42.989362+00:00
-2026-05-11 17:23:42,989 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:23:50,263 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:23:50,263 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:23:52,250 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:23:52,264 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:23:52,452 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a02650807bfc227790002e0, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02650807bfc227790002e0"}, "remainingTimeMS": 30}
-2026-05-11 17:35:48,564 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:35:48,564 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:35:51,035 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:35:51,056 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:35:51,056 WARNING backend.segmentation: Lifespan startup cancelled. Releasing resources.
-2026-05-11 17:35:51,056 INFO backend.segmentation: Releasing resources (full_unload=True)
-2026-05-11 17:35:51,100 INFO backend.segmentation: Lifespan exiting; releasing resources.
-2026-05-11 17:35:51,100 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:35:52,795 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
-2026-05-11 17:35:52,809 INFO backend.segmentation: [SAM2] SAM2 disabled (using Simplified OpenAI flow)
-2026-05-11 17:39:57,426 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0268cd69c7f8481e63f142, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0268cd69c7f8481e63f142"}, "remainingTimeMS": 30}
-2026-05-11 17:40:06,587 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:40:06.587125+00:00
-2026-05-11 17:40:06,587 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.000s at 2026-05-11T23:40:06.587125+00:00
-2026-05-11 17:40:06,587 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:42:20,430 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02695c8c7c9cbbe3d73a93, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02695c8c7c9cbbe3d73a93"}, "remainingTimeMS": 30}
-2026-05-11 17:42:23,168 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02695fd14dfcab99b31bb0, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02695fd14dfcab99b31bb0"}, "remainingTimeMS": 30}
-2026-05-11 17:42:24,195 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:42:24.195000+00:00
-2026-05-11 17:42:24,207 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.012s at 2026-05-11T23:42:24.207474+00:00
-2026-05-11 17:42:24,208 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:42:49,195 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:42:49.195264+00:00
-2026-05-11 17:42:49,202 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.007s at 2026-05-11T23:42:49.202264+00:00
-2026-05-11 17:42:49,202 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:42:50,897 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:42:50.897139+00:00
-2026-05-11 17:42:50,905 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.008s at 2026-05-11T23:42:50.905145+00:00
-2026-05-11 17:42:50,905 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:42:54,729 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:42:54.729010+00:00
-2026-05-11 17:42:54,737 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.008s at 2026-05-11T23:42:54.737010+00:00
-2026-05-11 17:42:54,737 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:44:02,023 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:44:02.023505+00:00
-2026-05-11 17:44:02,031 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.007s at 2026-05-11T23:44:02.031502+00:00
-2026-05-11 17:44:02,031 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:44:06,912 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:44:06.912421+00:00
-2026-05-11 17:44:06,919 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.007s at 2026-05-11T23:44:06.919421+00:00
-2026-05-11 17:44:06,919 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:44:08,458 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:44:08.458048+00:00
-2026-05-11 17:44:08,465 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.007s at 2026-05-11T23:44:08.465047+00:00
-2026-05-11 17:44:08,466 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:44:15,785 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:44:15.785067+00:00
-2026-05-11 17:44:15,792 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.008s at 2026-05-11T23:44:15.792067+00:00
-2026-05-11 17:44:15,793 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:44:45,666 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0269eda4c4e67897e4de91, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0269eda4c4e67897e4de91"}, "remainingTimeMS": 30}
-2026-05-11 17:44:50,557 INFO backend.segmentation: [APPLY_TEXTURE_AI] START at 2026-05-11T23:44:50.557167+00:00
-2026-05-11 17:44:50,565 INFO backend.segmentation: [APPLY_TEXTURE_AI] DONE 0.007s at 2026-05-11T23:44:50.565142+00:00
-2026-05-11 17:44:50,565 INFO backend.segmentation: Releasing resources (full_unload=False)
-2026-05-11 17:44:52,481 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0269f4a4c4e67897e4de92, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0269f4a4c4e67897e4de92"}, "remainingTimeMS": 30}
-2026-05-11 17:44:52,482 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0269f4a4c4e67897e4de92, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0269f4a4c4e67897e4de92"}, "remainingTimeMS": 30}
-2026-05-11 17:46:59,700 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a026a73d56a3146484b59dd, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026a73d56a3146484b59dd"}, "remainingTimeMS": 30}
-2026-05-11 17:47:05,233 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a026a79d56a3146484b59de, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026a79d56a3146484b59de"}, "remainingTimeMS": 30}
-2026-05-11 17:47:05,234 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a026a79d56a3146484b59de, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026a79d56a3146484b59de"}, "remainingTimeMS": 30}
-2026-05-11 17:47:30,427 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 17:47:56,420 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 17:50:02,713 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a026b2ac773958e310a1326, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026b2ac773958e310a1326"}, "remainingTimeMS": 30}
-2026-05-11 17:50:04,167 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a026b2cc773958e310a1327, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026b2cc773958e310a1327"}, "remainingTimeMS": 30}
-2026-05-11 17:50:04,207 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a026b2cc773958e310a1327, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026b2cc773958e310a1327"}, "remainingTimeMS": 30}
-2026-05-11 17:50:34,550 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 17:51:14,601 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 17:57:39,513 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a026cf3162482e62cf7ea3e, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026cf3162482e62cf7ea3e"}, "remainingTimeMS": 30}
-2026-05-11 17:57:42,313 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a026cf6472643c8c1e786d8, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026cf6472643c8c1e786d8"}, "remainingTimeMS": 30}
-2026-05-11 17:58:01,618 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 17:58:27,575 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 17:59:21,451 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 17:59:29,572 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a026d61676e4e120285cb22, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026d61676e4e120285cb22"}, "remainingTimeMS": 30}
-2026-05-11 17:59:32,127 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a026d649325671c76e0d3cc, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a026d649325671c76e0d3cc"}, "remainingTimeMS": 30}
-2026-05-11 18:00:00,476 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 18:00:20,146 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 18:00:36,292 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 18:13:24,578 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 18:22:57,043 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0272e19325671c76e0d3cd, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0272e19325671c76e0d3cd"}, "remainingTimeMS": 30}
-2026-05-11 18:22:57,044 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0272e19325671c76e0d3cd, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0272e19325671c76e0d3cd"}, "remainingTimeMS": 30}
-2026-05-11 18:23:24,738 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 18:43:21,019 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0277a9666e7bcf74e6e618, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0277a9666e7bcf74e6e618"}, "remainingTimeMS": 30}
-2026-05-11 18:47:06,723 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a02788a666e7bcf74e6e619, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02788a666e7bcf74e6e619"}, "remainingTimeMS": 30}
-2026-05-11 18:47:06,724 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a02788a666e7bcf74e6e619, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02788a666e7bcf74e6e619"}, "remainingTimeMS": 30}
-2026-05-11 18:47:14,864 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0278924b3f5d3d0d27e63c, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0278924b3f5d3d0d27e63c"}, "remainingTimeMS": 30}
-2026-05-11 18:47:17,556 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0278954a12dd2c11934073, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0278954a12dd2c11934073"}, "remainingTimeMS": 30}
-2026-05-11 18:47:40,240 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 18:47:53,426 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0278b94a12dd2c11934074, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0278b94a12dd2c11934074"}, "remainingTimeMS": 30}
-2026-05-11 18:47:53,426 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0278b94a12dd2c11934074, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0278b94a12dd2c11934074"}, "remainingTimeMS": 30}
-2026-05-11 19:06:05,368 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027cfda87b46fdcade70c0, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027cfda87b46fdcade70c0"}, "remainingTimeMS": 30}
-2026-05-11 19:06:12,738 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a027d04a87b46fdcade70c1, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027d04a87b46fdcade70c1"}, "remainingTimeMS": 30}
-2026-05-11 19:06:12,739 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a027d04a87b46fdcade70c1, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027d04a87b46fdcade70c1"}, "remainingTimeMS": 30}
-2026-05-11 19:08:06,520 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027d761ac5024147e14ddd, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027d761ac5024147e14ddd"}, "remainingTimeMS": 30}
-2026-05-11 19:08:47,155 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a027d9f1ac5024147e14dde, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027d9f1ac5024147e14dde"}, "remainingTimeMS": 30}
-2026-05-11 19:08:47,218 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a027d9f1ac5024147e14dde, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027d9f1ac5024147e14dde"}, "remainingTimeMS": 30}
-2026-05-11 19:09:25,574 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027dc593faabe7b94d01db, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027dc593faabe7b94d01db"}, "remainingTimeMS": 30}
-2026-05-11 19:09:28,759 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027dc83e594b87cb65fae1, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027dc83e594b87cb65fae1"}, "remainingTimeMS": 30}
-2026-05-11 19:11:42,248 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027e4e8ae5a4bdf2a01b4a, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027e4e8ae5a4bdf2a01b4a"}, "remainingTimeMS": 30}
-2026-05-11 19:11:45,646 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027e511d40e5545928f21a, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027e511d40e5545928f21a"}, "remainingTimeMS": 30}
-2026-05-11 19:12:29,155 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027e7d6b97ebcd8799b29a, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027e7d6b97ebcd8799b29a"}, "remainingTimeMS": 30}
-2026-05-11 19:12:32,505 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027e803a5d599a0d8af5ec, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027e803a5d599a0d8af5ec"}, "remainingTimeMS": 30}
-2026-05-11 19:12:38,840 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027e868bf43995e2ac9977, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027e868bf43995e2ac9977"}, "remainingTimeMS": 30}
-2026-05-11 19:15:15,838 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027f23949e3a6713885bd3, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027f23949e3a6713885bd3"}, "remainingTimeMS": 30}
-2026-05-11 19:15:16,974 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027f24949e3a6713885bd4, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027f24949e3a6713885bd4"}, "remainingTimeMS": 30}
-2026-05-11 19:15:51,653 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027f470f7d0c4f53d759f5, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027f470f7d0c4f53d759f5"}, "remainingTimeMS": 30}
-2026-05-11 19:15:52,590 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027f480f7d0c4f53d759f6, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027f480f7d0c4f53d759f6"}, "remainingTimeMS": 30}
-2026-05-11 19:17:39,169 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027fb35cc9f5b422b27472, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027fb35cc9f5b422b27472"}, "remainingTimeMS": 30}
-2026-05-11 19:17:40,232 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027fb45cc9f5b422b27473, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027fb45cc9f5b422b27473"}, "remainingTimeMS": 30}
-2026-05-11 19:17:43,584 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027fb7568814d4963dd0bb, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027fb7568814d4963dd0bb"}, "remainingTimeMS": 30}
-2026-05-11 19:17:44,583 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027fb8568814d4963dd0bc, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027fb8568814d4963dd0bc"}, "remainingTimeMS": 30}
-2026-05-11 19:18:49,835 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027ff9c4a2c8fb7771ae26, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027ff9c4a2c8fb7771ae26"}, "remainingTimeMS": 29}
-2026-05-11 19:18:51,007 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a027ffbc4a2c8fb7771ae27, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a027ffbc4a2c8fb7771ae27"}, "remainingTimeMS": 30}
-2026-05-11 19:19:00,509 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028004c4a2c8fb7771ae28, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028004c4a2c8fb7771ae28"}, "remainingTimeMS": 30}
-2026-05-11 19:19:34,358 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:20:25,698 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:23:23,468 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02810b6e10f71b8416429a, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02810b6e10f71b8416429a"}, "remainingTimeMS": 30}
-2026-05-11 19:23:24,520 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02810c6e10f71b8416429b, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02810c6e10f71b8416429b"}, "remainingTimeMS": 30}
-2026-05-11 19:25:05,589 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02817124161d08478a156b, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02817124161d08478a156b"}, "remainingTimeMS": 30}
-2026-05-11 19:25:06,714 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02817224161d08478a156c, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02817224161d08478a156c"}, "remainingTimeMS": 30}
-2026-05-11 19:25:28,914 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:26:13,818 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:26:21,775 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0281bd5ba8caf5a831ae90, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0281bd5ba8caf5a831ae90"}, "remainingTimeMS": 30}
-2026-05-11 19:26:22,789 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0281be5ba8caf5a831ae91, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0281be5ba8caf5a831ae91"}, "remainingTimeMS": 30}
-2026-05-11 19:36:28,448 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02841c703779c67f0d9b34, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02841c703779c67f0d9b34"}, "remainingTimeMS": 30}
-2026-05-11 19:36:29,570 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02841d703779c67f0d9b35, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02841d703779c67f0d9b35"}, "remainingTimeMS": 30}
-2026-05-11 19:36:33,261 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028421703779c67f0d9b36, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028421703779c67f0d9b36"}, "remainingTimeMS": 30}
-2026-05-11 19:36:33,261 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028421703779c67f0d9b36, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028421703779c67f0d9b36"}, "remainingTimeMS": 30}
-2026-05-11 19:37:02,209 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:39:05,683 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0284b9c02b8a2b4c1fd305, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0284b9c02b8a2b4c1fd305"}, "remainingTimeMS": 30}
-2026-05-11 19:39:09,088 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0284bd757457c966632fb6, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0284bd757457c966632fb6"}, "remainingTimeMS": 30}
-2026-05-11 19:39:10,088 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0284be757457c966632fb7, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0284be757457c966632fb7"}, "remainingTimeMS": 30}
-2026-05-11 19:39:52,700 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0284e8757457c966632fb8, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0284e8757457c966632fb8"}, "remainingTimeMS": 30}
-2026-05-11 19:39:52,701 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0284e8757457c966632fb8, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0284e8757457c966632fb8"}, "remainingTimeMS": 30}
-2026-05-11 19:41:00,305 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02852c8a1367122245eccc, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02852c8a1367122245eccc"}, "remainingTimeMS": 30}
-2026-05-11 19:41:03,225 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02852f267122fd694f21e3, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02852f267122fd694f21e3"}, "remainingTimeMS": 30}
-2026-05-11 19:41:04,203 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028530267122fd694f21e4, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028530267122fd694f21e4"}, "remainingTimeMS": 30}
-2026-05-11 19:41:41,968 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0285554c2f7ccbf3415908, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0285554c2f7ccbf3415908"}, "remainingTimeMS": 30}
-2026-05-11 19:41:42,925 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0285564c2f7ccbf3415909, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0285564c2f7ccbf3415909"}, "remainingTimeMS": 30}
-2026-05-11 19:42:05,869 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02856dac866a27c0a614ce, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02856dac866a27c0a614ce"}, "remainingTimeMS": 30}
-2026-05-11 19:42:07,090 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02856fac866a27c0a614cf, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02856fac866a27c0a614cf"}, "remainingTimeMS": 30}
-2026-05-11 19:42:08,500 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028570ac866a27c0a614d0, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028570ac866a27c0a614d0"}, "remainingTimeMS": 30}
-2026-05-11 19:42:08,500 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028570ac866a27c0a614d0, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028570ac866a27c0a614d0"}, "remainingTimeMS": 30}
-2026-05-11 19:42:45,966 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02859572403ff4d0782b8b, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02859572403ff4d0782b8b"}, "remainingTimeMS": 30}
-2026-05-11 19:42:46,913 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02859672403ff4d0782b8c, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02859672403ff4d0782b8c"}, "remainingTimeMS": 30}
-2026-05-11 19:42:59,118 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0285a372403ff4d0782b8d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0285a372403ff4d0782b8d"}, "remainingTimeMS": 30}
-2026-05-11 19:42:59,120 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0285a372403ff4d0782b8d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0285a372403ff4d0782b8d"}, "remainingTimeMS": 30}
-2026-05-11 19:43:13,311 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 19:43:33,906 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:48:53,424 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028705348962251040020b, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028705348962251040020b"}, "remainingTimeMS": 30}
-2026-05-11 19:48:54,613 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028706348962251040020c, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028706348962251040020c"}, "remainingTimeMS": 30}
-2026-05-11 19:48:56,049 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028708348962251040020d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028708348962251040020d"}, "remainingTimeMS": 30}
-2026-05-11 19:48:56,050 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028708348962251040020d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028708348962251040020d"}, "remainingTimeMS": 30}
-2026-05-11 19:48:56,051 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028708348962251040020d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028708348962251040020d"}, "remainingTimeMS": 30}
-2026-05-11 19:49:15,705 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 19:49:38,447 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:51:04,940 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0287887f7d678f206594ba, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0287887f7d678f206594ba"}, "remainingTimeMS": 30}
-2026-05-11 19:51:07,563 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02878bd029f8915c55e732, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02878bd029f8915c55e732"}, "remainingTimeMS": 30}
-2026-05-11 19:51:08,470 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02878cd029f8915c55e733, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02878cd029f8915c55e733"}, "remainingTimeMS": 30}
-2026-05-11 19:51:28,857 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 19:51:49,286 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:54:05,238 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02883d15dd6dc3e4f0f0b1, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02883d15dd6dc3e4f0f0b1"}, "remainingTimeMS": 30}
-2026-05-11 19:54:06,288 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02883e15dd6dc3e4f0f0b2, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02883e15dd6dc3e4f0f0b2"}, "remainingTimeMS": 30}
-2026-05-11 19:54:36,036 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02885c3027b040c1692ec0, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02885c3027b040c1692ec0"}, "remainingTimeMS": 30}
-2026-05-11 19:54:37,006 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02885d3027b040c1692ec1, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02885d3027b040c1692ec1"}, "remainingTimeMS": 30}
-2026-05-11 19:54:42,945 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0288623027b040c1692ec2, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0288623027b040c1692ec2"}, "remainingTimeMS": 30}
-2026-05-11 19:54:42,945 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0288623027b040c1692ec2, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0288623027b040c1692ec2"}, "remainingTimeMS": 30}
-2026-05-11 19:54:47,661 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 19:55:09,379 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:56:05,697 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0288b57400933c876eea54, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0288b57400933c876eea54"}, "remainingTimeMS": 30}
-2026-05-11 19:56:06,855 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0288b67400933c876eea55, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0288b67400933c876eea55"}, "remainingTimeMS": 30}
-2026-05-11 19:56:16,706 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0288c07400933c876eea56, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0288c07400933c876eea56"}, "remainingTimeMS": 30}
-2026-05-11 19:56:16,707 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0288c07400933c876eea56, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0288c07400933c876eea56"}, "remainingTimeMS": 30}
-2026-05-11 19:56:28,793 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0288ccf6c189e773fd6c5d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0288ccf6c189e773fd6c5d"}, "remainingTimeMS": 30}
-2026-05-11 19:56:29,776 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0288cdf6c189e773fd6c5e, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0288cdf6c189e773fd6c5e"}, "remainingTimeMS": 30}
-2026-05-11 19:56:34,696 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 19:56:59,964 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 19:58:10,776 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028932e1953cbd31f51412, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028932e1953cbd31f51412"}, "remainingTimeMS": 30}
-2026-05-11 19:58:11,857 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028933e1953cbd31f51413, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028933e1953cbd31f51413"}, "remainingTimeMS": 30}
-2026-05-11 19:58:53,417 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02895dafb540fa4caa5bd7, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02895dafb540fa4caa5bd7"}, "remainingTimeMS": 30}
-2026-05-11 19:58:56,404 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0289608155a426c77e36e5, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0289608155a426c77e36e5"}, "remainingTimeMS": 30}
-2026-05-11 19:58:57,390 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0289618155a426c77e36e6, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0289618155a426c77e36e6"}, "remainingTimeMS": 30}
-2026-05-11 19:59:02,129 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0289668155a426c77e36e7, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0289668155a426c77e36e7"}, "remainingTimeMS": 30}
-2026-05-11 19:59:02,130 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a0289668155a426c77e36e7, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0289668155a426c77e36e7"}, "remainingTimeMS": 30}
-2026-05-11 19:59:07,982 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 19:59:08,264 INFO backend.segmentation: OpenAI prompt length=919
-2026-05-11 19:59:28,536 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:00:00,304 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0289a0d1507d375ff12f71, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0289a0d1507d375ff12f71"}, "remainingTimeMS": 30}
-2026-05-11 20:00:01,492 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a0289a1d1507d375ff12f72, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0289a1d1507d375ff12f72"}, "remainingTimeMS": 30}
-2026-05-11 20:00:04,295 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:00:28,052 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:00:28,570 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:00:43,336 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:01:48,552 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:02:03,110 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:03:03,014 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028a578f37a4f8e8d7d66c, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028a578f37a4f8e8d7d66c"}, "remainingTimeMS": 30}
-2026-05-11 20:03:04,041 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028a588f37a4f8e8d7d66d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028a588f37a4f8e8d7d66d"}, "remainingTimeMS": 30}
-2026-05-11 20:03:05,250 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028a598f37a4f8e8d7d66e, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028a598f37a4f8e8d7d66e"}, "remainingTimeMS": 30}
-2026-05-11 20:03:05,250 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028a598f37a4f8e8d7d66e, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028a598f37a4f8e8d7d66e"}, "remainingTimeMS": 30}
-2026-05-11 20:03:16,863 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:03:31,328 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:04:42,487 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:04:58,256 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:06:22,491 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028b1ebc16a0851415bf50, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028b1ebc16a0851415bf50"}, "remainingTimeMS": 29}
-2026-05-11 20:06:23,537 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028b1fbc16a0851415bf51, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028b1fbc16a0851415bf51"}, "remainingTimeMS": 30}
-2026-05-11 20:06:47,110 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028b37a802942fd2594f91, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028b37a802942fd2594f91"}, "remainingTimeMS": 30}
-2026-05-11 20:06:49,908 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028b397b0f25a542e65c27, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028b397b0f25a542e65c27"}, "remainingTimeMS": 30}
-2026-05-11 20:06:50,920 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028b3a7b0f25a542e65c28, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028b3a7b0f25a542e65c28"}, "remainingTimeMS": 30}
-2026-05-11 20:11:50,807 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028c66b34267fbde5b34af, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028c66b34267fbde5b34af"}, "remainingTimeMS": 30}
-2026-05-11 20:11:51,851 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028c67b34267fbde5b34b0, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028c67b34267fbde5b34b0"}, "remainingTimeMS": 30}
-2026-05-11 20:13:05,234 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028cb1215d719b596e53d7, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028cb1215d719b596e53d7"}, "remainingTimeMS": 30}
-2026-05-11 20:13:06,341 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028cb2215d719b596e53d8, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028cb2215d719b596e53d8"}, "remainingTimeMS": 30}
-2026-05-11 20:15:36,865 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028d488e96660a60b8cfc4, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028d488e96660a60b8cfc4"}, "remainingTimeMS": 30}
-2026-05-11 20:15:37,926 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028d498e96660a60b8cfc5, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028d498e96660a60b8cfc5"}, "remainingTimeMS": 30}
-2026-05-11 20:15:39,983 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028d4b8e96660a60b8cfc6, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028d4b8e96660a60b8cfc6"}, "remainingTimeMS": 30}
-2026-05-11 20:15:39,983 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028d4b8e96660a60b8cfc6, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028d4b8e96660a60b8cfc6"}, "remainingTimeMS": 30}
-2026-05-11 20:15:47,786 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:16:09,295 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:16:09,669 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\2d6e02255c3a4f00804ace65c49f19aa.png
-2026-05-11 20:16:09,844 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x0000029BEA759D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a028d698e96660a60b8cfc7, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028d698e96660a60b8cfc7"}, "remainingTimeMS": 30}
-2026-05-11 20:20:08,586 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028e58878a8628bfee7a9c, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028e58878a8628bfee7a9c"}, "remainingTimeMS": 30}
-2026-05-11 20:20:09,725 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028e59878a8628bfee7a9d, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028e59878a8628bfee7a9d"}, "remainingTimeMS": 30}
-2026-05-11 20:20:11,253 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028e5b878a8628bfee7a9e, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028e5b878a8628bfee7a9e"}, "remainingTimeMS": 30}
-2026-05-11 20:20:11,255 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028e5b878a8628bfee7a9e, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028e5b878a8628bfee7a9e"}, "remainingTimeMS": 30}
-2026-05-11 20:20:16,995 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:20:33,482 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:20:34,342 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\231900b690ad4adb9883a3d600716a7d.png
-2026-05-11 20:20:34,542 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x000001E117FD9D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a028e72878a8628bfee7a9f, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028e72878a8628bfee7a9f"}, "remainingTimeMS": 30}
-2026-05-11 20:20:46,915 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:21:02,580 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:21:02,987 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\d664c83e3b614760834cdaad28769340.png
-2026-05-11 20:21:03,168 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x000001E117FD9D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a028e8f878a8628bfee7aa0, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028e8f878a8628bfee7aa0"}, "remainingTimeMS": 30}
-2026-05-11 20:24:43,167 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028f6bdd1d2a0373a94f3c, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028f6bdd1d2a0373a94f3c"}, "remainingTimeMS": 30}
-2026-05-11 20:24:46,257 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028f6ef42c431356712eb2, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028f6ef42c431356712eb2"}, "remainingTimeMS": 30}
-2026-05-11 20:24:47,309 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a028f6ff42c431356712eb3, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028f6ff42c431356712eb3"}, "remainingTimeMS": 30}
-2026-05-11 20:24:48,513 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028f70f42c431356712eb4, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028f70f42c431356712eb4"}, "remainingTimeMS": 30}
-2026-05-11 20:24:48,514 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a028f70f42c431356712eb4, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028f70f42c431356712eb4"}, "remainingTimeMS": 30}
-2026-05-11 20:24:50,217 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:25:09,782 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:25:10,153 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\5b6f11b554f74c5486ce33e390f8c75d.png
-2026-05-11 20:25:10,323 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x000001B7BDBC9D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a028f86f42c431356712eb5, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028f86f42c431356712eb5"}, "remainingTimeMS": 30}
-2026-05-11 20:26:39,620 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:27:01,355 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:27:01,729 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\032d76c129a442cebeac3323bc4fc080.png
-2026-05-11 20:27:01,908 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x000001B7BDBC9D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a028ff5f42c431356712eb6, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a028ff5f42c431356712eb6"}, "remainingTimeMS": 30}
-2026-05-11 20:27:10,935 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:27:31,741 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:27:32,280 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\08a1798e9521455a902edda85dc029cc.png
-2026-05-11 20:27:32,545 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x000001B7BDBC9D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a029014f42c431356712eb7, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a029014f42c431356712eb7"}, "remainingTimeMS": 30}
-2026-05-11 20:27:58,182 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:28:46,217 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:28:46,940 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\1bc4caa711694fb8acca6b23159f754f.png
-2026-05-11 20:28:47,112 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x000001B7BDBC9D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a02905ff42c431356712eb8, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02905ff42c431356712eb8"}, "remainingTimeMS": 30}
-2026-05-11 20:29:03,508 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:29:44,213 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:29:44,750 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\2a5b913b68a243379027cd01b187b4cd.png
-2026-05-11 20:29:44,955 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x000001B7BDBC9D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a029098f42c431356712eb9, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a029098f42c431356712eb9"}, "remainingTimeMS": 30}
-2026-05-11 20:29:53,559 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 20:30:37,983 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 20:30:38,490 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\836b20819d49430a9fc94c02e8e07885.png
-2026-05-11 20:30:38,711 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x000001B7BDBC9D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a0290cef42c431356712eba, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a0290cef42c431356712eba"}, "remainingTimeMS": 30}
-2026-05-11 21:01:35,945 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02980ff2c1d98dfeb7f208, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02980ff2c1d98dfeb7f208"}, "remainingTimeMS": 30}
-2026-05-11 21:01:37,029 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a029811f2c1d98dfeb7f209, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a029811f2c1d98dfeb7f209"}, "remainingTimeMS": 30}
-2026-05-11 21:01:40,034 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 6a029814f2c1d98dfeb7f20a, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a029814f2c1d98dfeb7f20a"}, "remainingTimeMS": 30}
-2026-05-11 21:01:47,994 INFO backend.segmentation: /api/generate-image received file: hyper-reality-1778254222964.jpg (84903 bytes)
-2026-05-11 21:02:33,393 INFO httpx: HTTP Request: POST https://api.openai.com/v1/images/edits "HTTP/1.1 200 OK"
-2026-05-11 21:02:34,216 INFO backend.segmentation: Saved generated image to C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\generated\dbd083972cf5430998885a9f7c36ac0a.png
-2026-05-11 21:02:34,417 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "<function writable_server_selector at 0x000001F9459E9D00>", "operation": "update", "topologyDescription": "<TopologyDescription id: 6a02984af2c1d98dfeb7f20b, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02984af2c1d98dfeb7f20b"}, "remainingTimeMS": 30}
-2026-05-11 21:24:58,204 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a029d8a0918a81303de0d02, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a029d8a0918a81303de0d02"}, "remainingTimeMS": 29}
-2026-05-11 21:24:59,154 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a029d8b0918a81303de0d03, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a029d8b0918a81303de0d03"}, "remainingTimeMS": 29}
-2026-05-11 21:40:04,778 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a114e143b18e2c2e46c8, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a114e143b18e2c2e46c8"}, "remainingTimeMS": 29}
-2026-05-11 21:40:05,867 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a115e143b18e2c2e46c9, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a115e143b18e2c2e46c9"}, "remainingTimeMS": 29}
-2026-05-11 21:46:09,477 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a281ff1e49d9c28f7695, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a281ff1e49d9c28f7695"}, "remainingTimeMS": 29}
-2026-05-11 21:46:16,536 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a288f90e330b3179de27, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a288f90e330b3179de27"}, "remainingTimeMS": 29}
-2026-05-11 21:46:17,577 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a289f90e330b3179de28, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a289f90e330b3179de28"}, "remainingTimeMS": 29}
-2026-05-11 21:47:09,901 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a2bda0a2f71661c7b112, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a2bda0a2f71661c7b112"}, "remainingTimeMS": 29}
-2026-05-11 21:47:10,936 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a2bea0a2f71661c7b113, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a2bea0a2f71661c7b113"}, "remainingTimeMS": 29}
-2026-05-11 21:49:09,831 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a33516532d6089e0e139, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a33516532d6089e0e139"}, "remainingTimeMS": 29}
-2026-05-11 21:49:10,788 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a33616532d6089e0e13a, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a33616532d6089e0e13a"}, "remainingTimeMS": 29}
-2026-05-11 21:50:09,487 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a371f53852099a1aed16, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a371f53852099a1aed16"}, "remainingTimeMS": 29}
-2026-05-11 21:50:16,933 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a378b6b31aba4a4c1c52, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a378b6b31aba4a4c1c52"}, "remainingTimeMS": 29}
-2026-05-11 21:50:17,879 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "count", "topologyDescription": "<TopologyDescription id: 6a02a379b6b31aba4a4c1c53, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "6a02a379b6b31aba4a4c1c53"}, "remainingTimeMS": 29}
+During handling of the above exception, another exception occurred:
+
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
+    label_map, mask_count = segment_via_gradio_sync(image_path)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
+    f"  GPU ({GRADIO_SPACE_URL}): {exc_gpu}\n"
+                                   ^^^^^^^
+UnboundLocalError: cannot access local variable 'exc_gpu' where it is not associated with a value
+2026-05-06 18:04:06,834 INFO backend.segmentation: [UPLOAD_BG] DONE 12.716s at 2026-05-07T00:04:06.834047+00:00
+2026-05-06 18:04:06,838 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 18:04:06,884 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:04:09,275 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/04b260c2-1554-4cba-a89f-13976ed4ac4d "HTTP/1.1 200 OK"
+2026-05-06 18:09:42,042 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-06 18:09:42,064 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 18:09:42,071 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:09:42.071378+00:00
+2026-05-06 18:09:42,076 INFO backend.segmentation: [JOB 45db3dde20444c6f97e1653fd7df1d17] preparing_image progress=12
+2026-05-06 18:09:42,120 INFO backend.segmentation: [JOB 45db3dde20444c6f97e1653fd7df1d17] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
+2026-05-06 18:09:42,121 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 18:09:44,483 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:09:46,855 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:09:46,857 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:09:46,861 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7860
+2026-05-06 18:09:47,293 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:09:49,183 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/1780c9d0-ac88-47b0-b6c1-3cf40997667d "HTTP/1.1 200 OK"
+2026-05-06 18:09:49,199 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:09:51,480 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:09:51,485 ERROR backend.segmentation: [JOB 45db3dde20444c6f97e1653fd7df1d17] failed: Both Gradio Spaces failed.
+  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
+    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
+    _overlay_file, combined_json_str = client.predict(
+                                       ^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 497, in predict
+    return self.submit(
+           ^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 543, in submit
+    inferred_fn_index = self._infer_fn_index(api_name, fn_index)
+                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 881, in _infer_fn_index
+    raise ValueError(error_message)
+ValueError: Cannot find a function with `api_name`: /segment.
+
+The above exception was the direct cause of the following exception:
+
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
+    label_map, mask_count = segment_via_gradio_sync(image_path)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
+    raise RuntimeError(
+RuntimeError: Both Gradio Spaces failed.
+  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+2026-05-06 18:09:51,487 INFO backend.segmentation: [UPLOAD_BG] DONE 9.415s at 2026-05-07T00:09:51.487122+00:00
+2026-05-06 18:09:51,487 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 18:09:51,545 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:09:53,753 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/36233c91-f2f7-4ec1-9a12-3d21c85acebf "HTTP/1.1 200 OK"
+2026-05-06 18:13:22,286 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:13:22.286531+00:00
+2026-05-06 18:13:22,286 INFO backend.segmentation: [JOB 1d0df1096d5f465b92fae7922f6f7018] preparing_image progress=12
+2026-05-06 18:13:22,361 INFO backend.segmentation: [JOB 1d0df1096d5f465b92fae7922f6f7018] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
+2026-05-06 18:13:22,362 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 18:13:24,786 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:13:27,139 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:13:27,145 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:13:27,146 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7860
+2026-05-06 18:13:27,264 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:13:29,620 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/903b6662-21a9-407f-849d-a09f627bf22b "HTTP/1.1 200 OK"
+2026-05-06 18:13:29,696 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:13:32,103 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:13:32,109 ERROR backend.segmentation: [JOB 1d0df1096d5f465b92fae7922f6f7018] failed: Both Gradio Spaces failed.
+  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
+    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
+    _overlay_file, combined_json_str = client.predict(
+                                       ^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 497, in predict
+    return self.submit(
+           ^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 543, in submit
+    inferred_fn_index = self._infer_fn_index(api_name, fn_index)
+                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 881, in _infer_fn_index
+    raise ValueError(error_message)
+ValueError: Cannot find a function with `api_name`: /segment.
+
+The above exception was the direct cause of the following exception:
+
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
+    label_map, mask_count = segment_via_gradio_sync(image_path)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
+    raise RuntimeError(
+RuntimeError: Both Gradio Spaces failed.
+  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+2026-05-06 18:13:32,119 INFO backend.segmentation: [UPLOAD_BG] DONE 9.833s at 2026-05-07T00:13:32.119224+00:00
+2026-05-06 18:13:32,120 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 18:13:32,165 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:13:34,556 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e4f38b15-d04a-41ee-bb91-06226b8fcbae "HTTP/1.1 200 OK"
+2026-05-06 18:14:12,194 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-06 18:14:12,207 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 18:14:24,360 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:14:24.360597+00:00
+2026-05-06 18:14:24,360 INFO backend.segmentation: [JOB d0714cc4813c4ff5b969676107410712] preparing_image progress=12
+2026-05-06 18:14:24,496 INFO backend.segmentation: [JOB d0714cc4813c4ff5b969676107410712] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
+2026-05-06 18:14:24,496 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 18:14:27,292 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:14:29,710 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:14:29,737 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:14:29,738 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7860
+2026-05-06 18:14:30,337 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:14:32,244 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/b1361a06-2ac6-4b8d-8a1c-79a0b653d2d4 "HTTP/1.1 200 OK"
+2026-05-06 18:14:32,247 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:14:34,724 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:14:34,728 ERROR backend.segmentation: [JOB d0714cc4813c4ff5b969676107410712] failed: Both Gradio Spaces failed.
+  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
+    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
+    _overlay_file, combined_json_str = client.predict(
+                                       ^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 497, in predict
+    return self.submit(
+           ^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 543, in submit
+    inferred_fn_index = self._infer_fn_index(api_name, fn_index)
+                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 881, in _infer_fn_index
+    raise ValueError(error_message)
+ValueError: Cannot find a function with `api_name`: /segment.
+
+The above exception was the direct cause of the following exception:
+
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
+    label_map, mask_count = segment_via_gradio_sync(image_path)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
+    raise RuntimeError(
+RuntimeError: Both Gradio Spaces failed.
+  GPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+  CPU (http://localhost:7860): Cannot find a function with `api_name`: /segment.
+2026-05-06 18:14:34,732 INFO backend.segmentation: [UPLOAD_BG] DONE 10.372s at 2026-05-07T00:14:34.731556+00:00
+2026-05-06 18:14:34,732 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 18:14:34,784 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:14:37,121 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e7673631-cbf6-43a7-8391-415fae5fc0e9 "HTTP/1.1 200 OK"
+2026-05-06 18:16:40,330 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-06 18:16:40,344 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 18:16:46,189 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:16:46.189444+00:00
+2026-05-06 18:16:46,189 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] preparing_image progress=12
+2026-05-06 18:16:46,293 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
+2026-05-06 18:16:46,293 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 18:16:49,078 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:16:51,479 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:16:51,497 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:16:51,498 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 18:16:52,101 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:16:54,019 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/6b53345b-dde9-4c3f-9adc-6c494ed360ef "HTTP/1.1 200 OK"
+2026-05-06 18:16:54,024 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 18:16:56,487 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:16:56,549 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:16:58,924 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/74fea2e0-6f0d-4dda-a138-a42ba84fc0aa "HTTP/1.1 200 OK"
+2026-05-06 18:16:58,960 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 18:17:01,339 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 18:17:03,913 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=74fea2e0-6f0d-4dda-a138-a42ba84fc0aa "HTTP/1.1 200 OK"
+2026-05-06 18:19:23,132 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\bdc55057e453f1e4793eccb7f3297d66322074e960cb173c3fcf63268faa1561\image.webp "HTTP/1.1 200 OK"
+2026-05-06 18:19:23,155 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🏙️ Fachada / Exterior motor=SAM Auto (Exteriores - Sin Prompts) mask_count=95
+2026-05-06 18:19:23,156 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] saving_masks progress=92
+2026-05-06 18:19:23,605 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] segments_meta saved (93 segments)
+2026-05-06 18:19:23,607 INFO backend.segmentation: [JOB a0e5eea5ea454870abc22c495d503be4] done mask_count=95
+2026-05-06 18:19:23,607 INFO backend.segmentation: [UPLOAD_BG] DONE 157.419s at 2026-05-07T00:19:23.607772+00:00
+2026-05-06 18:19:23,607 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 18:19:34,201 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:34.200405+00:00
+2026-05-06 18:19:34,746 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:19:35,040 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.840s at 2026-05-07T00:19:35.040623+00:00
+2026-05-06 18:19:42,196 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:42.196103+00:00
+2026-05-06 18:19:42,742 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:19:42,974 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.779s at 2026-05-07T00:19:42.974981+00:00
+2026-05-06 18:19:47,421 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:47.421826+00:00
+2026-05-06 18:19:47,977 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:19:48,182 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.759s at 2026-05-07T00:19:48.182179+00:00
+2026-05-06 18:19:54,412 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:54.412542+00:00
+2026-05-06 18:19:54,866 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:19:55,074 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.662s at 2026-05-07T00:19:55.074817+00:00
+2026-05-06 18:19:57,905 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:57.905487+00:00
+2026-05-06 18:19:58,384 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:19:58,598 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.692s at 2026-05-07T00:19:58.598145+00:00
+2026-05-06 18:19:59,918 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:19:59.918562+00:00
+2026-05-06 18:20:00,391 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:00,605 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.687s at 2026-05-07T00:20:00.605635+00:00
+2026-05-06 18:20:01,887 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:01.887221+00:00
+2026-05-06 18:20:02,339 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:02,550 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.663s at 2026-05-07T00:20:02.550706+00:00
+2026-05-06 18:20:04,982 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:04.982372+00:00
+2026-05-06 18:20:05,541 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:05,754 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.772s at 2026-05-07T00:20:05.753433+00:00
+2026-05-06 18:20:09,130 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:09.130132+00:00
+2026-05-06 18:20:09,706 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:09,918 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.788s at 2026-05-07T00:20:09.918209+00:00
+2026-05-06 18:20:13,606 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:13.606190+00:00
+2026-05-06 18:20:14,202 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:14,419 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.813s at 2026-05-07T00:20:14.419193+00:00
+2026-05-06 18:20:24,188 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:24.188464+00:00
+2026-05-06 18:20:24,558 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:24,768 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.580s at 2026-05-07T00:20:24.768332+00:00
+2026-05-06 18:20:31,993 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:31.993128+00:00
+2026-05-06 18:20:32,461 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:32,660 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.667s at 2026-05-07T00:20:32.660620+00:00
+2026-05-06 18:20:39,799 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:39.799176+00:00
+2026-05-06 18:20:40,213 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:40,415 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.616s at 2026-05-07T00:20:40.415329+00:00
+2026-05-06 18:20:48,557 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:48.557775+00:00
+2026-05-06 18:20:48,957 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:49,152 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.594s at 2026-05-07T00:20:49.152442+00:00
+2026-05-06 18:20:51,499 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:51.499668+00:00
+2026-05-06 18:20:51,887 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:52,080 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.581s at 2026-05-07T00:20:52.080875+00:00
+2026-05-06 18:20:58,550 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:20:58.550802+00:00
+2026-05-06 18:20:58,974 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:20:59,172 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.621s at 2026-05-07T00:20:59.172097+00:00
+2026-05-06 18:21:05,475 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:21:05.475735+00:00
+2026-05-06 18:21:05,968 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:21:06,170 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.695s at 2026-05-07T00:21:06.170299+00:00
+2026-05-06 18:21:58,411 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:21:58.411200+00:00
+2026-05-06 18:21:58,922 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:21:59,122 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.711s at 2026-05-07T00:21:59.122602+00:00
+2026-05-06 18:22:03,353 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:03.353237+00:00
+2026-05-06 18:22:03,666 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:22:03,899 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.546s at 2026-05-07T00:22:03.899330+00:00
+2026-05-06 18:22:18,857 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:18.857782+00:00
+2026-05-06 18:22:19,152 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:22:19,352 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.495s at 2026-05-07T00:22:19.351744+00:00
+2026-05-06 18:22:33,242 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:33.241502+00:00
+2026-05-06 18:22:33,608 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:22:33,808 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.566s at 2026-05-07T00:22:33.808058+00:00
+2026-05-06 18:22:46,303 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:46.303027+00:00
+2026-05-06 18:22:46,613 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:22:46,820 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.517s at 2026-05-07T00:22:46.820104+00:00
+2026-05-06 18:22:53,994 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:22:53.994710+00:00
+2026-05-06 18:22:54,335 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:22:54,531 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.538s at 2026-05-07T00:22:54.531877+00:00
+2026-05-06 18:23:03,058 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:23:03.058568+00:00
+2026-05-06 18:23:03,713 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:23:03,917 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.859s at 2026-05-07T00:23:03.917765+00:00
+2026-05-06 18:23:13,406 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:23:13.406391+00:00
+2026-05-06 18:23:13,942 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
+2026-05-06 18:23:13,967 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:23:14,176 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.771s at 2026-05-07T00:23:14.176983+00:00
+2026-05-06 18:23:56,519 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:23:56.519124+00:00
+2026-05-06 18:23:57,096 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:23:57,280 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.761s at 2026-05-07T00:23:57.280365+00:00
+2026-05-06 18:30:22,767 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-06 18:30:22,786 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 18:30:23,875 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-06 18:30:23,890 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 18:30:40,305 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-06 18:30:40,318 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 18:30:47,397 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:30:47.397798+00:00
+2026-05-06 18:30:47,398 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] preparing_image progress=12
+2026-05-06 18:30:47,494 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
+2026-05-06 18:30:47,495 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 18:30:50,214 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:30:52,639 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:30:52,643 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:30:52,644 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 18:30:53,251 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:30:55,145 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 18:30:55,156 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/ecb9300c-1e9f-4a3b-9c4a-3263e97e0a30 "HTTP/1.1 200 OK"
+2026-05-06 18:30:57,506 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:30:57,568 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:30:59,968 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/b5d0cc5e-3739-47c1-96d5-e2849a4fe991 "HTTP/1.1 200 OK"
+2026-05-06 18:30:59,972 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 18:31:02,313 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 18:31:04,749 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=b5d0cc5e-3739-47c1-96d5-e2849a4fe991 "HTTP/1.1 200 OK"
+2026-05-06 18:33:25,005 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\bdc55057e453f1e4793eccb7f3297d66322074e960cb173c3fcf63268faa1561\image.webp "HTTP/1.1 200 OK"
+2026-05-06 18:33:25,027 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🏙️ Fachada / Exterior motor=SAM Auto (Exteriores - Sin Prompts) mask_count=95
+2026-05-06 18:33:25,028 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] saving_masks progress=92
+2026-05-06 18:33:25,352 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] segments_meta saved (93 segments)
+2026-05-06 18:33:25,353 INFO backend.segmentation: [JOB 37f6fc15168b48aea5bf3d353e1cd8bc] done mask_count=95
+2026-05-06 18:33:25,353 INFO backend.segmentation: [UPLOAD_BG] DONE 157.955s at 2026-05-07T00:33:25.353379+00:00
+2026-05-06 18:33:25,354 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 18:33:32,815 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:32.815130+00:00
+2026-05-06 18:33:33,172 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:33:33,554 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.739s at 2026-05-07T00:33:33.554031+00:00
+2026-05-06 18:33:36,147 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:36.147891+00:00
+2026-05-06 18:33:36,589 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
+2026-05-06 18:33:36,616 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:33:36,847 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.700s at 2026-05-07T00:33:36.847452+00:00
+2026-05-06 18:33:39,658 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:39.658618+00:00
+2026-05-06 18:33:40,173 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
+2026-05-06 18:33:40,198 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:33:40,445 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.787s at 2026-05-07T00:33:40.445326+00:00
+2026-05-06 18:33:42,787 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:42.787102+00:00
+2026-05-06 18:33:43,295 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:33:43,530 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.744s at 2026-05-07T00:33:43.530960+00:00
+2026-05-06 18:33:44,949 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:44.949548+00:00
+2026-05-06 18:33:45,490 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:33:45,716 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.768s at 2026-05-07T00:33:45.716664+00:00
+2026-05-06 18:33:53,000 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:33:53.000130+00:00
+2026-05-06 18:33:53,538 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:33:53,781 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.781s at 2026-05-07T00:33:53.781571+00:00
+2026-05-06 18:34:12,078 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:12.078767+00:00
+2026-05-06 18:34:12,759 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:34:12,996 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.918s at 2026-05-07T00:34:12.996206+00:00
+2026-05-06 18:34:25,880 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:25.880027+00:00
+2026-05-06 18:34:26,401 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:34:26,649 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.770s at 2026-05-07T00:34:26.649818+00:00
+2026-05-06 18:34:33,573 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:33.572267+00:00
+2026-05-06 18:34:33,888 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:34:34,124 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.551s at 2026-05-07T00:34:34.124108+00:00
+2026-05-06 18:34:38,104 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:38.104579+00:00
+2026-05-06 18:34:38,547 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:34:38,781 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.677s at 2026-05-07T00:34:38.781767+00:00
+2026-05-06 18:34:43,958 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:43.958224+00:00
+2026-05-06 18:34:44,396 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
+2026-05-06 18:34:44,422 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:34:44,657 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.700s at 2026-05-07T00:34:44.657499+00:00
+2026-05-06 18:34:50,537 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:50.537840+00:00
+2026-05-06 18:34:50,991 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.50, h_ratio=1.82)
+2026-05-06 18:34:51,019 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:34:51,263 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.725s at 2026-05-07T00:34:51.263124+00:00
+2026-05-06 18:34:56,797 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:34:56.797730+00:00
+2026-05-06 18:34:57,208 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:34:57,462 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.666s at 2026-05-07T00:34:57.462972+00:00
+2026-05-06 18:35:00,689 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:35:00.689108+00:00
+2026-05-06 18:35:01,074 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:35:01,329 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.641s at 2026-05-07T00:35:01.329788+00:00
+2026-05-06 18:35:02,869 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:35:02.869035+00:00
+2026-05-06 18:35:03,292 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.45)
+2026-05-06 18:35:03,313 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:35:03,548 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.679s at 2026-05-07T00:35:03.548094+00:00
+2026-05-06 18:35:09,675 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:35:09.675245+00:00
+2026-05-06 18:35:10,176 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.21, h_ratio=1.01)
+2026-05-06 18:35:10,210 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:35:10,449 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.775s at 2026-05-07T00:35:10.449920+00:00
+2026-05-06 18:35:57,783 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:35:57.783409+00:00
+2026-05-06 18:35:58,342 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
+2026-05-06 18:35:58,368 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:35:58,597 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.814s at 2026-05-07T00:35:58.597593+00:00
+2026-05-06 18:36:05,048 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:05.048300+00:00
+2026-05-06 18:36:05,424 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
+2026-05-06 18:36:05,446 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:36:05,683 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.635s at 2026-05-07T00:36:05.683990+00:00
+2026-05-06 18:36:09,348 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:09.348934+00:00
+2026-05-06 18:36:09,689 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:36:09,939 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.591s at 2026-05-07T00:36:09.939262+00:00
+2026-05-06 18:36:11,515 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:11.515772+00:00
+2026-05-06 18:36:11,864 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:36:12,115 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.600s at 2026-05-07T00:36:12.115522+00:00
+2026-05-06 18:36:14,119 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:14.119433+00:00
+2026-05-06 18:36:14,467 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:36:14,703 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.583s at 2026-05-07T00:36:14.703339+00:00
+2026-05-06 18:36:17,955 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:17.955143+00:00
+2026-05-06 18:36:18,323 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.50, h_ratio=1.82)
+2026-05-06 18:36:18,346 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:36:18,587 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.632s at 2026-05-07T00:36:18.587038+00:00
+2026-05-06 18:36:29,722 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:29.722755+00:00
+2026-05-06 18:36:30,041 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.21, h_ratio=1.01)
+2026-05-06 18:36:30,075 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:36:30,316 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.595s at 2026-05-07T00:36:30.316931+00:00
+2026-05-06 18:36:55,258 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:55.258246+00:00
+2026-05-06 18:36:55,839 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.21, h_ratio=1.01)
+2026-05-06 18:36:55,875 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:36:56,125 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.867s at 2026-05-07T00:36:56.124977+00:00
+2026-05-06 18:36:59,138 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:36:59.138564+00:00
+2026-05-06 18:36:59,725 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.45)
+2026-05-06 18:36:59,750 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-06 18:36:59,984 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.846s at 2026-05-07T00:36:59.984763+00:00
+2026-05-06 18:37:16,745 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:37:16.745961+00:00
+2026-05-06 18:37:16,745 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] preparing_image progress=12
+2026-05-06 18:37:16,797 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] segmenting_with_sam2 progress=30 estimated_seconds=94.01599999999999
+2026-05-06 18:37:16,798 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 18:37:19,202 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:37:21,617 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:37:21,620 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:37:21,623 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 18:37:21,755 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:37:24,077 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/09adaa1b-fd4b-4053-96e7-e3e0b7cb26b3 "HTTP/1.1 200 OK"
+2026-05-06 18:37:24,081 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 18:37:26,501 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:37:26,560 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:37:28,941 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/450ca127-bb6f-4e37-b304-d51b440a9dbd "HTTP/1.1 200 OK"
+2026-05-06 18:37:28,947 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 18:37:31,443 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 18:37:33,986 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=450ca127-bb6f-4e37-b304-d51b440a9dbd "HTTP/1.1 200 OK"
+2026-05-06 18:39:54,826 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\8fee556ace9ab88dababff8e3183ddda34f5b57dd22cd0c9c4270241d97fe1a7\image.webp "HTTP/1.1 200 OK"
+2026-05-06 18:39:54,847 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🏙️ Fachada / Exterior motor=SAM Auto (Exteriores - Sin Prompts) mask_count=91
+2026-05-06 18:39:54,847 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] saving_masks progress=92
+2026-05-06 18:39:55,291 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] segments_meta saved (90 segments)
+2026-05-06 18:39:55,291 INFO backend.segmentation: [JOB 884dbcda1cef4f96803a35b3a89b9c60] done mask_count=91
+2026-05-06 18:39:55,292 INFO backend.segmentation: [UPLOAD_BG] DONE 158.546s at 2026-05-07T00:39:55.291225+00:00
+2026-05-06 18:39:55,292 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 18:40:28,080 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:28.080549+00:00
+2026-05-06 18:40:28,641 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-06 18:40:29,060 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.980s at 2026-05-07T00:40:29.060020+00:00
+2026-05-06 18:40:37,726 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:37.726439+00:00
+2026-05-06 18:40:38,269 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-06 18:40:38,656 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.930s at 2026-05-07T00:40:38.656587+00:00
+2026-05-06 18:40:41,361 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:41.361471+00:00
+2026-05-06 18:40:41,870 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-06 18:40:42,256 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.895s at 2026-05-07T00:40:42.255570+00:00
+2026-05-06 18:40:50,492 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:50.492837+00:00
+2026-05-06 18:40:51,018 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-06 18:40:51,365 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.872s at 2026-05-07T00:40:51.364239+00:00
+2026-05-06 18:40:53,275 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:40:53.275769+00:00
+2026-05-06 18:40:53,826 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-06 18:40:54,179 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.905s at 2026-05-07T00:40:54.179973+00:00
+2026-05-06 18:41:02,123 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:41:02.123703+00:00
+2026-05-06 18:41:02,497 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-06 18:41:02,880 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.756s at 2026-05-07T00:41:02.880196+00:00
+2026-05-06 18:41:13,602 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:41:13.602484+00:00
+2026-05-06 18:41:14,055 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-06 18:41:14,428 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.827s at 2026-05-07T00:41:14.428892+00:00
+2026-05-06 18:41:19,676 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:41:19.676717+00:00
+2026-05-06 18:41:20,113 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-06 18:41:20,484 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.808s at 2026-05-07T00:41:20.484587+00:00
+2026-05-06 18:41:28,383 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:41:28.383560+00:00
+2026-05-06 18:41:28,729 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-06 18:41:29,136 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.752s at 2026-05-07T00:41:29.136269+00:00
+2026-05-06 18:42:20,651 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:42:20.651898+00:00
+2026-05-06 18:42:20,652 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] preparing_image progress=12
+2026-05-06 18:42:20,720 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-06 18:42:20,722 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 18:42:23,169 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:42:25,513 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:42:25,518 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:42:25,523 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 18:42:25,648 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:42:27,979 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 18:42:28,011 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/eff4d6f4-a526-4e3c-885b-21716e034b5b "HTTP/1.1 200 OK"
+2026-05-06 18:42:30,320 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:42:30,384 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:42:32,775 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/bb6c3136-6f1c-4623-bf35-86865beea318 "HTTP/1.1 200 OK"
+2026-05-06 18:42:32,825 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 18:42:35,212 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 18:42:37,701 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=bb6c3136-6f1c-4623-bf35-86865beea318 "HTTP/1.1 200 OK"
+2026-05-06 18:43:12,742 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\bd5cc89cdf220f59a58e54c17de42ccd2fe478787be6fafda37778eaf1d6f8c0\image.webp "HTTP/1.1 200 OK"
+2026-05-06 18:43:12,768 INFO services.gradio_client_service: Gradio Space segmentation: entorno=🛋️ Interiores (Sala / Cuartos) motor=SegFormer (SegFormer ADE20K+ DINO) + SAM 2.1 mask_count=15
+2026-05-06 18:43:12,768 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] saving_masks progress=92
+2026-05-06 18:43:12,827 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] segments_meta saved (9 segments)
+2026-05-06 18:43:12,828 INFO backend.segmentation: [JOB f7c2c35798df4443b6954b52ae0e50c7] done mask_count=15
+2026-05-06 18:43:12,828 INFO backend.segmentation: [UPLOAD_BG] DONE 52.177s at 2026-05-07T00:43:12.828557+00:00
+2026-05-06 18:43:12,829 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 18:43:24,334 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:43:24.334962+00:00
+2026-05-06 18:43:24,892 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.41.58.jpg
+2026-05-06 18:43:25,127 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.792s at 2026-05-07T00:43:25.127393+00:00
+2026-05-06 18:45:52,139 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:45:52.139300+00:00
+2026-05-06 18:45:52,631 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
+2026-05-06 18:45:52,652 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.41.58.jpg
+2026-05-06 18:45:52,934 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.795s at 2026-05-07T00:45:52.934786+00:00
+2026-05-06 18:48:05,742 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:48:05.742257+00:00
+2026-05-06 18:48:05,742 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] preparing_image progress=12
+2026-05-06 18:48:05,805 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-06 18:48:05,806 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 18:48:08,161 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 18:48:10,524 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:48:10,528 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:48:10,529 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 18:48:10,657 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:48:12,980 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/7be43e9c-5bea-422d-bb06-60720d9880bf "HTTP/1.1 200 OK"
+2026-05-06 18:48:12,981 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 18:48:15,268 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:48:15,340 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:48:17,721 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/562af56b-498c-4c62-9020-b784b3cd3643 "HTTP/1.1 200 OK"
+2026-05-06 18:48:17,756 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 18:48:20,089 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 18:48:22,469 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=562af56b-498c-4c62-9020-b784b3cd3643 "HTTP/1.1 200 OK"
+2026-05-06 18:50:33,287 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\307e144a6a358b2b31461825d5a83d98d89d0a4426bbff036b53a58abbce6a7f\image.webp "HTTP/1.1 200 OK"
+2026-05-06 18:50:33,299 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=75
+2026-05-06 18:50:33,301 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] saving_masks progress=92
+2026-05-06 18:50:33,531 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] segments_meta saved (65 segments)
+2026-05-06 18:50:33,534 INFO backend.segmentation: [JOB 6b7b7b29836840008fe1b69188169fdd] done mask_count=75
+2026-05-06 18:50:33,534 INFO backend.segmentation: [UPLOAD_BG] DONE 147.793s at 2026-05-07T00:50:33.534228+00:00
+2026-05-06 18:50:33,535 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 18:50:43,317 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:50:43.317662+00:00
+2026-05-06 18:50:43,744 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.18, h_ratio=287.00)
+2026-05-06 18:50:43,761 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:50:43,971 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.654s at 2026-05-07T00:50:43.971226+00:00
+2026-05-06 18:50:48,879 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:50:48.879893+00:00
+2026-05-06 18:50:49,294 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:50:49,529 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.649s at 2026-05-07T00:50:49.529626+00:00
+2026-05-06 18:50:57,857 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:50:57.857319+00:00
+2026-05-06 18:50:58,384 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=1.27)
+2026-05-06 18:50:58,407 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:50:58,621 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.764s at 2026-05-07T00:50:58.621573+00:00
+2026-05-06 18:51:06,144 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:51:06.144106+00:00
+2026-05-06 18:51:06,633 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.25, h_ratio=1.00)
+2026-05-06 18:51:06,651 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:51:06,863 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.719s at 2026-05-07T00:51:06.863196+00:00
+2026-05-06 18:51:15,682 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:51:15.682186+00:00
+2026-05-06 18:51:16,277 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
+2026-05-06 18:51:16,298 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:51:16,515 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.833s at 2026-05-07T00:51:16.515186+00:00
+2026-05-06 18:51:19,654 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:51:19.654232+00:00
+2026-05-06 18:51:19,971 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
+2026-05-06 18:51:19,990 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:51:20,208 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.555s at 2026-05-07T00:51:20.208584+00:00
+2026-05-06 18:52:00,456 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:00.456384+00:00
+2026-05-06 18:52:00,996 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=292.55)
+2026-05-06 18:52:01,022 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:52:01,244 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.788s at 2026-05-07T00:52:01.244355+00:00
+2026-05-06 18:52:26,614 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:26.614595+00:00
+2026-05-06 18:52:27,072 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
+2026-05-06 18:52:27,091 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:52:27,309 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.695s at 2026-05-07T00:52:27.309474+00:00
+2026-05-06 18:52:31,418 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:31.418579+00:00
+2026-05-06 18:52:31,917 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
+2026-05-06 18:52:31,937 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:52:32,167 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.748s at 2026-05-07T00:52:32.167442+00:00
+2026-05-06 18:52:36,908 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:36.908697+00:00
+2026-05-06 18:52:37,340 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.00 < 0.35, skip perspective)
+2026-05-06 18:52:37,360 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:52:37,571 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.663s at 2026-05-07T00:52:37.571758+00:00
+2026-05-06 18:52:42,394 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:52:42.394838+00:00
+2026-05-06 18:52:42,800 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:52:43,012 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.618s at 2026-05-07T00:52:43.012733+00:00
+2026-05-06 18:53:17,599 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:17.599012+00:00
+2026-05-06 18:53:18,767 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:53:19,517 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.918s at 2026-05-07T00:53:19.517003+00:00
+2026-05-06 18:53:20,941 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:20.941029+00:00
+2026-05-06 18:53:22,268 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.18, h_ratio=287.00)
+2026-05-06 18:53:22,309 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:53:22,958 INFO backend.segmentation: [APPLY_TEXTURE] DONE 2.017s at 2026-05-07T00:53:22.958657+00:00
+2026-05-06 18:53:26,815 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:26.815426+00:00
+2026-05-06 18:53:27,767 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.18, h_ratio=287.00)
+2026-05-06 18:53:27,822 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:53:28,496 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.681s at 2026-05-07T00:53:28.496136+00:00
+2026-05-06 18:53:29,211 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:29.211502+00:00
+2026-05-06 18:53:30,092 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:53:30,714 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.503s at 2026-05-07T00:53:30.714065+00:00
+2026-05-06 18:53:43,274 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T00:53:43.274502+00:00
+2026-05-06 18:53:44,185 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.80)
+2026-05-06 18:53:44,258 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 18:53:44,915 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.642s at 2026-05-07T00:53:44.915473+00:00
+2026-05-06 18:56:42,127 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-06 18:56:42,164 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 18:56:55,483 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T00:56:55.483048+00:00
+2026-05-06 18:56:55,487 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] preparing_image progress=12
+2026-05-06 18:56:55,916 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-06 18:56:55,930 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-06 18:57:00,068 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-06 18:57:01,629 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:57:01,716 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 18:57:01,731 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 18:57:02,949 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:57:03,037 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/a5e246b1-7256-4e47-bd59-4324d860981a "HTTP/1.1 200 OK"
+2026-05-06 18:57:04,851 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 18:57:08,278 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 18:57:08,445 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 18:57:11,795 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/80c98c2b-f464-4c63-be57-df896c3ca445 "HTTP/1.1 200 OK"
+2026-05-06 18:57:11,848 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 18:57:14,425 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 18:57:16,934 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=80c98c2b-f464-4c63-be57-df896c3ca445 "HTTP/1.1 200 OK"
+2026-05-06 18:59:19,174 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\307e144a6a358b2b31461825d5a83d98d89d0a4426bbff036b53a58abbce6a7f\image.webp "HTTP/1.1 200 OK"
+2026-05-06 18:59:19,199 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=75
+2026-05-06 18:59:19,201 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] saving_masks progress=92
+2026-05-06 18:59:19,479 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] segments_meta saved (65 segments)
+2026-05-06 18:59:19,480 INFO backend.segmentation: [JOB b2b162abddce42c7a37266a35a44b3e4] done mask_count=75
+2026-05-06 18:59:19,481 INFO backend.segmentation: [UPLOAD_BG] DONE 143.997s at 2026-05-07T00:59:19.481114+00:00
+2026-05-06 18:59:19,481 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:00:44,615 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-06 19:00:44,631 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 19:00:54,117 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:00:54.117066+00:00
+2026-05-06 19:00:54,118 INFO backend.segmentation: [JOB 857272f2f2794d61a8320ba9fc0a0b9c] preparing_image progress=12
+2026-05-06 19:00:54,227 INFO backend.segmentation: [JOB 857272f2f2794d61a8320ba9fc0a0b9c] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-06 19:00:54,228 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-06 19:00:55,352 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-06 19:00:55,962 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:00:56,025 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:00:56,027 ERROR backend.segmentation: [JOB 857272f2f2794d61a8320ba9fc0a0b9c] failed: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
+    label_map, mask_count = segment_via_gradio_sync(image_path)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 87, in segment_via_gradio_sync
+    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
+RuntimeError: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
+2026-05-06 19:00:56,028 INFO backend.segmentation: [UPLOAD_BG] DONE 1.912s at 2026-05-07T01:00:56.028803+00:00
+2026-05-06 19:00:56,029 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:00:56,598 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:00:56,674 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/4209bbfb-31fd-49ce-8bfa-3bd088857ca8 "HTTP/1.1 200 OK"
+2026-05-06 19:01:51,403 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:01:51.403342+00:00
+2026-05-06 19:01:51,403 INFO backend.segmentation: [JOB 3767a577a5df43449aa13600c7a14d0c] preparing_image progress=12
+2026-05-06 19:01:51,499 INFO backend.segmentation: [JOB 3767a577a5df43449aa13600c7a14d0c] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-06 19:01:51,499 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-06 19:01:52,190 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-06 19:01:52,799 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:01:52,856 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:01:52,857 ERROR backend.segmentation: [JOB 3767a577a5df43449aa13600c7a14d0c] failed: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
+    label_map, mask_count = segment_via_gradio_sync(image_path)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 87, in segment_via_gradio_sync
+    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
+RuntimeError: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
+2026-05-06 19:01:52,858 INFO backend.segmentation: [UPLOAD_BG] DONE 1.455s at 2026-05-07T01:01:52.858105+00:00
+2026-05-06 19:01:52,858 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:01:53,023 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:01:53,494 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/2c3065a9-d718-45a7-8b87-980f332c885e "HTTP/1.1 200 OK"
+2026-05-06 19:17:22,918 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:17:22.918521+00:00
+2026-05-06 19:17:22,918 INFO backend.segmentation: [JOB 2f51a6c8a71e4a1abde690771af923c8] preparing_image progress=12
+2026-05-06 19:17:23,012 INFO backend.segmentation: [JOB 2f51a6c8a71e4a1abde690771af923c8] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-06 19:17:23,013 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-06 19:17:23,790 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-06 19:17:24,541 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:17:24,595 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:17:24,596 ERROR backend.segmentation: [JOB 2f51a6c8a71e4a1abde690771af923c8] failed: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 137, in run_upload_job
+    label_map, mask_count = segment_via_gradio_sync(image_path)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 87, in segment_via_gradio_sync
+    raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
+RuntimeError: GPU Gradio Space failed and no CPU fallback configured. Error: Cannot find a function with `api_name`: /segment.
+2026-05-06 19:17:24,598 INFO backend.segmentation: [UPLOAD_BG] DONE 1.680s at 2026-05-07T01:17:24.598238+00:00
+2026-05-06 19:17:24,599 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:17:24,970 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:17:25,584 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/0dc57ee9-5e05-4959-abe6-f013266fa198 "HTTP/1.1 200 OK"
+2026-05-06 19:17:42,518 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-06 19:17:42,533 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 19:17:51,915 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:17:51.915900+00:00
+2026-05-06 19:17:51,915 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] preparing_image progress=12
+2026-05-06 19:17:52,074 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-06 19:17:52,077 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 19:17:55,274 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 19:17:57,503 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:17:57,507 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:17:57,507 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 19:17:57,893 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:17:59,796 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/f7a98d0a-9306-4dbc-93b7-601ff79c950e "HTTP/1.1 200 OK"
+2026-05-06 19:17:59,799 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 19:18:02,032 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:18:02,104 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:18:04,304 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/2d410380-be25-4691-8948-df224948856b "HTTP/1.1 200 OK"
+2026-05-06 19:18:04,308 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 19:18:06,507 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 19:18:08,705 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=2d410380-be25-4691-8948-df224948856b "HTTP/1.1 200 OK"
+2026-05-06 19:20:30,315 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\ba6745bca4b9348c165f22fc4ea78e92894e852d9a17a054a2f8f302e7eede49\image.webp "HTTP/1.1 200 OK"
+2026-05-06 19:20:30,336 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=108
+2026-05-06 19:20:30,342 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] saving_masks progress=92
+2026-05-06 19:20:30,735 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] segments_meta saved (94 segments)
+2026-05-06 19:20:30,736 INFO backend.segmentation: [JOB 63e59d4c364544d9a7e673575d6476fa] done mask_count=108
+2026-05-06 19:20:30,736 INFO backend.segmentation: [UPLOAD_BG] DONE 158.821s at 2026-05-07T01:20:30.736356+00:00
+2026-05-06 19:20:30,736 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:20:54,598 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:20:54.598398+00:00
+2026-05-06 19:20:55,454 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.22, h_ratio=1.42)
+2026-05-06 19:20:55,479 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:20:55,852 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.253s at 2026-05-07T01:20:55.852286+00:00
+2026-05-06 19:21:02,878 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:02.878905+00:00
+2026-05-06 19:21:03,409 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.03)
+2026-05-06 19:21:03,430 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:21:03,652 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.774s at 2026-05-07T01:21:03.652782+00:00
+2026-05-06 19:21:04,556 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:04.556252+00:00
+2026-05-06 19:21:05,073 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:21:05,304 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.749s at 2026-05-07T01:21:05.304889+00:00
+2026-05-06 19:21:09,382 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:09.382363+00:00
+2026-05-06 19:21:09,876 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:21:10,099 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.717s at 2026-05-07T01:21:10.099363+00:00
+2026-05-06 19:21:12,168 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:12.168998+00:00
+2026-05-06 19:21:12,676 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:21:12,902 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.734s at 2026-05-07T01:21:12.902123+00:00
+2026-05-06 19:21:17,676 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:17.676155+00:00
+2026-05-06 19:21:18,186 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:21:18,406 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.730s at 2026-05-07T01:21:18.406221+00:00
+2026-05-06 19:21:28,033 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:28.033139+00:00
+2026-05-06 19:21:28,602 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.04, h_ratio=30.15)
+2026-05-06 19:21:28,621 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:21:28,847 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.815s at 2026-05-07T01:21:28.847576+00:00
+2026-05-06 19:21:37,759 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:37.759732+00:00
+2026-05-06 19:21:38,294 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.08, h_ratio=2.31)
+2026-05-06 19:21:38,324 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:21:38,542 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.783s at 2026-05-07T01:21:38.542862+00:00
+2026-05-06 19:21:45,517 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:45.517095+00:00
+2026-05-06 19:21:45,886 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.45, h_ratio=1.00)
+2026-05-06 19:21:45,904 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:21:46,127 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.610s at 2026-05-07T01:21:46.127155+00:00
+2026-05-06 19:21:47,910 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:21:47.910379+00:00
+2026-05-06 19:21:48,240 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.03)
+2026-05-06 19:21:48,258 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:21:48,550 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.640s at 2026-05-07T01:21:48.550311+00:00
+2026-05-06 19:22:01,490 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:01.490043+00:00
+2026-05-06 19:22:01,800 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.40, h_ratio=1.19)
+2026-05-06 19:22:01,820 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:22:02,038 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.549s at 2026-05-07T01:22:02.038685+00:00
+2026-05-06 19:22:14,676 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:14.676095+00:00
+2026-05-06 19:22:14,981 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.24)
+2026-05-06 19:22:15,000 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:22:15,217 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.542s at 2026-05-07T01:22:15.217076+00:00
+2026-05-06 19:22:18,393 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:18.393596+00:00
+2026-05-06 19:22:18,727 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=3.19, h_ratio=1.08)
+2026-05-06 19:22:18,748 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:22:18,967 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.573s at 2026-05-07T01:22:18.967471+00:00
+2026-05-06 19:22:20,453 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:20.453051+00:00
+2026-05-06 19:22:20,787 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.25, h_ratio=1.00)
+2026-05-06 19:22:20,807 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:22:21,031 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.578s at 2026-05-07T01:22:21.031223+00:00
+2026-05-06 19:22:21,815 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:22:21.815779+00:00
+2026-05-06 19:22:22,122 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:22:22,328 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.512s at 2026-05-07T01:22:22.328994+00:00
+2026-05-06 19:23:32,211 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:23:32.211857+00:00
+2026-05-06 19:23:32,509 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:23:32,730 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.518s at 2026-05-07T01:23:32.730152+00:00
+2026-05-06 19:23:38,227 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:23:38.227849+00:00
+2026-05-06 19:23:38,534 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:23:38,859 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.632s at 2026-05-07T01:23:38.859962+00:00
+2026-05-06 19:26:19,159 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:26:19.158670+00:00
+2026-05-06 19:26:19,159 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] preparing_image progress=12
+2026-05-06 19:26:19,236 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-05-06 19:26:19,237 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 19:26:21,653 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 19:26:24,033 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:26:24,036 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:26:24,038 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 19:26:24,154 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:26:25,313 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:26:25.313791+00:00
+2026-05-06 19:26:25,314 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] preparing_image progress=12
+2026-05-06 19:26:25,380 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-06 19:26:25,382 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 19:26:26,501 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 19:26:26,514 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/253a1026-e06a-44b1-a442-8e6324d90510 "HTTP/1.1 200 OK"
+2026-05-06 19:26:27,773 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 19:26:28,745 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:26:28,804 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:26:29,998 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:26:30,000 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:26:30,000 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 19:26:30,064 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:26:31,044 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/ef93ac7c-1d1e-49c1-a68d-1e312c61dbd6 "HTTP/1.1 200 OK"
+2026-05-06 19:26:31,045 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 19:26:32,302 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/f94b5838-f8e4-404c-b91a-44c18e0fd13d "HTTP/1.1 200 OK"
+2026-05-06 19:26:32,303 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 19:26:33,276 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 19:26:34,511 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:26:34,571 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:26:35,511 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=ef93ac7c-1d1e-49c1-a68d-1e312c61dbd6 "HTTP/1.1 200 OK"
+2026-05-06 19:26:36,930 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/f61335a1-cff8-4529-990e-d2408f346c4b "HTTP/1.1 200 OK"
+2026-05-06 19:26:36,985 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 19:26:39,872 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 19:26:42,392 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=f61335a1-cff8-4529-990e-d2408f346c4b "HTTP/1.1 200 OK"
+2026-05-06 19:28:56,877 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\6ab9a3531b560f214c105197415e0af0532fde83c6bfe58ed1c0313fcd859477\image.webp "HTTP/1.1 200 OK"
+2026-05-06 19:28:56,897 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=131
+2026-05-06 19:28:56,898 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] saving_masks progress=92
+2026-05-06 19:28:57,283 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] segments_meta saved (100 segments)
+2026-05-06 19:28:57,286 INFO backend.segmentation: [JOB 8008bb4df0774cc693f720f155ffe536] done mask_count=131
+2026-05-06 19:28:57,290 INFO backend.segmentation: [UPLOAD_BG] DONE 158.131s at 2026-05-07T01:28:57.289976+00:00
+2026-05-06 19:28:57,290 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:31:09,088 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\0fad9dd5d2167e81275663b268759f254ced3260a00596d8148c4b82b18a447b\image.webp "HTTP/1.1 200 OK"
+2026-05-06 19:31:09,105 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=108
+2026-05-06 19:31:09,106 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] saving_masks progress=92
+2026-05-06 19:31:09,387 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] segments_meta saved (83 segments)
+2026-05-06 19:31:09,388 INFO backend.segmentation: [JOB 7aac21170040414a9aefcbeb3fbff6c5] done mask_count=108
+2026-05-06 19:31:09,389 INFO backend.segmentation: [UPLOAD_BG] DONE 284.075s at 2026-05-07T01:31:09.389195+00:00
+2026-05-06 19:31:09,389 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:31:25,769 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:25.769543+00:00
+2026-05-06 19:31:26,322 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.38, h_ratio=1.21)
+2026-05-06 19:31:26,345 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:31:26,561 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.791s at 2026-05-07T01:31:26.561149+00:00
+2026-05-06 19:31:30,093 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:30.093130+00:00
+2026-05-06 19:31:30,610 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=73.16, h_ratio=1.19)
+2026-05-06 19:31:30,630 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:31:30,852 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.760s at 2026-05-07T01:31:30.852656+00:00
+2026-05-06 19:31:32,510 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:32.510227+00:00
+2026-05-06 19:31:33,024 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:31:33,261 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.751s at 2026-05-07T01:31:33.261864+00:00
+2026-05-06 19:31:34,688 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:34.688411+00:00
+2026-05-06 19:31:35,245 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.82, h_ratio=1.04)
+2026-05-06 19:31:35,273 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:31:35,585 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.897s at 2026-05-07T01:31:35.585466+00:00
+2026-05-06 19:31:37,308 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:37.308846+00:00
+2026-05-06 19:31:37,845 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:31:38,063 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.754s at 2026-05-07T01:31:38.063134+00:00
+2026-05-06 19:31:39,470 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:31:39.470279+00:00
+2026-05-06 19:31:40,021 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.28)
+2026-05-06 19:31:40,041 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:31:40,265 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.795s at 2026-05-07T01:31:40.265221+00:00
+2026-05-06 19:32:07,072 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:32:07.072763+00:00
+2026-05-06 19:32:07,073 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] preparing_image progress=12
+2026-05-06 19:32:07,137 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-05-06 19:32:07,137 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 19:32:09,529 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 19:32:11,885 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:32:11,888 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:32:11,888 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 19:32:12,020 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:32:14,326 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/be75cb37-7b07-4bcc-8b3d-efdee17bbc4a "HTTP/1.1 200 OK"
+2026-05-06 19:32:14,327 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 19:32:16,703 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:32:16,767 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:32:19,164 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/c6911703-f527-40a3-889a-6c77edcd8d21 "HTTP/1.1 200 OK"
+2026-05-06 19:32:19,202 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 19:32:21,606 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 19:32:24,189 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=c6911703-f527-40a3-889a-6c77edcd8d21 "HTTP/1.1 200 OK"
+2026-05-06 19:34:39,587 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\21889eae2fc6a2146ef59d302265bd9c57edff263c81a559c184526108f142d6\image.webp "HTTP/1.1 200 OK"
+2026-05-06 19:34:39,600 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=160
+2026-05-06 19:34:39,601 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] saving_masks progress=92
+2026-05-06 19:34:39,913 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] segments_meta saved (109 segments)
+2026-05-06 19:34:39,916 INFO backend.segmentation: [JOB 28de69b0b9f74b04a79ddc8f1c43f4a5] done mask_count=160
+2026-05-06 19:34:39,916 INFO backend.segmentation: [UPLOAD_BG] DONE 152.844s at 2026-05-07T01:34:39.916411+00:00
+2026-05-06 19:34:39,917 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:34:58,860 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:34:58.860869+00:00
+2026-05-06 19:34:59,384 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=2.09)
+2026-05-06 19:34:59,410 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 19:34:59,597 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.737s at 2026-05-07T01:34:59.597723+00:00
+2026-05-06 19:35:04,315 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:35:04.314184+00:00
+2026-05-06 19:35:04,828 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 19:35:05,031 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.717s at 2026-05-07T01:35:05.031564+00:00
+2026-05-06 19:35:07,195 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:35:07.195100+00:00
+2026-05-06 19:35:07,775 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 19:35:07,959 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.764s at 2026-05-07T01:35:07.959507+00:00
+2026-05-06 19:35:16,717 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:35:16.717055+00:00
+2026-05-06 19:35:17,292 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.12, h_ratio=1.24)
+2026-05-06 19:35:17,313 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 19:35:17,489 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.772s at 2026-05-07T01:35:17.489338+00:00
+2026-05-06 19:35:21,896 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:35:21.896286+00:00
+2026-05-06 19:35:22,460 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=2.25)
+2026-05-06 19:35:22,477 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 19:35:22,652 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.756s at 2026-05-07T01:35:22.652693+00:00
+2026-05-06 19:35:31,661 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:35:31.661603+00:00
+2026-05-06 19:35:31,662 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] preparing_image progress=12
+2026-05-06 19:35:31,730 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-05-06 19:35:31,730 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 19:35:34,148 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 19:35:36,513 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:35:36,516 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:35:36,517 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 19:35:36,647 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:35:38,956 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/bee4b6dd-5fb5-46e5-b79e-991fbe34799b "HTTP/1.1 200 OK"
+2026-05-06 19:35:38,972 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 19:35:41,374 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:35:41,437 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:35:43,849 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 19:35:43,862 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/d8a928aa-2516-473b-85f5-9bf75d1e3f77 "HTTP/1.1 200 OK"
+2026-05-06 19:35:46,265 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 19:35:48,784 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=d8a928aa-2516-473b-85f5-9bf75d1e3f77 "HTTP/1.1 200 OK"
+2026-05-06 19:38:08,031 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\21889eae2fc6a2146ef59d302265bd9c57edff263c81a559c184526108f142d6\image.webp "HTTP/1.1 200 OK"
+2026-05-06 19:38:08,050 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=160
+2026-05-06 19:38:08,051 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] saving_masks progress=92
+2026-05-06 19:38:08,352 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] segments_meta saved (109 segments)
+2026-05-06 19:38:08,353 INFO backend.segmentation: [JOB 97d58fca6faa4b94b385e3762a859555] done mask_count=160
+2026-05-06 19:38:08,353 INFO backend.segmentation: [UPLOAD_BG] DONE 156.692s at 2026-05-07T01:38:08.353974+00:00
+2026-05-06 19:38:08,353 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:38:54,725 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:38:54.725946+00:00
+2026-05-06 19:38:55,301 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 19:38:55,485 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.760s at 2026-05-07T01:38:55.485826+00:00
+2026-05-06 19:39:02,094 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:39:02.094076+00:00
+2026-05-06 19:39:02,676 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 19:39:02,898 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.805s at 2026-05-07T01:39:02.898407+00:00
+2026-05-06 19:39:05,813 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:39:05.813452+00:00
+2026-05-06 19:39:05,813 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] preparing_image progress=12
+2026-05-06 19:39:05,890 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-05-06 19:39:05,891 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-06 19:39:08,294 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-06 19:39:10,647 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:39:10,650 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:39:10,650 INFO services.gradio_client_service: Calling CPU fallback Space: http://localhost:7861
+2026-05-06 19:39:10,769 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:39:13,127 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/4460ecf1-ea82-47e4-a1d6-b5bc3d4c71d2 "HTTP/1.1 200 OK"
+2026-05-06 19:39:13,130 INFO httpx: HTTP Request: GET http://localhost:7861/config "HTTP/1.1 200 OK"
+2026-05-06 19:39:15,535 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:39:15,595 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:39:17,956 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/heartbeat/97643e3a-0304-4e2b-8472-769ee08d3b1b "HTTP/1.1 200 OK"
+2026-05-06 19:39:17,959 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 19:39:20,370 INFO httpx: HTTP Request: POST http://localhost:7861/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 19:39:22,889 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/queue/data?session_hash=97643e3a-0304-4e2b-8472-769ee08d3b1b "HTTP/1.1 200 OK"
+2026-05-06 19:41:28,459 INFO httpx: HTTP Request: GET http://localhost:7861/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\76d9b286b2fcdbd80abdc7e15a0a7f680d3f4fbf2b90ca4d6d6f24bbf1545d1c\image.webp "HTTP/1.1 200 OK"
+2026-05-06 19:41:28,470 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=166
+2026-05-06 19:41:28,471 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] saving_masks progress=92
+2026-05-06 19:41:28,681 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] segments_meta saved (137 segments)
+2026-05-06 19:41:28,681 INFO backend.segmentation: [JOB 90601a35a7a147e784baf2d51c1e45e7] done mask_count=166
+2026-05-06 19:41:28,682 INFO backend.segmentation: [UPLOAD_BG] DONE 142.868s at 2026-05-07T01:41:28.682118+00:00
+2026-05-06 19:41:28,682 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:50:21,809 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-06 19:50:21,823 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-06 19:50:26,378 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T01:50:26.378489+00:00
+2026-05-06 19:50:26,384 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] preparing_image progress=12
+2026-05-06 19:50:26,471 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-06 19:50:26,472 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-06 19:50:27,262 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-06 19:50:27,877 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:50:27,893 WARNING services.gradio_client_service: GPU Space failed (Cannot find a function with `api_name`: /segment.), trying CPU fallback...
+2026-05-06 19:50:27,897 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
+2026-05-06 19:50:28,465 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:50:28,587 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/5aad3e23-2d4a-4ff2-b2d1-2ff407eed648 "HTTP/1.1 200 OK"
+2026-05-06 19:50:28,729 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-06 19:50:29,178 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 19:50:29,318 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 19:50:30,078 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 19:50:30,375 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/bf131e2f-59cc-4bcb-90cf-326d0eed81f6 "HTTP/1.1 200 OK"
+2026-05-06 19:50:30,577 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 19:50:30,996 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=bf131e2f-59cc-4bcb-90cf-326d0eed81f6 "HTTP/1.1 200 OK"
+2026-05-06 19:56:12,792 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/file=/tmp/gradio/ca352ba59707f92cf2713ac194ff5f07119898301b89fe92d0d511d51a9854a3/image.webp "HTTP/1.1 200 OK"
+2026-05-06 19:56:12,902 INFO services.gradio_client_service: Gradio Space segmentation: entorno=auto motor=SAM Auto (Exteriores - Sin Prompts) mask_count=108
+2026-05-06 19:56:12,904 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] saving_masks progress=92
+2026-05-06 19:56:13,248 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] segments_meta saved (94 segments)
+2026-05-06 19:56:13,248 INFO backend.segmentation: [JOB 3731a48e488e4df2831bb7387b531e3c] done mask_count=108
+2026-05-06 19:56:13,248 INFO backend.segmentation: [UPLOAD_BG] DONE 346.870s at 2026-05-07T01:56:13.248662+00:00
+2026-05-06 19:56:13,249 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 19:56:28,190 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:28.190920+00:00
+2026-05-06 19:56:28,586 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.89, h_ratio=1.16)
+2026-05-06 19:56:28,610 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:56:28,946 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.756s at 2026-05-07T01:56:28.946955+00:00
+2026-05-06 19:56:32,308 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:32.308758+00:00
+2026-05-06 19:56:32,636 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:56:32,842 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.534s at 2026-05-07T01:56:32.842046+00:00
+2026-05-06 19:56:38,221 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:38.221694+00:00
+2026-05-06 19:56:38,549 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.45, h_ratio=1.00)
+2026-05-06 19:56:38,582 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:56:38,797 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.576s at 2026-05-07T01:56:38.797605+00:00
+2026-05-06 19:56:40,976 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:40.976482+00:00
+2026-05-06 19:56:41,307 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.03)
+2026-05-06 19:56:41,347 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:56:41,596 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.620s at 2026-05-07T01:56:41.596887+00:00
+2026-05-06 19:56:45,053 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:45.053373+00:00
+2026-05-06 19:56:45,558 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:56:45,750 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.697s at 2026-05-07T01:56:45.750699+00:00
+2026-05-06 19:56:48,758 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:48.757132+00:00
+2026-05-06 19:56:49,268 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.08, h_ratio=2.31)
+2026-05-06 19:56:49,292 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:56:49,508 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.751s at 2026-05-07T01:56:49.508898+00:00
+2026-05-06 19:56:53,597 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T01:56:53.597538+00:00
+2026-05-06 19:56:54,195 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.45, h_ratio=1.00)
+2026-05-06 19:56:54,219 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-06 19:56:54,438 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.841s at 2026-05-07T01:56:54.438299+00:00
+2026-05-06 20:00:21,372 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T02:00:21.372294+00:00
+2026-05-06 20:00:21,372 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] preparing_image progress=12
+2026-05-06 20:00:21,437 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-05-06 20:00:21,437 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-06 20:00:22,134 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-06 20:00:22,726 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-06 20:00:22,915 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-06 20:00:23,461 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/c7959aba-7eb6-4ecb-81ad-712329ac5c7c "HTTP/1.1 200 OK"
+2026-05-06 20:00:23,560 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-06 20:00:24,012 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-06 20:00:24,861 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=c7959aba-7eb6-4ecb-81ad-712329ac5c7c "HTTP/1.1 200 OK"
+2026-05-06 20:00:42,409 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/b16694b4215c6ddd7ab507195e91a516ff5142807df0ec7e847eb878eb7c1ab3/image.webp "HTTP/1.1 200 OK"
+2026-05-06 20:00:42,518 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=131
+2026-05-06 20:00:42,519 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] saving_masks progress=92
+2026-05-06 20:00:42,727 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] segments_meta saved (114 segments)
+2026-05-06 20:00:42,727 INFO backend.segmentation: [JOB 9dd987f4caec430e9a186637a9178708] done mask_count=131
+2026-05-06 20:00:42,727 INFO backend.segmentation: [UPLOAD_BG] DONE 21.356s at 2026-05-07T02:00:42.727446+00:00
+2026-05-06 20:00:42,728 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-06 20:17:14,645 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:14.645451+00:00
+2026-05-06 20:17:15,135 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=1.09)
+2026-05-06 20:17:15,152 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 20:17:15,329 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.684s at 2026-05-07T02:17:15.329979+00:00
+2026-05-06 20:17:15,339 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:15.339985+00:00
+2026-05-06 20:17:15,656 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=1.09)
+2026-05-06 20:17:15,678 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 20:17:15,875 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.535s at 2026-05-07T02:17:15.875096+00:00
+2026-05-06 20:17:34,601 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:34.601321+00:00
+2026-05-06 20:17:34,920 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 20:17:35,110 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.510s at 2026-05-07T02:17:35.110889+00:00
+2026-05-06 20:17:42,322 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:42.322700+00:00
+2026-05-06 20:17:42,821 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 20:17:42,999 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.677s at 2026-05-07T02:17:42.998640+00:00
+2026-05-06 20:17:46,209 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T02:17:46.209208+00:00
+2026-05-06 20:17:46,792 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=1.09)
+2026-05-06 20:17:46,811 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-06 20:17:46,990 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.781s at 2026-05-07T02:17:46.990848+00:00
+2026-05-07 12:51:24,606 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 12:51:24,620 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-07 12:51:38,487 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T18:51:38.487778+00:00
+2026-05-07 12:51:38,488 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] preparing_image progress=12
+2026-05-07 12:51:38,722 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 12:51:38,722 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 12:51:57,921 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 12:51:58,597 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 12:51:59,277 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 12:51:59,382 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/94b31a0d-c4b3-4776-9bf3-feb7cfb2deb5 "HTTP/1.1 200 OK"
+2026-05-07 12:51:59,569 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 12:52:00,104 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 12:52:00,784 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=94b31a0d-c4b3-4776-9bf3-feb7cfb2deb5 "HTTP/1.1 200 OK"
+2026-05-07 12:52:21,780 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/58f73381cbe3266caa6d35a2c12cb77e720345122d5cf9f7cdb96e041ceca7c9/image.webp "HTTP/1.1 200 OK"
+2026-05-07 12:52:21,889 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=108
+2026-05-07 12:52:21,890 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] saving_masks progress=92
+2026-05-07 12:52:22,192 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] segments_meta saved (94 segments)
+2026-05-07 12:52:22,192 INFO backend.segmentation: [JOB 021594e26fe54ec19990002de5a49e1e] done mask_count=108
+2026-05-07 12:52:22,192 INFO backend.segmentation: [UPLOAD_BG] DONE 43.706s at 2026-05-07T18:52:22.192480+00:00
+2026-05-07 12:52:22,193 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 12:56:10,928 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T18:56:10.928142+00:00
+2026-05-07 12:56:10,929 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] preparing_image progress=12
+2026-05-07 12:56:10,997 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 12:56:10,997 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 12:56:11,625 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 12:56:12,229 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 12:56:12,412 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 12:56:12,966 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/ed1495a1-4a2c-4fab-a409-975c2768b89c "HTTP/1.1 200 OK"
+2026-05-07 12:56:13,063 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 12:56:13,579 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 12:56:14,152 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=ed1495a1-4a2c-4fab-a409-975c2768b89c "HTTP/1.1 200 OK"
+2026-05-07 12:56:25,727 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/58f73381cbe3266caa6d35a2c12cb77e720345122d5cf9f7cdb96e041ceca7c9/image.webp "HTTP/1.1 200 OK"
+2026-05-07 12:56:25,845 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=108
+2026-05-07 12:56:25,845 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] saving_masks progress=92
+2026-05-07 12:56:26,112 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] segments_meta saved (94 segments)
+2026-05-07 12:56:26,112 INFO backend.segmentation: [JOB 6e3dc1caa0ea4d58a9fdb96458cc352a] done mask_count=108
+2026-05-07 12:56:26,112 INFO backend.segmentation: [UPLOAD_BG] DONE 15.184s at 2026-05-07T18:56:26.112231+00:00
+2026-05-07 12:56:26,112 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 13:01:56,800 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T19:01:56.800564+00:00
+2026-05-07 13:01:56,801 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] preparing_image progress=12
+2026-05-07 13:01:56,873 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 13:01:56,874 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 13:01:57,517 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 13:01:58,135 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 13:01:58,320 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 13:01:58,810 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/5c3e334b-800c-4d78-93b4-35d66a611f5d "HTTP/1.1 200 OK"
+2026-05-07 13:01:58,963 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 13:01:59,514 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 13:02:00,027 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=5c3e334b-800c-4d78-93b4-35d66a611f5d "HTTP/1.1 200 OK"
+2026-05-07 13:02:11,627 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/58f73381cbe3266caa6d35a2c12cb77e720345122d5cf9f7cdb96e041ceca7c9/image.webp "HTTP/1.1 200 OK"
+2026-05-07 13:02:11,743 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=108
+2026-05-07 13:02:11,747 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] saving_masks progress=92
+2026-05-07 13:02:12,035 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] segments_meta saved (94 segments)
+2026-05-07 13:02:12,035 INFO backend.segmentation: [JOB c145be47d09942d691ae3f650e362810] done mask_count=108
+2026-05-07 13:02:12,035 INFO backend.segmentation: [UPLOAD_BG] DONE 15.235s at 2026-05-07T19:02:12.035158+00:00
+2026-05-07 13:02:12,036 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 14:54:46,839 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 14:54:46,873 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-07 14:55:18,464 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T20:55:18.464808+00:00
+2026-05-07 14:55:18,465 INFO backend.segmentation: [JOB e2978c252391482ea410013edd5dd614] preparing_image progress=12
+2026-05-07 14:55:18,684 INFO backend.segmentation: [JOB e2978c252391482ea410013edd5dd614] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 14:55:18,684 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 14:55:20,941 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 14:55:21,523 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 14:55:22,147 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 14:55:22,266 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/044411e2-1c1d-423c-8a2b-1bf8aa03347d "HTTP/1.1 200 OK"
+2026-05-07 14:55:22,418 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 14:55:22,953 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 14:55:23,627 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=044411e2-1c1d-423c-8a2b-1bf8aa03347d "HTTP/1.1 200 OK"
+2026-05-07 14:55:38,599 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/e46ee411d94ec777ba35b9e436d075e4a9639d5f1e564687b887320d75811f38/image.webp "HTTP/1.1 200 OK"
+2026-05-07 14:55:38,603 WARNING services.gradio_client_service: GPU Space failed (Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^), trying CPU fallback...
+2026-05-07 14:55:38,604 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
+2026-05-07 14:55:39,263 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 14:55:39,888 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 14:55:40,067 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 14:55:40,580 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/0cb7d459-fd3f-4435-b44f-3d93594c3e32 "HTTP/1.1 200 OK"
+2026-05-07 14:55:40,750 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 14:55:41,291 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 14:55:41,867 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=0cb7d459-fd3f-4435-b44f-3d93594c3e32 "HTTP/1.1 200 OK"
+2026-05-07 14:59:17,106 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T20:59:17.106093+00:00
+2026-05-07 14:59:17,106 INFO backend.segmentation: [JOB 9d8e54c57b804dd6a5868f2f16907d6a] preparing_image progress=12
+2026-05-07 14:59:17,177 INFO backend.segmentation: [JOB 9d8e54c57b804dd6a5868f2f16907d6a] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 14:59:17,178 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 14:59:17,820 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 14:59:18,429 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 14:59:18,612 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 14:59:19,270 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/4bafc24c-7b3e-47e5-ab5c-040b1104f6ad "HTTP/1.1 200 OK"
+2026-05-07 14:59:19,316 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 14:59:19,895 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 14:59:20,498 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=4bafc24c-7b3e-47e5-ab5c-040b1104f6ad "HTTP/1.1 200 OK"
+2026-05-07 14:59:22,556 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/e46ee411d94ec777ba35b9e436d075e4a9639d5f1e564687b887320d75811f38/image.webp "HTTP/1.1 200 OK"
+2026-05-07 14:59:22,561 WARNING services.gradio_client_service: GPU Space failed (Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^), trying CPU fallback...
+2026-05-07 14:59:22,562 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
+2026-05-07 14:59:23,331 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 14:59:24,033 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 14:59:24,159 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 14:59:24,691 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/58739913-8194-4cc9-ae76-fab58874372a "HTTP/1.1 200 OK"
+2026-05-07 14:59:24,844 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 14:59:25,478 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 14:59:26,087 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=58739913-8194-4cc9-ae76-fab58874372a "HTTP/1.1 200 OK"
+2026-05-07 14:59:38,140 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/file=/tmp/gradio/0870aa16fb1d36280b4436effe666b2d40896a35db44e69dfe24e623f43e743b/image.webp "HTTP/1.1 200 OK"
+2026-05-07 14:59:38,143 ERROR backend.segmentation: [JOB e2978c252391482ea410013edd5dd614] failed: Both Gradio Spaces failed.
+  GPU (https://eduardo4547-hyper-reality-sam2-gpu.hf.space): Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
+  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/usr/local/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
+    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 47, in _call_gradio_sync
+    raise RuntimeError(f"Gradio Space error: {combined['error'][:500]}")
+RuntimeError: Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/usr/local/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The above exception was the direct cause of the following exception:
+
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
+    label_map, mask_count = segment_via_gradio_sync(image_path)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
+    raise RuntimeError(
+RuntimeError: Both Gradio Spaces failed.
+  GPU (https://eduardo4547-hyper-reality-sam2-gpu.hf.space): Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
+  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/usr/local/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+2026-05-07 14:59:38,144 INFO backend.segmentation: [UPLOAD_BG] DONE 259.680s at 2026-05-07T20:59:38.144994+00:00
+2026-05-07 14:59:38,144 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:02:17,066 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 15:02:17,090 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-07 15:02:54,241 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:02:54.241047+00:00
+2026-05-07 15:02:54,241 INFO backend.segmentation: [JOB 77ed4dd081d7432cbc3073f159883876] preparing_image progress=12
+2026-05-07 15:02:54,369 INFO backend.segmentation: [JOB 77ed4dd081d7432cbc3073f159883876] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 15:02:54,369 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 15:02:55,466 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 15:02:55,989 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:02:56,471 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:02:56,561 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/ae72d127-eaf7-4469-8805-b2f2d63b0e9a "HTTP/1.1 200 OK"
+2026-05-07 15:02:56,764 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:02:57,222 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:02:57,668 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=ae72d127-eaf7-4469-8805-b2f2d63b0e9a "HTTP/1.1 200 OK"
+2026-05-07 15:02:59,650 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/e46ee411d94ec777ba35b9e436d075e4a9639d5f1e564687b887320d75811f38/image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:02:59,653 WARNING services.gradio_client_service: GPU Space failed (Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^), trying CPU fallback...
+2026-05-07 15:02:59,654 INFO services.gradio_client_service: Calling CPU fallback Space: https://eduardo4547-hyper-reality-sam2-cpu.hf.space
+2026-05-07 15:03:01,621 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 15:03:02,088 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:03:02,262 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:03:02,629 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/heartbeat/2f3a5842-bc35-4aa3-8198-e3338bde647a "HTTP/1.1 200 OK"
+2026-05-07 15:03:02,785 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:03:03,183 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:03:03,623 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-cpu.hf.space/gradio_api/queue/data?session_hash=2f3a5842-bc35-4aa3-8198-e3338bde647a "HTTP/1.1 200 OK"
+2026-05-07 15:11:16,099 ERROR backend.segmentation: [JOB 77ed4dd081d7432cbc3073f159883876] failed: Both Gradio Spaces failed.
+  GPU (https://eduardo4547-hyper-reality-sam2-gpu.hf.space): Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
+  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): 
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 91, in segment_via_gradio_sync
+    return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 36, in _call_gradio_sync
+    _overlay_file, combined_json_str = client.predict(
+                                       ^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 499, in predict
+    ).result()
+      ^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 1484, in result
+    return super().result(timeout=timeout)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.12_3.12.2800.0_x64__qbz5n2kfra8p0\Lib\concurrent\futures\_base.py", line 456, in result
+    return self.__get_result()
+           ^^^^^^^^^^^^^^^^^^^
+  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.12_3.12.2800.0_x64__qbz5n2kfra8p0\Lib\concurrent\futures\_base.py", line 401, in __get_result
+    raise self._exception
+  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.12_3.12.2800.0_x64__qbz5n2kfra8p0\Lib\concurrent\futures\thread.py", line 59, in run
+    result = self.fn(*self.args, **self.kwargs)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 1080, in _inner
+    predictions = _predict(*data, **kwargs)
+                  ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 1188, in _predict
+    result = self._sse_fn_v1plus(helper, event_id, self.protocol)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\client.py", line 1388, in _sse_fn_v1plus
+    return utils.get_pred_from_sse_v1plus(
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\utils.py", line 395, in get_pred_from_sse_v1plus
+    raise exception
+  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.12_3.12.2800.0_x64__qbz5n2kfra8p0\Lib\concurrent\futures\thread.py", line 59, in run
+    result = self.fn(*self.args, **self.kwargs)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\.venv\Lib\site-packages\gradio_client\utils.py", line 511, in stream_sse_v1plus
+    raise concurrent.futures.CancelledError()
+concurrent.futures._base.CancelledError
+
+The above exception was the direct cause of the following exception:
+
+Traceback (most recent call last):
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\image_service.py", line 138, in run_upload_job
+    label_map, mask_count = segment_via_gradio_sync(image_path)
+                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\services\gradio_client_service.py", line 93, in segment_via_gradio_sync
+    raise RuntimeError(
+RuntimeError: Both Gradio Spaces failed.
+  GPU (https://eduardo4547-hyper-reality-sam2-gpu.hf.space): Gradio Space error: Traceback (most recent call last):
+  File "/app/app.py", line 133, in segment_for_backend
+    resultado = sam_vit_pipeline(
+        pil_image,
+    ...<5 lines>...
+        crops_n_layers=PARAMS["crops_n_layers"],
+    )
+  File "/root/.pyenv/versions/3.13.13/lib/python3.13/site-packages/transformers/pipelines/mask_generation.py", line 190, in __call__
+    return super().__call__(image, *args, num_workers=num_workers, batch_size=batch_size, **kwargs)
+           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
+  CPU (https://eduardo4547-hyper-reality-sam2-cpu.hf.space): 
+2026-05-07 15:11:16,123 INFO backend.segmentation: [UPLOAD_BG] DONE 501.883s at 2026-05-07T21:11:16.123777+00:00
+2026-05-07 15:11:16,123 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:11:33,448 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 15:11:33,462 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-07 15:11:38,641 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:11:38.641727+00:00
+2026-05-07 15:11:38,642 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] preparing_image progress=12
+2026-05-07 15:11:38,745 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 15:11:38,747 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 15:11:39,778 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 15:11:40,250 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:11:40,717 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:11:40,821 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/2ba41729-fa1a-4207-b1a6-9c3ef6526887 "HTTP/1.1 200 OK"
+2026-05-07 15:11:40,924 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:11:41,336 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:11:42,039 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=2ba41729-fa1a-4207-b1a6-9c3ef6526887 "HTTP/1.1 200 OK"
+2026-05-07 15:12:02,740 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d17dd4b993c601f166cf197f34896b5d17a23e30a9fe1f5022b368a594a3f823/image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:12:02,846 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
+2026-05-07 15:12:02,846 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] saving_masks progress=92
+2026-05-07 15:12:02,991 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] segments_meta saved (54 segments)
+2026-05-07 15:12:02,991 INFO backend.segmentation: [JOB 710a0f404cce4589bd59a34ef7a8fff9] done mask_count=63
+2026-05-07 15:12:02,992 INFO backend.segmentation: [UPLOAD_BG] DONE 24.350s at 2026-05-07T21:12:02.992931+00:00
+2026-05-07 15:12:02,992 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:12:30,031 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:12:30.031296+00:00
+2026-05-07 15:12:30,558 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:12:30,891 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.860s at 2026-05-07T21:12:30.891199+00:00
+2026-05-07 15:13:18,964 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:13:18.964838+00:00
+2026-05-07 15:13:18,964 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] preparing_image progress=12
+2026-05-07 15:13:19,050 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 15:13:19,051 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 15:13:19,623 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 15:13:20,207 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:13:20,445 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:13:20,882 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/6b2ee8fb-256a-4778-af39-73fbc7180d64 "HTTP/1.1 200 OK"
+2026-05-07 15:13:21,064 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:13:21,680 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:13:22,271 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=6b2ee8fb-256a-4778-af39-73fbc7180d64 "HTTP/1.1 200 OK"
+2026-05-07 15:13:32,414 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d17dd4b993c601f166cf197f34896b5d17a23e30a9fe1f5022b368a594a3f823/image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:13:32,528 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
+2026-05-07 15:13:32,528 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] saving_masks progress=92
+2026-05-07 15:13:32,702 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] segments_meta saved (54 segments)
+2026-05-07 15:13:32,703 INFO backend.segmentation: [JOB 27e16fe858474d01905b11a66b235cc4] done mask_count=63
+2026-05-07 15:13:32,703 INFO backend.segmentation: [UPLOAD_BG] DONE 13.740s at 2026-05-07T21:13:32.703517+00:00
+2026-05-07 15:13:32,704 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:19:48,376 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:19:48.376272+00:00
+2026-05-07 15:19:48,376 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] preparing_image progress=12
+2026-05-07 15:19:48,443 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 15:19:48,444 INFO services.gradio_client_service: Calling GPU Gradio Space: https://eduardo4547-hyper-reality-sam2-gpu.hf.space
+2026-05-07 15:19:49,095 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/config "HTTP/1.1 200 OK"
+2026-05-07 15:19:49,716 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:19:49,928 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:19:50,414 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/heartbeat/c601fff9-ae77-444d-86f4-c6eb6ee29ae8 "HTTP/1.1 200 OK"
+2026-05-07 15:19:50,537 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:19:51,092 INFO httpx: HTTP Request: POST https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:19:51,642 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/queue/data?session_hash=c601fff9-ae77-444d-86f4-c6eb6ee29ae8 "HTTP/1.1 200 OK"
+2026-05-07 15:20:01,890 INFO httpx: HTTP Request: GET https://eduardo4547-hyper-reality-sam2-gpu.hf.space/gradio_api/file=/tmp/gradio/d17dd4b993c601f166cf197f34896b5d17a23e30a9fe1f5022b368a594a3f823/image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:20:02,004 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
+2026-05-07 15:20:02,005 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] saving_masks progress=92
+2026-05-07 15:20:02,221 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] segments_meta saved (54 segments)
+2026-05-07 15:20:02,221 INFO backend.segmentation: [JOB 6ec5c36da3b941c48ee955a0e6018efd] done mask_count=63
+2026-05-07 15:20:02,221 INFO backend.segmentation: [UPLOAD_BG] DONE 13.846s at 2026-05-07T21:20:02.221722+00:00
+2026-05-07 15:20:02,222 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:21:36,330 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:21:36.330551+00:00
+2026-05-07 15:21:36,908 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:21:37,121 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.790s at 2026-05-07T21:21:37.121352+00:00
+2026-05-07 15:21:45,205 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:21:45.203794+00:00
+2026-05-07 15:21:45,723 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.39, h_ratio=1.19)
+2026-05-07 15:21:45,743 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:21:45,953 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.748s at 2026-05-07T21:21:45.953335+00:00
+2026-05-07 15:21:49,795 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:21:49.795014+00:00
+2026-05-07 15:21:50,312 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.24)
+2026-05-07 15:21:50,331 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:21:50,547 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.753s at 2026-05-07T21:21:50.547610+00:00
+2026-05-07 15:21:56,068 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:21:56.068945+00:00
+2026-05-07 15:21:56,572 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.18, h_ratio=287.00)
+2026-05-07 15:21:56,592 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:21:56,802 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.734s at 2026-05-07T21:21:56.802967+00:00
+2026-05-07 15:23:52,960 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-07 15:23:52,981 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-07 15:24:42,274 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:24:42.274969+00:00
+2026-05-07 15:24:42,274 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] preparing_image progress=12
+2026-05-07 15:24:42,409 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 15:24:42,414 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 15:24:45,341 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 15:24:47,723 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:24:48,299 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:24:50,226 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/dab64d79-0e60-4114-b75e-b53930a5d4f7 "HTTP/1.1 200 OK"
+2026-05-07 15:24:50,247 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:24:54,192 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:24:56,620 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=dab64d79-0e60-4114-b75e-b53930a5d4f7 "HTTP/1.1 200 OK"
+2026-05-07 15:27:24,526 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:27:24,538 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
+2026-05-07 15:27:24,538 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] saving_masks progress=92
+2026-05-07 15:27:24,702 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] segments_meta saved (63 segments)
+2026-05-07 15:27:24,702 INFO backend.segmentation: [JOB ca20946463e74f8a9be921cb5dc3580f] done mask_count=63
+2026-05-07 15:27:24,702 INFO backend.segmentation: [UPLOAD_BG] DONE 162.428s at 2026-05-07T21:27:24.702523+00:00
+2026-05-07 15:27:24,702 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:27:41,959 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:41.959810+00:00
+2026-05-07 15:27:42,278 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.05, h_ratio=416.39)
+2026-05-07 15:27:42,305 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:27:42,814 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.854s at 2026-05-07T21:27:42.814627+00:00
+2026-05-07 15:27:46,763 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:46.763830+00:00
+2026-05-07 15:27:47,166 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:27:47,378 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.614s at 2026-05-07T21:27:47.378508+00:00
+2026-05-07 15:27:49,193 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:49.193540+00:00
+2026-05-07 15:27:49,513 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
+2026-05-07 15:27:49,532 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:27:49,729 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.536s at 2026-05-07T21:27:49.729431+00:00
+2026-05-07 15:27:51,249 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:51.249369+00:00
+2026-05-07 15:27:51,544 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:27:51,755 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.506s at 2026-05-07T21:27:51.755618+00:00
+2026-05-07 15:27:52,680 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:52.680739+00:00
+2026-05-07 15:27:52,986 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:27:53,211 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.531s at 2026-05-07T21:27:53.211475+00:00
+2026-05-07 15:27:54,203 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:27:54.203416+00:00
+2026-05-07 15:27:54,500 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:27:54,736 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.533s at 2026-05-07T21:27:54.736190+00:00
+2026-05-07 15:28:31,805 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:28:31.805147+00:00
+2026-05-07 15:28:32,098 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:28:32,338 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.534s at 2026-05-07T21:28:32.338930+00:00
+2026-05-07 15:28:42,559 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:28:42.559339+00:00
+2026-05-07 15:28:43,089 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:28:43,307 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.748s at 2026-05-07T21:28:43.307767+00:00
+2026-05-07 15:28:46,313 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:28:46.313349+00:00
+2026-05-07 15:28:46,831 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.74, h_ratio=1.19)
+2026-05-07 15:28:46,865 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:28:47,077 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.764s at 2026-05-07T21:28:47.077622+00:00
+2026-05-07 15:28:59,114 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:28:59.114208+00:00
+2026-05-07 15:28:59,643 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:28:59,870 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.756s at 2026-05-07T21:28:59.870175+00:00
+2026-05-07 15:29:02,857 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:29:02.857460+00:00
+2026-05-07 15:29:03,385 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:29:03,598 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.741s at 2026-05-07T21:29:03.598245+00:00
+2026-05-07 15:29:09,230 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:29:09.230242+00:00
+2026-05-07 15:29:09,812 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
+2026-05-07 15:29:09,836 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:29:10,063 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.832s at 2026-05-07T21:29:10.063265+00:00
+2026-05-07 15:30:08,609 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:30:08.608222+00:00
+2026-05-07 15:30:09,164 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
+2026-05-07 15:30:09,188 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:30:09,393 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.785s at 2026-05-07T21:30:09.393640+00:00
+2026-05-07 15:30:14,390 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:30:14.390221+00:00
+2026-05-07 15:30:14,951 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=2.27, h_ratio=1.02)
+2026-05-07 15:30:14,970 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 15:30:15,192 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.803s at 2026-05-07T21:30:15.192554+00:00
+2026-05-07 15:30:40,712 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:30:40.712459+00:00
+2026-05-07 15:30:40,713 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] preparing_image progress=12
+2026-05-07 15:30:40,791 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] segmenting_with_sam2 progress=30 estimated_seconds=63.05024
+2026-05-07 15:30:40,792 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 15:30:43,195 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 15:30:45,588 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:30:45,733 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:30:48,162 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:30:48,173 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/d1c209e4-d368-4e81-8ce0-b7c8824ed437 "HTTP/1.1 200 OK"
+2026-05-07 15:30:50,534 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:30:53,316 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=d1c209e4-d368-4e81-8ce0-b7c8824ed437 "HTTP/1.1 200 OK"
+2026-05-07 15:33:13,981 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\3944faeeae589a5b426a0f9b9ce0280816fb839f02b7dd9ab2628c5aef775da2\image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:33:13,999 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=66
+2026-05-07 15:33:14,000 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] saving_masks progress=92
+2026-05-07 15:33:14,323 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] segments_meta saved (66 segments)
+2026-05-07 15:33:14,324 INFO backend.segmentation: [JOB 9d4215753f664bf08bfac6b433db1a36] done mask_count=66
+2026-05-07 15:33:14,325 INFO backend.segmentation: [UPLOAD_BG] DONE 153.613s at 2026-05-07T21:33:14.324926+00:00
+2026-05-07 15:33:14,325 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:33:20,991 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:20.991904+00:00
+2026-05-07 15:33:21,557 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.03)
+2026-05-07 15:33:21,587 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-07 15:33:21,856 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.865s at 2026-05-07T21:33:21.856475+00:00
+2026-05-07 15:33:23,187 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:23.187537+00:00
+2026-05-07 15:33:23,640 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=106.02)
+2026-05-07 15:33:23,660 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-07 15:33:23,887 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.700s at 2026-05-07T21:33:23.887323+00:00
+2026-05-07 15:33:28,666 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:28.666370+00:00
+2026-05-07 15:33:29,256 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.24, h_ratio=1.13)
+2026-05-07 15:33:29,278 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-07 15:33:29,514 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.849s at 2026-05-07T21:33:29.514966+00:00
+2026-05-07 15:33:35,559 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:35.559814+00:00
+2026-05-07 15:33:36,119 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.03)
+2026-05-07 15:33:36,156 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-07 15:33:36,369 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.810s at 2026-05-07T21:33:36.369980+00:00
+2026-05-07 15:33:41,348 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:33:41.348944+00:00
+2026-05-07 15:33:41,841 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.03)
+2026-05-07 15:33:41,873 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-07 15:33:42,143 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.796s at 2026-05-07T21:33:42.143571+00:00
+2026-05-07 15:34:05,661 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:34:05.661441+00:00
+2026-05-07 15:34:06,223 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.53, h_ratio=1.33)
+2026-05-07 15:34:06,245 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\venta-de-casas-modernas-residencial-los-robles.jpg
+2026-05-07 15:34:06,458 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.797s at 2026-05-07T21:34:06.458559+00:00
+2026-05-07 15:37:38,373 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:37:38.373999+00:00
+2026-05-07 15:37:38,375 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] preparing_image progress=12
+2026-05-07 15:37:38,423 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] segmenting_with_sam2 progress=30 estimated_seconds=94.01599999999999
+2026-05-07 15:37:38,423 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 15:37:40,841 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 15:37:43,152 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:37:43,304 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:37:45,640 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:37:45,645 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/96233e8c-fcb3-4e6e-a52b-43f262d4afc5 "HTTP/1.1 200 OK"
+2026-05-07 15:37:48,001 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:37:50,838 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=96233e8c-fcb3-4e6e-a52b-43f262d4afc5 "HTTP/1.1 200 OK"
+2026-05-07 15:39:30,039 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\56758f540e1c547de434b369fae158810fde033fe3650199c54eecf9fd68ac46\image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:39:30,055 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=58
+2026-05-07 15:39:30,056 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] saving_masks progress=92
+2026-05-07 15:39:30,380 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] segments_meta saved (58 segments)
+2026-05-07 15:39:30,381 INFO backend.segmentation: [JOB 24ce2b1d21234ddb8fbb35b45f4d8792] done mask_count=58
+2026-05-07 15:39:30,381 INFO backend.segmentation: [UPLOAD_BG] DONE 112.008s at 2026-05-07T21:39:30.381897+00:00
+2026-05-07 15:39:30,381 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:42:27,756 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:27.756524+00:00
+2026-05-07 15:42:28,316 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-07 15:42:28,714 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.958s at 2026-05-07T21:42:28.714486+00:00
+2026-05-07 15:42:31,110 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:31.110675+00:00
+2026-05-07 15:42:31,681 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-07 15:42:32,030 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.920s at 2026-05-07T21:42:32.030068+00:00
+2026-05-07 15:42:36,790 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:36.789013+00:00
+2026-05-07 15:42:37,354 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-07 15:42:37,723 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.934s at 2026-05-07T21:42:37.723785+00:00
+2026-05-07 15:42:43,821 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:43.821895+00:00
+2026-05-07 15:42:44,133 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-07 15:42:44,503 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.682s at 2026-05-07T21:42:44.503891+00:00
+2026-05-07 15:42:45,709 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:45.709851+00:00
+2026-05-07 15:42:46,014 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-07 15:42:46,365 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.656s at 2026-05-07T21:42:46.365851+00:00
+2026-05-07 15:42:48,755 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:48.755885+00:00
+2026-05-07 15:42:49,065 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-07 15:42:49,433 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.677s at 2026-05-07T21:42:49.433452+00:00
+2026-05-07 15:42:56,861 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:42:56.861868+00:00
+2026-05-07 15:42:57,289 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-07 15:42:57,689 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.827s at 2026-05-07T21:42:57.687938+00:00
+2026-05-07 15:47:02,637 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:47:02.637766+00:00
+2026-05-07 15:47:02,987 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-07 15:47:03,354 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.717s at 2026-05-07T21:47:03.354802+00:00
+2026-05-07 15:47:06,315 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:47:06.315345+00:00
+2026-05-07 15:47:06,692 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.31, h_ratio=1.04)
+2026-05-07 15:47:06,734 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm azul.jpg
+2026-05-07 15:47:07,092 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.777s at 2026-05-07T21:47:07.092208+00:00
+2026-05-07 15:47:19,592 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:47:19.592166+00:00
+2026-05-07 15:47:19,593 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] preparing_image progress=12
+2026-05-07 15:47:20,196 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] segmenting_with_sam2 progress=30 estimated_seconds=57.674240000000005
+2026-05-07 15:47:20,197 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 15:47:22,577 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 15:47:24,974 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:47:25,112 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:47:27,430 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9d1507c0-f15b-4ce4-8a14-a75643934023 "HTTP/1.1 200 OK"
+2026-05-07 15:47:27,451 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:47:29,917 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:47:32,852 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9d1507c0-f15b-4ce4-8a14-a75643934023 "HTTP/1.1 200 OK"
+2026-05-07 15:49:56,285 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\7fb2980e7537a93df201edb46c01cac70b34b0d407baf16d8c766c8326b688bb\image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:49:56,299 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=56
+2026-05-07 15:49:56,301 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] saving_masks progress=92
+2026-05-07 15:49:56,485 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] segments_meta saved (56 segments)
+2026-05-07 15:49:56,486 INFO backend.segmentation: [JOB fe9309b4ebae4857a7b0ff42d9faf677] done mask_count=56
+2026-05-07 15:49:56,486 INFO backend.segmentation: [UPLOAD_BG] DONE 156.895s at 2026-05-07T21:49:56.486476+00:00
+2026-05-07 15:49:56,486 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:50:23,300 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:23.300896+00:00
+2026-05-07 15:50:23,632 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.43)
+2026-05-07 15:50:23,649 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
+2026-05-07 15:50:23,860 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.560s at 2026-05-07T21:50:23.860900+00:00
+2026-05-07 15:50:25,390 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:25.390001+00:00
+2026-05-07 15:50:25,729 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.05, h_ratio=1.59)
+2026-05-07 15:50:25,748 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
+2026-05-07 15:50:25,961 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.573s at 2026-05-07T21:50:25.961503+00:00
+2026-05-07 15:50:29,067 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:29.067701+00:00
+2026-05-07 15:50:29,357 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
+2026-05-07 15:50:29,574 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.505s at 2026-05-07T21:50:29.573244+00:00
+2026-05-07 15:50:30,765 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:30.765933+00:00
+2026-05-07 15:50:31,113 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.43, h_ratio=1.00)
+2026-05-07 15:50:31,135 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
+2026-05-07 15:50:31,381 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.616s at 2026-05-07T21:50:31.381120+00:00
+2026-05-07 15:50:34,372 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:34.372354+00:00
+2026-05-07 15:50:34,702 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
+2026-05-07 15:50:34,919 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.547s at 2026-05-07T21:50:34.919402+00:00
+2026-05-07 15:50:38,283 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:38.283908+00:00
+2026-05-07 15:50:38,620 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
+2026-05-07 15:50:38,822 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.538s at 2026-05-07T21:50:38.821521+00:00
+2026-05-07 15:50:42,362 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:42.362356+00:00
+2026-05-07 15:50:42,752 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=81.06)
+2026-05-07 15:50:42,770 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
+2026-05-07 15:50:42,983 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.622s at 2026-05-07T21:50:42.983933+00:00
+2026-05-07 15:50:46,827 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:46.827950+00:00
+2026-05-07 15:50:47,260 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
+2026-05-07 15:50:47,509 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.681s at 2026-05-07T21:50:47.509694+00:00
+2026-05-07 15:50:51,671 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:50:51.671277+00:00
+2026-05-07 15:50:52,056 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\EB-UD3231 (1).jpg
+2026-05-07 15:50:52,261 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.591s at 2026-05-07T21:50:52.261800+00:00
+2026-05-07 15:51:01,177 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:51:01.177947+00:00
+2026-05-07 15:51:01,177 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] preparing_image progress=12
+2026-05-07 15:51:01,277 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] segmenting_with_sam2 progress=30 estimated_seconds=71.65183999999999
+2026-05-07 15:51:01,279 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 15:51:03,724 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 15:51:06,105 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:51:06,299 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:51:08,531 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/1f6ec649-450c-4d10-a42f-a0714e8554c6 "HTTP/1.1 200 OK"
+2026-05-07 15:51:08,533 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:51:10,974 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:51:13,861 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=1f6ec649-450c-4d10-a42f-a0714e8554c6 "HTTP/1.1 200 OK"
+2026-05-07 15:53:32,035 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\9b2d1c318212280bd44f91bf2c3aa028767f3015780e04d1e67d456398adfe23\image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:53:32,051 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=55
+2026-05-07 15:53:32,051 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] saving_masks progress=92
+2026-05-07 15:53:32,291 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] segments_meta saved (55 segments)
+2026-05-07 15:53:32,291 INFO backend.segmentation: [JOB 79a04736dcfa4abc8383a745c149b88c] done mask_count=55
+2026-05-07 15:53:32,291 INFO backend.segmentation: [UPLOAD_BG] DONE 151.115s at 2026-05-07T21:53:32.291574+00:00
+2026-05-07 15:53:32,291 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:53:42,312 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:53:42.312363+00:00
+2026-05-07 15:53:42,838 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.04, h_ratio=1.36)
+2026-05-07 15:53:42,868 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
+2026-05-07 15:53:43,124 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.812s at 2026-05-07T21:53:43.124323+00:00
+2026-05-07 15:53:45,407 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:53:45.407699+00:00
+2026-05-07 15:53:45,913 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
+2026-05-07 15:53:46,160 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.752s at 2026-05-07T21:53:46.160544+00:00
+2026-05-07 15:53:51,917 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:53:51.917268+00:00
+2026-05-07 15:53:52,460 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.04, h_ratio=1.36)
+2026-05-07 15:53:52,504 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
+2026-05-07 15:53:52,784 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.868s at 2026-05-07T21:53:52.784729+00:00
+2026-05-07 15:53:59,737 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:53:59.737940+00:00
+2026-05-07 15:54:00,303 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.01, h_ratio=1.26)
+2026-05-07 15:54:00,325 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
+2026-05-07 15:54:00,581 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.843s at 2026-05-07T21:54:00.581113+00:00
+2026-05-07 15:54:07,204 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:54:07.204959+00:00
+2026-05-07 15:54:07,723 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.02 < 0.35, skip perspective)
+2026-05-07 15:54:07,755 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
+2026-05-07 15:54:08,011 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.806s at 2026-05-07T21:54:08.011194+00:00
+2026-05-07 15:54:14,251 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:54:14.251503+00:00
+2026-05-07 15:54:14,586 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.02 < 0.35, skip perspective)
+2026-05-07 15:54:14,618 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
+2026-05-07 15:54:14,893 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.642s at 2026-05-07T21:54:14.893824+00:00
+2026-05-07 15:54:20,951 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:54:20.951821+00:00
+2026-05-07 15:54:21,369 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.00, h_ratio=1.21)
+2026-05-07 15:54:21,394 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\unnamed.jpg
+2026-05-07 15:54:21,654 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.703s at 2026-05-07T21:54:21.654007+00:00
+2026-05-07 15:55:49,324 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:55:49.324991+00:00
+2026-05-07 15:55:49,325 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] preparing_image progress=12
+2026-05-07 15:55:49,407 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-05-07 15:55:49,407 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 15:55:51,777 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 15:55:54,163 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:55:54,303 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:55:56,641 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/ddc1fa5d-ad06-492d-be12-a7f5ee46894f "HTTP/1.1 200 OK"
+2026-05-07 15:55:56,647 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:55:59,061 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:56:01,950 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=ddc1fa5d-ad06-492d-be12-a7f5ee46894f "HTTP/1.1 200 OK"
+2026-05-07 15:58:10,784 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\63f35ee774073b13ee87a1d3c7e73d1d3b47b4183190f3b098b633273f464612\image.webp "HTTP/1.1 200 OK"
+2026-05-07 15:58:10,799 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=61
+2026-05-07 15:58:10,799 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] saving_masks progress=92
+2026-05-07 15:58:11,031 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] segments_meta saved (61 segments)
+2026-05-07 15:58:11,033 INFO backend.segmentation: [JOB df4da3c76a584af9a84bfa05b6253222] done mask_count=61
+2026-05-07 15:58:11,033 INFO backend.segmentation: [UPLOAD_BG] DONE 141.708s at 2026-05-07T21:58:11.033788+00:00
+2026-05-07 15:58:11,033 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 15:58:20,920 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:20.920319+00:00
+2026-05-07 15:58:21,375 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.07)
+2026-05-07 15:58:21,407 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 15:58:21,598 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.679s at 2026-05-07T21:58:21.598068+00:00
+2026-05-07 15:58:24,623 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:24.623163+00:00
+2026-05-07 15:58:25,169 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.07)
+2026-05-07 15:58:25,191 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 15:58:25,360 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.738s at 2026-05-07T21:58:25.360818+00:00
+2026-05-07 15:58:28,165 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:28.165635+00:00
+2026-05-07 15:58:28,661 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 15:58:28,843 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.678s at 2026-05-07T21:58:28.843020+00:00
+2026-05-07 15:58:32,464 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:32.464694+00:00
+2026-05-07 15:58:32,978 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.08, h_ratio=1.42)
+2026-05-07 15:58:32,994 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 15:58:33,161 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.696s at 2026-05-07T21:58:33.161634+00:00
+2026-05-07 15:58:38,273 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:38.273840+00:00
+2026-05-07 15:58:38,781 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.13, h_ratio=2.54)
+2026-05-07 15:58:38,796 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 15:58:39,000 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.726s at 2026-05-07T21:58:39.000222+00:00
+2026-05-07 15:58:46,330 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:46.330265+00:00
+2026-05-07 15:58:46,828 INFO backend.segmentation: [APPLY_TEXTURE] perspective floor tiling applied (trap=1.00)
+2026-05-07 15:58:46,842 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 15:58:47,013 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.682s at 2026-05-07T21:58:47.013199+00:00
+2026-05-07 15:58:50,609 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:50.609562+00:00
+2026-05-07 15:58:51,166 INFO backend.segmentation: [APPLY_TEXTURE] perspective floor tiling applied (trap=1.00)
+2026-05-07 15:58:51,183 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 15:58:51,361 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.752s at 2026-05-07T21:58:51.361385+00:00
+2026-05-07 15:58:55,441 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:58:55.441205+00:00
+2026-05-07 15:58:55,946 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 15:58:56,114 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.673s at 2026-05-07T21:58:56.113779+00:00
+2026-05-07 15:59:08,450 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T21:59:08.450556+00:00
+2026-05-07 15:59:08,975 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.23, h_ratio=1.07)
+2026-05-07 15:59:09,001 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 15:59:09,173 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.723s at 2026-05-07T21:59:09.173815+00:00
+2026-05-07 15:59:16,551 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T21:59:16.551116+00:00
+2026-05-07 15:59:16,552 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] preparing_image progress=12
+2026-05-07 15:59:16,631 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-05-07 15:59:16,631 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 15:59:18,993 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 15:59:21,337 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 15:59:21,485 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 15:59:23,779 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/c1c694f0-2678-4cce-a664-ce7657360059 "HTTP/1.1 200 OK"
+2026-05-07 15:59:23,799 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 15:59:26,196 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 15:59:29,114 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=c1c694f0-2678-4cce-a664-ce7657360059 "HTTP/1.1 200 OK"
+2026-05-07 16:01:40,463 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\3f4bbc5e6cf6ca3e1f300135e65cb8423907d8d2601a24cab61eaf4e68bb94d8\image.webp "HTTP/1.1 200 OK"
+2026-05-07 16:01:40,478 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=51
+2026-05-07 16:01:40,479 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] saving_masks progress=92
+2026-05-07 16:01:40,648 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] segments_meta saved (51 segments)
+2026-05-07 16:01:40,649 INFO backend.segmentation: [JOB 08b23c3c64214b4aa800997fa64cd9a7] done mask_count=51
+2026-05-07 16:01:40,649 INFO backend.segmentation: [UPLOAD_BG] DONE 144.098s at 2026-05-07T22:01:40.649441+00:00
+2026-05-07 16:01:40,649 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 16:04:16,992 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:04:16.992111+00:00
+2026-05-07 16:04:17,540 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 16:04:17,715 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.724s at 2026-05-07T22:04:17.715600+00:00
+2026-05-07 16:04:20,514 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:04:20.514659+00:00
+2026-05-07 16:04:21,019 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=1.38)
+2026-05-07 16:04:21,036 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 16:04:21,242 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.727s at 2026-05-07T22:04:21.242012+00:00
+2026-05-07 16:04:28,071 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:04:28.071982+00:00
+2026-05-07 16:04:28,407 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.30, h_ratio=1.35)
+2026-05-07 16:04:28,428 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 16:04:28,596 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.525s at 2026-05-07T22:04:28.596511+00:00
+2026-05-07 16:04:30,490 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:04:30.490530+00:00
+2026-05-07 16:04:30,813 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.02, h_ratio=1.81)
+2026-05-07 16:04:30,833 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 16:04:31,008 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.519s at 2026-05-07T22:04:31.008084+00:00
+2026-05-07 16:05:02,767 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:05:02.767829+00:00
+2026-05-07 16:05:03,251 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\demo-room.jpg
+2026-05-07 16:05:03,405 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.636s at 2026-05-07T22:05:03.405079+00:00
+2026-05-07 16:05:43,990 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:05:43.990943+00:00
+2026-05-07 16:05:43,990 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] preparing_image progress=12
+2026-05-07 16:05:44,067 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] segmenting_with_sam2 progress=30 estimated_seconds=49.28768
+2026-05-07 16:05:44,067 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 16:05:46,491 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 16:05:48,868 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 16:05:49,016 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 16:05:51,323 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/6f95fab4-a857-4501-89ac-ccbf7e0581ea "HTTP/1.1 200 OK"
+2026-05-07 16:05:51,327 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 16:05:53,691 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 16:05:56,691 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=6f95fab4-a857-4501-89ac-ccbf7e0581ea "HTTP/1.1 200 OK"
+2026-05-07 16:08:09,268 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\63f35ee774073b13ee87a1d3c7e73d1d3b47b4183190f3b098b633273f464612\image.webp "HTTP/1.1 200 OK"
+2026-05-07 16:08:09,288 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=61
+2026-05-07 16:08:09,289 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] saving_masks progress=92
+2026-05-07 16:08:09,486 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] segments_meta saved (61 segments)
+2026-05-07 16:08:09,486 INFO backend.segmentation: [JOB 3e0cf02dd665435db0db0a0143215be8] done mask_count=61
+2026-05-07 16:08:09,488 INFO backend.segmentation: [UPLOAD_BG] DONE 145.497s at 2026-05-07T22:08:09.488380+00:00
+2026-05-07 16:08:09,488 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 16:22:47,224 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:22:47.224087+00:00
+2026-05-07 16:22:47,225 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] preparing_image progress=12
+2026-05-07 16:22:47,297 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 16:22:47,298 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 16:22:49,799 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 16:22:52,184 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 16:22:52,330 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 16:22:54,605 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/3d5ff637-214a-47c4-8a4f-d64d884b7a8b "HTTP/1.1 200 OK"
+2026-05-07 16:22:54,640 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 16:22:57,021 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 16:23:00,162 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=3d5ff637-214a-47c4-8a4f-d64d884b7a8b "HTTP/1.1 200 OK"
+2026-05-07 16:25:15,470 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
+2026-05-07 16:25:15,487 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
+2026-05-07 16:25:15,487 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] saving_masks progress=92
+2026-05-07 16:25:15,707 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] segments_meta saved (63 segments)
+2026-05-07 16:25:15,708 INFO backend.segmentation: [JOB bc86ad310222406a8ffacc5db249c183] done mask_count=63
+2026-05-07 16:25:15,708 INFO backend.segmentation: [UPLOAD_BG] DONE 148.483s at 2026-05-07T22:25:15.708008+00:00
+2026-05-07 16:25:15,708 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 16:29:50,418 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:29:50.418894+00:00
+2026-05-07 16:29:50,418 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] preparing_image progress=12
+2026-05-07 16:29:50,498 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 16:29:50,500 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 16:29:52,926 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 16:29:55,311 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 16:29:55,457 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 16:29:57,773 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/c79c4e3d-25f5-4e6a-a4ba-45e7493b7b23 "HTTP/1.1 200 OK"
+2026-05-07 16:29:57,774 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 16:30:00,168 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 16:30:03,061 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=c79c4e3d-25f5-4e6a-a4ba-45e7493b7b23 "HTTP/1.1 200 OK"
+2026-05-07 16:32:17,053 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
+2026-05-07 16:32:17,071 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
+2026-05-07 16:32:17,071 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] saving_masks progress=92
+2026-05-07 16:32:17,286 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] segments_meta saved (63 segments)
+2026-05-07 16:32:17,286 INFO backend.segmentation: [JOB ddc21cbf4f774a4590e387679154a1d1] done mask_count=63
+2026-05-07 16:32:17,288 INFO backend.segmentation: [UPLOAD_BG] DONE 146.869s at 2026-05-07T22:32:17.288291+00:00
+2026-05-07 16:32:17,288 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 16:32:41,697 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:32:41.697454+00:00
+2026-05-07 16:32:42,204 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 16:32:42,424 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.726s at 2026-05-07T22:32:42.424111+00:00
+2026-05-07 16:33:01,624 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:33:01.624117+00:00
+2026-05-07 16:33:01,624 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] preparing_image progress=12
+2026-05-07 16:33:01,697 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 16:33:01,698 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 16:33:04,132 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 16:33:06,530 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 16:33:06,692 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 16:33:08,991 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/78cd91de-4ac8-417d-a699-df5ceae4592f "HTTP/1.1 200 OK"
+2026-05-07 16:33:08,994 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 16:33:11,414 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 16:33:14,289 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=78cd91de-4ac8-417d-a699-df5ceae4592f "HTTP/1.1 200 OK"
+2026-05-07 16:35:33,030 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
+2026-05-07 16:35:33,049 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
+2026-05-07 16:35:33,049 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] saving_masks progress=92
+2026-05-07 16:35:33,274 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] segments_meta saved (63 segments)
+2026-05-07 16:35:33,275 INFO backend.segmentation: [JOB e3808e0cd3a54671be6ce77b16600d2d] done mask_count=63
+2026-05-07 16:35:33,276 INFO backend.segmentation: [UPLOAD_BG] DONE 151.652s at 2026-05-07T22:35:33.276280+00:00
+2026-05-07 16:35:33,276 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 16:36:09,236 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:09.236174+00:00
+2026-05-07 16:36:09,540 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.59, h_ratio=1.44)
+2026-05-07 16:36:09,562 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 16:36:09,777 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.540s at 2026-05-07T22:36:09.777110+00:00
+2026-05-07 16:36:15,985 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:15.985071+00:00
+2026-05-07 16:36:16,483 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.16, h_ratio=1.26)
+2026-05-07 16:36:16,504 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 16:36:16,716 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.731s at 2026-05-07T22:36:16.716050+00:00
+2026-05-07 16:36:25,017 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:25.017619+00:00
+2026-05-07 16:36:25,564 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.03, h_ratio=1.37)
+2026-05-07 16:36:25,587 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 16:36:25,803 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.786s at 2026-05-07T22:36:25.803112+00:00
+2026-05-07 16:36:26,817 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:26.817271+00:00
+2026-05-07 16:36:27,352 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 16:36:27,584 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.767s at 2026-05-07T22:36:27.584739+00:00
+2026-05-07 16:36:28,334 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:28.334300+00:00
+2026-05-07 16:36:28,857 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 16:36:29,081 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.747s at 2026-05-07T22:36:29.081102+00:00
+2026-05-07 16:36:32,240 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:36:32.240623+00:00
+2026-05-07 16:36:32,772 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\WhatsApp Image 2026-05-06 at 18.47.21.jpg
+2026-05-07 16:36:33,003 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.763s at 2026-05-07T22:36:33.003855+00:00
+2026-05-07 16:40:31,573 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:40:31.573485+00:00
+2026-05-07 16:40:31,573 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] preparing_image progress=12
+2026-05-07 16:40:31,619 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] segmenting_with_sam2 progress=30 estimated_seconds=94.01599999999999
+2026-05-07 16:40:31,620 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 16:40:34,052 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 16:40:36,278 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 16:40:36,412 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 16:40:38,556 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/e3bbcd8a-d009-4eb7-b2ef-0318dd7f287c "HTTP/1.1 200 OK"
+2026-05-07 16:40:38,575 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 16:40:40,832 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 16:40:43,079 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=e3bbcd8a-d009-4eb7-b2ef-0318dd7f287c "HTTP/1.1 200 OK"
+2026-05-07 16:42:01,159 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\56758f540e1c547de434b369fae158810fde033fe3650199c54eecf9fd68ac46\image.webp "HTTP/1.1 200 OK"
+2026-05-07 16:42:01,173 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=58
+2026-05-07 16:42:01,174 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] saving_masks progress=92
+2026-05-07 16:42:01,396 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] segments_meta saved (58 segments)
+2026-05-07 16:42:01,397 INFO backend.segmentation: [JOB abe6fcd597e44e188de85ec16c828d4f] done mask_count=58
+2026-05-07 16:42:01,397 INFO backend.segmentation: [UPLOAD_BG] DONE 89.824s at 2026-05-07T22:42:01.397333+00:00
+2026-05-07 16:42:01,397 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 16:43:02,036 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T22:43:02.036847+00:00
+2026-05-07 16:43:02,036 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] preparing_image progress=12
+2026-05-07 16:43:02,378 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] segmenting_with_sam2 progress=30 estimated_seconds=105.8432
+2026-05-07 16:43:02,380 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 16:43:04,773 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 16:43:07,148 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 16:43:07,281 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 16:43:09,603 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/a89250d1-ac0d-45ef-9bdc-7f28bdbd5c74 "HTTP/1.1 200 OK"
+2026-05-07 16:43:09,607 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 16:43:12,018 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 16:43:14,837 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=a89250d1-ac0d-45ef-9bdc-7f28bdbd5c74 "HTTP/1.1 200 OK"
+2026-05-07 16:45:52,678 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\fe7e296f49e3953b396fc8aeb7f4885b83ba4201a8d3f8d451ff0339d7391c52\image.webp "HTTP/1.1 200 OK"
+2026-05-07 16:45:52,698 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=74
+2026-05-07 16:45:52,698 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] saving_masks progress=92
+2026-05-07 16:45:53,143 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] segments_meta saved (74 segments)
+2026-05-07 16:45:53,143 INFO backend.segmentation: [JOB 98668f875a5a491a9e24d80f6c5877f7] done mask_count=74
+2026-05-07 16:45:53,144 INFO backend.segmentation: [UPLOAD_BG] DONE 171.106s at 2026-05-07T22:45:53.144055+00:00
+2026-05-07 16:45:53,144 INFO backend.segmentation: Releasing resources (full_unload=False)
+2026-05-07 16:46:04,090 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:04.090988+00:00
+2026-05-07 16:46:04,428 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.31 < 0.35, skip perspective)
+2026-05-07 16:46:04,482 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 16:46:04,894 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.803s at 2026-05-07T22:46:04.893619+00:00
+2026-05-07 16:46:13,581 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:13.581681+00:00
+2026-05-07 16:46:13,926 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 16:46:14,330 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.749s at 2026-05-07T22:46:14.330751+00:00
+2026-05-07 16:46:19,978 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:19.978023+00:00
+2026-05-07 16:46:20,448 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.31 < 0.35, skip perspective)
+2026-05-07 16:46:20,501 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 16:46:20,917 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.939s at 2026-05-07T22:46:20.917957+00:00
+2026-05-07 16:46:24,322 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:24.322422+00:00
+2026-05-07 16:46:24,904 INFO backend.segmentation: [APPLY_TEXTURE] perspective floor tiling applied (trap=1.00)
+2026-05-07 16:46:24,949 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 16:46:25,362 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.040s at 2026-05-07T22:46:25.362160+00:00
+2026-05-07 16:46:29,955 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:29.955304+00:00
+2026-05-07 16:46:30,502 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
+2026-05-07 16:46:30,549 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 16:46:30,987 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.033s at 2026-05-07T22:46:30.987573+00:00
+2026-05-07 16:46:38,234 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T22:46:38.234058+00:00
+2026-05-07 16:46:38,637 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.31 < 0.35, skip perspective)
+2026-05-07 16:46:38,690 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 16:46:39,101 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.867s at 2026-05-07T22:46:39.101314+00:00
+2026-05-07 17:01:04,655 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:01:04.655845+00:00
+2026-05-07 17:01:05,250 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.05, h_ratio=1.68)
+2026-05-07 17:01:05,308 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:01:05,726 INFO backend.segmentation: [APPLY_TEXTURE] DONE 1.071s at 2026-05-07T23:01:05.726857+00:00
+2026-05-07 17:19:38,903 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-07 17:19:38,930 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-07 17:20:05,519 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:05.519131+00:00
+2026-05-07 17:20:05,664 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
+2026-05-07 17:20:05,718 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:20:06,288 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.770s at 2026-05-07T23:20:06.288369+00:00
+2026-05-07 17:20:10,885 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:10.885784+00:00
+2026-05-07 17:20:11,012 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
+2026-05-07 17:20:11,057 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:20:11,494 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.609s at 2026-05-07T23:20:11.493854+00:00
+2026-05-07 17:20:16,040 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:16.040610+00:00
+2026-05-07 17:20:16,136 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:20:16,549 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.509s at 2026-05-07T23:20:16.549652+00:00
+2026-05-07 17:20:18,515 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:18.515915+00:00
+2026-05-07 17:20:18,600 INFO backend.segmentation: [APPLY_TEXTURE] flat floor tiling (trap=0.31 < 0.35, skip perspective)
+2026-05-07 17:20:18,652 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:20:19,065 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.550s at 2026-05-07T23:20:19.065884+00:00
+2026-05-07 17:20:25,048 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:25.048663+00:00
+2026-05-07 17:20:25,199 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.17, h_ratio=1.48)
+2026-05-07 17:20:25,233 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:20:25,664 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.616s at 2026-05-07T23:20:25.664798+00:00
+2026-05-07 17:20:29,831 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:29.831966+00:00
+2026-05-07 17:20:29,986 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.17, h_ratio=1.48)
+2026-05-07 17:20:30,018 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:20:30,460 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.629s at 2026-05-07T23:20:30.460822+00:00
+2026-05-07 17:20:31,763 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:31.763484+00:00
+2026-05-07 17:20:31,886 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
+2026-05-07 17:20:31,929 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:20:32,354 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.591s at 2026-05-07T23:20:32.354006+00:00
+2026-05-07 17:20:33,945 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:33.945098+00:00
+2026-05-07 17:20:34,040 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:20:34,468 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.523s at 2026-05-07T23:20:34.468881+00:00
+2026-05-07 17:20:35,606 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:20:35.606548+00:00
+2026-05-07 17:20:35,728 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
+2026-05-07 17:20:35,776 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:20:36,186 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.580s at 2026-05-07T23:20:36.186410+00:00
+2026-05-07 17:21:19,858 INFO backend.segmentation: [APPLY_TEXTURE] START at 2026-05-07T23:21:19.858037+00:00
+2026-05-07 17:21:19,984 INFO backend.segmentation: [APPLY_TEXTURE] perspective wall tiling applied (w_ratio=1.72, h_ratio=1.98)
+2026-05-07 17:21:20,031 INFO backend.segmentation: [APPLY_TEXTURE] cleared mask from original source: C:\Users\alane\OneDrive\Escritorio\Trabajo\Prueba-PoC\backend\uploads\acm gris.jpg
+2026-05-07 17:21:20,492 INFO backend.segmentation: [APPLY_TEXTURE] DONE 0.633s at 2026-05-07T23:21:20.492075+00:00
+2026-05-07 17:23:17,203 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-07 17:23:17,220 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-07 17:34:54,520 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-07 17:34:54,537 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-07 17:34:55,382 INFO backend.segmentation: [STARTUP] GRADIO_SPACE_URL=http://localhost:7860
+2026-05-07 17:34:55,400 INFO backend.segmentation: [LIFESPAN] GRADIO_SPACE_URL set — skipping local SAM2 load.
+2026-05-07 17:35:53,725 INFO pymongo.serverSelection: {"message": "Waiting for suitable server to become available", "selector": "Primary()", "operation": "find", "topologyDescription": "<TopologyDescription id: 69fd21d97b5fb8b402d113c5, topology_type: ReplicaSetNoPrimary, servers: [<ServerDescription ('ac-tynjizz-shard-00-00.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-01.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>, <ServerDescription ('ac-tynjizz-shard-00-02.n9htwoa.mongodb.net', 27017) server_type: Unknown, rtt: None>]>", "clientId": {"$oid": "69fd21d97b5fb8b402d113c5"}, "remainingTimeMS": 30}
+2026-05-07 17:38:06,088 INFO backend.segmentation: [UPLOAD_BG] START at 2026-05-07T23:38:06.088546+00:00
+2026-05-07 17:38:06,088 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] preparing_image progress=12
+2026-05-07 17:38:06,177 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] segmenting_with_sam2 progress=30 estimated_seconds=58.39104
+2026-05-07 17:38:06,178 INFO services.gradio_client_service: Calling GPU Gradio Space: http://localhost:7860
+2026-05-07 17:38:10,859 INFO httpx: HTTP Request: GET http://localhost:7860/config "HTTP/1.1 200 OK"
+2026-05-07 17:38:13,266 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/info?serialize=False "HTTP/1.1 200 OK"
+2026-05-07 17:38:13,842 INFO httpx: HTTP Request: HEAD https://huggingface.co/api/telemetry/py_client/initiated "HTTP/1.1 200 OK"
+2026-05-07 17:38:15,792 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/heartbeat/9771f2ad-8cd2-4dbb-bf76-dbcaa54a9e8c "HTTP/1.1 200 OK"
+2026-05-07 17:38:15,799 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/upload "HTTP/1.1 200 OK"
+2026-05-07 17:38:18,175 INFO httpx: HTTP Request: POST http://localhost:7860/gradio_api/queue/join "HTTP/1.1 200 OK"
+2026-05-07 17:38:21,015 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/queue/data?session_hash=9771f2ad-8cd2-4dbb-bf76-dbcaa54a9e8c "HTTP/1.1 200 OK"
+2026-05-07 17:39:18,012 INFO httpx: HTTP Request: GET http://localhost:7860/gradio_api/file=C:\Users\alane\AppData\Local\Temp\gradio\e9e23a4c03e9b88d2db6cb764c2778b1091e1c8b97c256c28501ff9297140221\image.webp "HTTP/1.1 200 OK"
+2026-05-07 17:39:18,026 INFO services.gradio_client_service: Gradio Space segmentation: entorno=gpu motor=SAM Auto (GPU - ZeroGPU) mask_count=63
+2026-05-07 17:39:18,026 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] saving_masks progress=92
+2026-05-07 17:39:18,184 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] segments_meta saved (63 segments)
+2026-05-07 17:39:18,184 INFO backend.segmentation: [JOB 1c11e34d2f414d9e9328b1801e210f5a] done mask_count=63
+2026-05-07 17:39:18,184 INFO backend.segmentation: [UPLOAD_BG] DONE 72.097s at 2026-05-07T23:39:18.184964+00:00
+2026-05-07 17:39:18,184 INFO backend.segmentation: Releasing resources (full_unload=False)
diff --git a/backend/main.py b/backend/main.py
index 00ef88c46c9bb07c0d6be505fca3abc7f50cbd04..4124d71f52b02ea7f28f86ba7f8323a94b4a0758 100644
--- a/backend/main.py
+++ b/backend/main.py
@@ -1,176 +1,128 @@
-import mimetypes
-import os
-import subprocess
-import shutil
-import threading
-import time
-from pathlib import Path
-
-from dotenv import load_dotenv
-load_dotenv(Path(__file__).resolve().parent / ".env")
-
-from fastapi import FastAPI, Request
-from fastapi.responses import RedirectResponse, FileResponse
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.staticfiles import StaticFiles
-
-from core.config import logger
-from routers import auth, catalog, media, pages, segmentation, sessions, share, openai_image, active_sessions
-from routers.catalog import seed_catalog
-
-mimetypes.add_type("application/javascript", ".js", strict=True)
-mimetypes.add_type("text/css", ".css", strict=True)
-mimetypes.add_type("image/svg+xml", ".svg", strict=True)
-
-app = FastAPI(title="Hyper Reality Backend")
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["GET", "POST", "PUT", "DELETE", "OPTIONS"],
-    allow_headers=["*"],
-)
-
-
-@app.middleware("http")
-async def remove_x_frame_options(request: Request, call_next):
-    response = await call_next(request)
-    if "x-frame-options" in response.headers:
-        del response.headers["x-frame-options"]
-    response.headers["Content-Security-Policy"] = "frame-ancestors *"
-    return response
-
-
-# Routers
-# Mantener sólo la ruta de subida de imágenes (/api/upload-image).
-# Comentamos las demás inclusiones para deshabilitar funcionalidades
-# posteriores (segmentación, inpainting, sesiones, catálogo, etc.).
-# Re-activar routers necesarios para el frontend
-app.include_router(auth.router)
-app.include_router(media.router)
-app.include_router(pages.router)
-app.include_router(sessions.router)
-app.include_router(segmentation.router)
-app.include_router(openai_image.router)
-app.include_router(active_sessions.router)
-app.include_router(catalog.router)
-
-# Static files
-BASE_DIR = Path(__file__).resolve().parent
-UPLOADS_DIR = BASE_DIR / "uploads"
-FRONTEND_DIST = BASE_DIR.parent / "frontend" / "dist"
-
-UPLOADS_DIR.mkdir(parents=True, exist_ok=True)
-app.mount("/uploads", StaticFiles(directory=UPLOADS_DIR), name="uploads")
-
-if (FRONTEND_DIST / "index.html").exists():
-    # Montar la SPA únicamente en /app (el servidor tiene su propia landing en /)
-    app.mount("/app", StaticFiles(directory=FRONTEND_DIST, html=True), name="frontend_app")
-    # También exponer los assets estáticos en la raíz /assets para que los
-    # archivos generados por Vite (con rutas absolutas `/assets/...`) sean
-    # resueltos correctamente cuando la SPA se carga desde /app.
-    assets_dir = FRONTEND_DIST / "assets"
-    if assets_dir.exists():
-        app.mount("/assets", StaticFiles(directory=assets_dir), name="frontend_assets")
-    # Servir manifest y favicon desde el dist para PWA/links absolutos
-    manifest = FRONTEND_DIST / "manifest.json"
-    favicon = FRONTEND_DIST / "favicon.svg"
-    if manifest.exists():
-        @app.get("/manifest.json")
-        async def _manifest():
-            return FileResponse(str(manifest), media_type="application/manifest+json")
-    if favicon.exists():
-        @app.get("/favicon.svg")
-        async def _favicon():
-            return FileResponse(str(favicon), media_type="image/svg+xml")
-
-# Ruta raíz: servir `backend/home.html` cuando exista (landing del servidor)
-HOME_HTML = BASE_DIR / "home.html"
-if HOME_HTML.exists():
-    @app.get("/")
-    async def _root_home():
-        return FileResponse(str(HOME_HTML), media_type="text/html")
-else:
-    # Si no existe `home.html`, redirigimos a la SPA en /app
-    @app.get("/")
-    async def _root_redirect():
-        return RedirectResponse(url="/app")
-
-
-# Frontend watcher (development helper)
-FRONTEND_DIR = BASE_DIR.parent / "frontend"
-FRONTEND_SRC = FRONTEND_DIR / "src"
-
-
-def scan_frontend_sources() -> dict:
-    if not FRONTEND_SRC.exists():
-        return {}
-    files = {}
-    for path in FRONTEND_SRC.rglob("*"):
-        if path.is_file() and path.suffix in {".ts", ".tsx", ".js", ".jsx", ".css", ".json", ".html"}:
-            files[path] = path.stat().st_mtime
-    for extra in [FRONTEND_DIR / "vite.config.ts", FRONTEND_DIR / "package.json", FRONTEND_DIR / "tsconfig.json"]:
-        if extra.exists():
-            files[extra] = extra.stat().st_mtime
-    return files
-
-
-def run_frontend_build() -> None:
-    if not FRONTEND_DIR.exists():
-        return
-    # Allow disabling automatic frontend builds (useful in production or CI without Node installed)
-    if os.getenv("SKIP_FRONTEND_BUILD", "").lower() in {"1", "true", "yes"}:
-        print("[backend] SKIP_FRONTEND_BUILD is set — skipping frontend build.")
-        return
-
-    npm_path = shutil.which("npm")
-    if not npm_path:
-        print("[backend] npm not found in PATH — skipping frontend build. Install Node.js/npm to enable auto-build or set SKIP_FRONTEND_BUILD=1 to disable this message.")
-        return
-
-    print("[backend] Ejecutando build del frontend...")
-    try:
-        result = subprocess.run([npm_path, "run", "build"], cwd=str(FRONTEND_DIR), capture_output=True, text=True)
-    except FileNotFoundError:
-        print("[backend] Error: npm executable not found when attempting to run build. Skipping frontend build.")
-        return
-
-    if result.returncode != 0:
-        print("[backend] Build falló:")
-        print(result.stdout)
-        print(result.stderr)
-    else:
-        print("[backend] Build completado correctamente.")
-
-
-def watch_frontend_changes(interval: float = 2.0) -> None:
-    last_state = scan_frontend_sources()
-    while True:
-        time.sleep(interval)
-        current_state = scan_frontend_sources()
-        if current_state != last_state:
-            if last_state:
-                print("[backend] Cambio detectado en frontend. Reconstruyendo...")
-                run_frontend_build()
-            last_state = current_state
-
-
-@app.on_event("startup")
-async def startup_seed_catalog():
-    if MONGODB_URI := os.getenv("MONGODB_URI", ""):
-        try:
-            await seed_catalog()
-        except Exception as exc:
-            logger.warning("[STARTUP] seed_catalog falló: %s", exc)
-
-
-@app.on_event("startup")
-async def startup_watch_frontend():
-    thread = threading.Thread(target=watch_frontend_changes, daemon=True)
-    thread.start()
-
-
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000, log_level="info")
+import mimetypes
+import os
+import subprocess
+import threading
+import time
+from pathlib import Path
+
+from dotenv import load_dotenv
+load_dotenv(Path(__file__).resolve().parent / ".env")
+
+from fastapi import FastAPI, Request
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.staticfiles import StaticFiles
+
+from core.config import GRADIO_SPACE_URL, logger
+from routers import auth, catalog, media, pages, segmentation, sessions, share
+from routers.catalog import seed_catalog
+from services.sam2_service import lifespan
+
+mimetypes.add_type("application/javascript", ".js", strict=True)
+mimetypes.add_type("text/css", ".css", strict=True)
+mimetypes.add_type("image/svg+xml", ".svg", strict=True)
+
+logger.info("[STARTUP] GRADIO_SPACE_URL=%s", GRADIO_SPACE_URL or "(not set — using local SAM2)")
+
+app = FastAPI(title="Hyper Reality Backend", lifespan=lifespan)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["GET", "POST", "PUT", "DELETE", "OPTIONS"],
+    allow_headers=["*"],
+)
+
+
+@app.middleware("http")
+async def remove_x_frame_options(request: Request, call_next):
+    response = await call_next(request)
+    if "x-frame-options" in response.headers:
+        del response.headers["x-frame-options"]
+    response.headers["Content-Security-Policy"] = "frame-ancestors *"
+    return response
+
+
+# Routers
+app.include_router(pages.router)
+app.include_router(auth.router)
+app.include_router(share.router)
+app.include_router(media.router)
+app.include_router(catalog.router)
+app.include_router(sessions.router)
+app.include_router(segmentation.router)
+
+# Static files
+BASE_DIR = Path(__file__).resolve().parent
+UPLOADS_DIR = BASE_DIR / "uploads"
+FRONTEND_DIST = BASE_DIR.parent / "frontend" / "dist"
+
+UPLOADS_DIR.mkdir(parents=True, exist_ok=True)
+app.mount("/uploads", StaticFiles(directory=UPLOADS_DIR), name="uploads")
+
+if (FRONTEND_DIST / "index.html").exists():
+    # Montado en "/" como catch-all para SPA — los routers de API tienen prioridad
+    app.mount("/", StaticFiles(directory=FRONTEND_DIST, html=True), name="frontend")
+
+
+# Frontend watcher (development helper)
+FRONTEND_DIR = BASE_DIR.parent / "frontend"
+FRONTEND_SRC = FRONTEND_DIR / "src"
+
+
+def scan_frontend_sources() -> dict:
+    if not FRONTEND_SRC.exists():
+        return {}
+    files = {}
+    for path in FRONTEND_SRC.rglob("*"):
+        if path.is_file() and path.suffix in {".ts", ".tsx", ".js", ".jsx", ".css", ".json", ".html"}:
+            files[path] = path.stat().st_mtime
+    for extra in [FRONTEND_DIR / "vite.config.ts", FRONTEND_DIR / "package.json", FRONTEND_DIR / "tsconfig.json"]:
+        if extra.exists():
+            files[extra] = extra.stat().st_mtime
+    return files
+
+
+def run_frontend_build() -> None:
+    if not FRONTEND_DIR.exists():
+        return
+    print("[backend] Ejecutando build del frontend...")
+    result = subprocess.run(["npm", "run", "build"], cwd=str(FRONTEND_DIR), capture_output=True, text=True)
+    if result.returncode != 0:
+        print("[backend] Build falló:")
+        print(result.stdout)
+        print(result.stderr)
+    else:
+        print("[backend] Build completado correctamente.")
+
+
+def watch_frontend_changes(interval: float = 2.0) -> None:
+    last_state = scan_frontend_sources()
+    while True:
+        time.sleep(interval)
+        current_state = scan_frontend_sources()
+        if current_state != last_state:
+            if last_state:
+                print("[backend] Cambio detectado en frontend. Reconstruyendo...")
+                run_frontend_build()
+            last_state = current_state
+
+
+@app.on_event("startup")
+async def startup_seed_catalog():
+    if MONGODB_URI := os.getenv("MONGODB_URI", ""):
+        try:
+            await seed_catalog()
+        except Exception as exc:
+            logger.warning("[STARTUP] seed_catalog falló: %s", exc)
+
+
+@app.on_event("startup")
+async def startup_watch_frontend():
+    thread = threading.Thread(target=watch_frontend_changes, daemon=True)
+    thread.start()
+
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000, log_level="info")
diff --git a/backend/models/schemas.py b/backend/models/schemas.py
index e11337e242da2a879a7ca3bdbb8703994fc01a18..8dafd515c5368ebdb39978c249fa96179c2ebc7a 100644
--- a/backend/models/schemas.py
+++ b/backend/models/schemas.py
@@ -112,7 +112,5 @@ class ApplyColorRequest(BaseModel):
 class ApplyTextureAIRequest(BaseModel):
     filename: str
     original_filename: str = ""
-    mask_filename: str = ""
+    mask_filename: str
     prompt: str = ""
-    texture_name: str = ""
-
diff --git a/backend/preview.html b/backend/preview.html
index bee7cabdbf05d5d4939926995555a667304a99c7..382e6c185500c2dca6c5f565c3b73ca378b87a38 100644
--- a/backend/preview.html
+++ b/backend/preview.html
@@ -1,242 +1,242 @@
-<!doctype html>
-<html lang="es">
-  <head>
-    <meta charset="UTF-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Vista previa del app</title>
-    <script src="https://cdn.tailwindcss.com"></script>
-  </head>
-  <body class="bg-slate-100 text-slate-900">
-    <div class="max-w-5xl mx-auto p-6 space-y-6">
-      <header class="flex items-center justify-between gap-4">
-        <div>
-          <h1 class="text-3xl font-bold">Vista previa del app</h1>
-          <p class="text-slate-600">
-            Aquí puedes ver cómo se despliega el visualizador con una API key de
-            ejemplo.
-          </p>
-        </div>
-        <a
-          href="/admin"
-          class="px-4 py-2 bg-slate-800 text-white rounded-xl hover:bg-slate-900"
-          >Ir al panel</a
-        >
-      </header>
-
-      <div
-        class="rounded-3xl overflow-hidden border border-slate-200 shadow-lg"
-      >
-        <iframe
-          id="preview-iframe"
-          src=""
-          class="w-full min-h-[600px] border-0"
-        ></iframe>
-      </div>
-      <div class="rounded-3xl bg-white p-6 shadow-lg">
-        <h2 class="text-xl font-semibold mb-3">Puente de desarrollo</h2>
-        <p class="text-slate-700 mb-4">
-          Esta vista previa se conecta con el app React embebido. Puedes enviar
-          comandos y ver las respuestas del iframe.
-        </p>
-        <div class="grid gap-4 md:grid-cols-2 mb-4">
-          <div>
-            <label class="block text-sm font-medium text-slate-700 mb-2">
-              Cliente de prueba
-            </label>
-            <select
-              id="client-select"
-              class="w-full rounded-2xl border border-slate-300 px-4 py-3"
-            >
-              <option value="ID_UNICO_DEL_CLIENTE_001">
-                ID_UNICO_DEL_CLIENTE_001
-              </option>
-            </select>
-          </div>
-          <div>
-            <label class="block text-sm font-medium text-slate-700 mb-2">
-              Comando personalizado
-            </label>
-            <input
-              id="custom-command"
-              type="text"
-              placeholder="Ej. set-color:#f97316"
-              class="w-full rounded-2xl border border-slate-300 px-4 py-3"
-            />
-          </div>
-        </div>
-        <div class="flex flex-wrap gap-3 mb-4">
-          <button
-            id="load-client"
-            class="px-4 py-2 bg-indigo-600 text-white rounded-xl hover:bg-indigo-700"
-          >
-            Cargar cliente seleccionado
-          </button>
-          <button
-            id="send-ping"
-            class="px-4 py-2 bg-blue-600 text-white rounded-xl hover:bg-blue-700"
-          >
-            Enviar ping
-          </button>
-          <button
-            id="request-status"
-            class="px-4 py-2 bg-slate-200 text-slate-900 rounded-xl hover:bg-slate-300"
-          >
-            Pedir estado al app
-          </button>
-          <button
-            id="send-custom"
-            class="px-4 py-2 bg-green-600 text-white rounded-xl hover:bg-green-700"
-          >
-            Enviar comando
-          </button>
-        </div>
-        <div
-          id="bridge-log"
-          class="rounded-2xl border border-slate-200 bg-slate-50 p-4 text-slate-700 h-52 overflow-y-auto"
-        ></div>
-      </div>
-      <script>
-        const iframe = document.getElementById("preview-iframe");
-        const bridgeLog = document.getElementById("bridge-log");
-        const clientSelect = document.getElementById("client-select");
-        const customCommand = document.getElementById("custom-command");
-
-        function addLog(message) {
-          const item = document.createElement("div");
-          item.className = "text-sm mb-2";
-          item.textContent = message;
-          bridgeLog.appendChild(item);
-          bridgeLog.scrollTop = bridgeLog.scrollHeight;
-        }
-
-        async function loadClients() {
-          try {
-            const res = await fetch("/api/keys");
-            const data = await res.json();
-            if (!res.ok) {
-              throw new Error(data.error || "No se pudo cargar los clientes.");
-            }
-            clientSelect.innerHTML = data.keys
-              .map(
-                (key) =>
-                  `<option value="${key.client_id}">${key.client_id} - ${key.nombre}</option>`,
-              )
-              .join("");
-            addLog(`Clientes cargados: ${data.keys.length}`);
-          } catch (error) {
-            addLog(`Error al cargar clientes: ${error.message || error}`);
-          }
-        }
-
-        async function checkEnvironment() {
-          try {
-            const res = await fetch("/health");
-            const data = await res.json();
-            if (!res.ok || !data.frontend_ready) {
-              addLog(
-                "Ambiente no listo: asegúrate de tener backend y frontend levantados.",
-              );
-              return false;
-            }
-            addLog("Ambiente OK: backend y frontend están levantados.");
-            return true;
-          } catch (error) {
-            addLog(
-              "No se pudo verificar el ambiente. El backend debe estar corriendo.",
-            );
-            return false;
-          }
-        }
-
-        async function loadPreviewToken() {
-          const backendOk = await checkEnvironment();
-          if (!backendOk) return;
-          const clientId = clientSelect.value || "ID_UNICO_DEL_CLIENTE_001";
-          try {
-            const res = await fetch("/api/token", {
-              method: "POST",
-              headers: { "Content-Type": "application/x-www-form-urlencoded" },
-              body: `client_id=${encodeURIComponent(clientId)}`,
-            });
-            const data = await res.json();
-            if (!res.ok) {
-              throw new Error(data.error || "No se pudo generar token.");
-            }
-            iframe.src = `/app?token=${encodeURIComponent(data.token)}`;
-            addLog(`Token generado para ${clientId}`);
-          } catch (error) {
-            addLog(`Error generando token: ${error.message || error}`);
-          }
-        }
-
-        function sendBridgeCommand(command, payload) {
-          if (!iframe.contentWindow) {
-            addLog("El iframe aún no está listo.");
-            return;
-          }
-          iframe.contentWindow.postMessage(
-            { type: "preview-command", command, payload },
-            "*",
-          );
-          addLog(
-            `Enviado comando al app: ${command}${payload ? ` ${JSON.stringify(payload)}` : ""}`,
-          );
-        }
-
-        window.addEventListener("message", (event) => {
-          if (event.source !== iframe.contentWindow) return;
-          const data = event.data;
-          if (!data || typeof data !== "object") return;
-
-          if (data.type === "saas-session-active") {
-            addLog(`React indicó sesión activa: ${data.nombreCliente}`);
-          }
-          if (data.type === "app-loaded") {
-            addLog(`React cargado con cliente: ${data.clientId}`);
-          }
-          if (data.type === "preview-response") {
-            addLog(`React responde: ${JSON.stringify(data)}`);
-          }
-        });
-
-        document.getElementById("load-client").addEventListener("click", () => {
-          loadPreviewToken();
-        });
-
-        document.getElementById("send-ping").addEventListener("click", () => {
-          sendBridgeCommand("ping");
-        });
-
-        document
-          .getElementById("request-status")
-          .addEventListener("click", () => {
-            sendBridgeCommand("status");
-          });
-
-        document.getElementById("send-custom").addEventListener("click", () => {
-          const commandText = customCommand.value.trim();
-          if (!commandText) {
-            addLog("Ingresa un comando personalizado.");
-            return;
-          }
-          const [command, payloadString] = commandText.split(":", 2);
-          let payload;
-          if (payloadString) {
-            payload = { value: payloadString };
-          }
-          sendBridgeCommand(command, payload);
-        });
-
-        loadClients().then(loadPreviewToken);
-      </script>
-
-      <div class="rounded-3xl bg-white p-6 shadow-lg">
-        <h2 class="text-xl font-semibold mb-3">Nota</h2>
-        <p class="text-slate-700">
-          Esta vista previa genera un token de acceso para el cliente
-          <strong>ID_UNICO_DEL_CLIENTE_001</strong> y carga el app con él.
-        </p>
-      </div>
-    </div>
-  </body>
-</html>
+<!doctype html>
+<html lang="es">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>Vista previa del app</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+  </head>
+  <body class="bg-slate-100 text-slate-900">
+    <div class="max-w-5xl mx-auto p-6 space-y-6">
+      <header class="flex items-center justify-between gap-4">
+        <div>
+          <h1 class="text-3xl font-bold">Vista previa del app</h1>
+          <p class="text-slate-600">
+            Aquí puedes ver cómo se despliega el visualizador con una API key de
+            ejemplo.
+          </p>
+        </div>
+        <a
+          href="/admin"
+          class="px-4 py-2 bg-slate-800 text-white rounded-xl hover:bg-slate-900"
+          >Ir al panel</a
+        >
+      </header>
+
+      <div
+        class="rounded-3xl overflow-hidden border border-slate-200 shadow-lg"
+      >
+        <iframe
+          id="preview-iframe"
+          src=""
+          class="w-full min-h-[600px] border-0"
+        ></iframe>
+      </div>
+      <div class="rounded-3xl bg-white p-6 shadow-lg">
+        <h2 class="text-xl font-semibold mb-3">Puente de desarrollo</h2>
+        <p class="text-slate-700 mb-4">
+          Esta vista previa se conecta con el app React embebido. Puedes enviar
+          comandos y ver las respuestas del iframe.
+        </p>
+        <div class="grid gap-4 md:grid-cols-2 mb-4">
+          <div>
+            <label class="block text-sm font-medium text-slate-700 mb-2">
+              Cliente de prueba
+            </label>
+            <select
+              id="client-select"
+              class="w-full rounded-2xl border border-slate-300 px-4 py-3"
+            >
+              <option value="ID_UNICO_DEL_CLIENTE_001">
+                ID_UNICO_DEL_CLIENTE_001
+              </option>
+            </select>
+          </div>
+          <div>
+            <label class="block text-sm font-medium text-slate-700 mb-2">
+              Comando personalizado
+            </label>
+            <input
+              id="custom-command"
+              type="text"
+              placeholder="Ej. set-color:#f97316"
+              class="w-full rounded-2xl border border-slate-300 px-4 py-3"
+            />
+          </div>
+        </div>
+        <div class="flex flex-wrap gap-3 mb-4">
+          <button
+            id="load-client"
+            class="px-4 py-2 bg-indigo-600 text-white rounded-xl hover:bg-indigo-700"
+          >
+            Cargar cliente seleccionado
+          </button>
+          <button
+            id="send-ping"
+            class="px-4 py-2 bg-blue-600 text-white rounded-xl hover:bg-blue-700"
+          >
+            Enviar ping
+          </button>
+          <button
+            id="request-status"
+            class="px-4 py-2 bg-slate-200 text-slate-900 rounded-xl hover:bg-slate-300"
+          >
+            Pedir estado al app
+          </button>
+          <button
+            id="send-custom"
+            class="px-4 py-2 bg-green-600 text-white rounded-xl hover:bg-green-700"
+          >
+            Enviar comando
+          </button>
+        </div>
+        <div
+          id="bridge-log"
+          class="rounded-2xl border border-slate-200 bg-slate-50 p-4 text-slate-700 h-52 overflow-y-auto"
+        ></div>
+      </div>
+      <script>
+        const iframe = document.getElementById("preview-iframe");
+        const bridgeLog = document.getElementById("bridge-log");
+        const clientSelect = document.getElementById("client-select");
+        const customCommand = document.getElementById("custom-command");
+
+        function addLog(message) {
+          const item = document.createElement("div");
+          item.className = "text-sm mb-2";
+          item.textContent = message;
+          bridgeLog.appendChild(item);
+          bridgeLog.scrollTop = bridgeLog.scrollHeight;
+        }
+
+        async function loadClients() {
+          try {
+            const res = await fetch("/api/keys");
+            const data = await res.json();
+            if (!res.ok) {
+              throw new Error(data.error || "No se pudo cargar los clientes.");
+            }
+            clientSelect.innerHTML = data.keys
+              .map(
+                (key) =>
+                  `<option value="${key.client_id}">${key.client_id} - ${key.nombre}</option>`,
+              )
+              .join("");
+            addLog(`Clientes cargados: ${data.keys.length}`);
+          } catch (error) {
+            addLog(`Error al cargar clientes: ${error.message || error}`);
+          }
+        }
+
+        async function checkEnvironment() {
+          try {
+            const res = await fetch("/health");
+            const data = await res.json();
+            if (!res.ok || !data.frontend_ready) {
+              addLog(
+                "Ambiente no listo: asegúrate de tener backend y frontend levantados.",
+              );
+              return false;
+            }
+            addLog("Ambiente OK: backend y frontend están levantados.");
+            return true;
+          } catch (error) {
+            addLog(
+              "No se pudo verificar el ambiente. El backend debe estar corriendo.",
+            );
+            return false;
+          }
+        }
+
+        async function loadPreviewToken() {
+          const backendOk = await checkEnvironment();
+          if (!backendOk) return;
+          const clientId = clientSelect.value || "ID_UNICO_DEL_CLIENTE_001";
+          try {
+            const res = await fetch("/api/token", {
+              method: "POST",
+              headers: { "Content-Type": "application/x-www-form-urlencoded" },
+              body: `client_id=${encodeURIComponent(clientId)}`,
+            });
+            const data = await res.json();
+            if (!res.ok) {
+              throw new Error(data.error || "No se pudo generar token.");
+            }
+            iframe.src = `/app?token=${encodeURIComponent(data.token)}`;
+            addLog(`Token generado para ${clientId}`);
+          } catch (error) {
+            addLog(`Error generando token: ${error.message || error}`);
+          }
+        }
+
+        function sendBridgeCommand(command, payload) {
+          if (!iframe.contentWindow) {
+            addLog("El iframe aún no está listo.");
+            return;
+          }
+          iframe.contentWindow.postMessage(
+            { type: "preview-command", command, payload },
+            "*",
+          );
+          addLog(
+            `Enviado comando al app: ${command}${payload ? ` ${JSON.stringify(payload)}` : ""}`,
+          );
+        }
+
+        window.addEventListener("message", (event) => {
+          if (event.source !== iframe.contentWindow) return;
+          const data = event.data;
+          if (!data || typeof data !== "object") return;
+
+          if (data.type === "saas-session-active") {
+            addLog(`React indicó sesión activa: ${data.nombreCliente}`);
+          }
+          if (data.type === "app-loaded") {
+            addLog(`React cargado con cliente: ${data.clientId}`);
+          }
+          if (data.type === "preview-response") {
+            addLog(`React responde: ${JSON.stringify(data)}`);
+          }
+        });
+
+        document.getElementById("load-client").addEventListener("click", () => {
+          loadPreviewToken();
+        });
+
+        document.getElementById("send-ping").addEventListener("click", () => {
+          sendBridgeCommand("ping");
+        });
+
+        document
+          .getElementById("request-status")
+          .addEventListener("click", () => {
+            sendBridgeCommand("status");
+          });
+
+        document.getElementById("send-custom").addEventListener("click", () => {
+          const commandText = customCommand.value.trim();
+          if (!commandText) {
+            addLog("Ingresa un comando personalizado.");
+            return;
+          }
+          const [command, payloadString] = commandText.split(":", 2);
+          let payload;
+          if (payloadString) {
+            payload = { value: payloadString };
+          }
+          sendBridgeCommand(command, payload);
+        });
+
+        loadClients().then(loadPreviewToken);
+      </script>
+
+      <div class="rounded-3xl bg-white p-6 shadow-lg">
+        <h2 class="text-xl font-semibold mb-3">Nota</h2>
+        <p class="text-slate-700">
+          Esta vista previa genera un token de acceso para el cliente
+          <strong>ID_UNICO_DEL_CLIENTE_001</strong> y carga el app con él.
+        </p>
+      </div>
+    </div>
+  </body>
+</html>
diff --git a/backend/requirements.txt b/backend/requirements.txt
index 9cdd6f80918e68712eb7a2223f6323bb95d490bc..3175b21c48e925ab26cc56aff8037f1b7054dea8 100644
--- a/backend/requirements.txt
+++ b/backend/requirements.txt
@@ -9,4 +9,3 @@ pydantic
 python-multipart
 gradio_client
 opencv-python-headless
-openai
diff --git a/backend/routers/auth.py b/backend/routers/auth.py
index 974d50bbe63f179d8125a217fe291f5745b546e3..3035696dae49b1393b46b569662febb7ee2a9aa6 100644
--- a/backend/routers/auth.py
+++ b/backend/routers/auth.py
@@ -21,7 +21,7 @@ def _get_col():
     global _client, _db, _col
     if _col is None:
         if not MONGODB_URI:
-            return None
+            raise RuntimeError("MONGODB_URI no configurado")
         _client = AsyncIOMotorClient(MONGODB_URI)
         _db = _client["hyper_reality"]
         _col = _db["clients"]
@@ -87,14 +87,6 @@ async def startup():
 
 @router.post("/api/token")
 async def token(client_id: str = Form(...)):
-    if not MONGODB_URI:
-        # fallback in-memory lookup
-        doc = next((c for c in _DEFAULT_CLIENTS if c["_id"] == client_id), None)
-        if not doc:
-            return JSONResponse(content={"error": "client_id inválido"}, status_code=400)
-        tok = generate_token_for_client(client_id)
-        return JSONResponse(content={"token": tok, "expires_in": TOKEN_TTL})
-
     col = _get_col()
     doc = await col.find_one({"_id": client_id})
     if not doc:
@@ -111,13 +103,10 @@ async def config(client_id: str = Query(None), token: str = Query(None)):
             return JSONResponse(content={"error": "token inválido o expirado"}, status_code=401)
     if not client_id:
         return JSONResponse(content={"error": "client_id o token requerido"}, status_code=400)
-    if not MONGODB_URI:
-        doc = next((c for c in _DEFAULT_CLIENTS if c["_id"] == client_id), None)
-        datos = doc or {"nombre": "Cliente Desconocido", "color_primario": "#f97316", "created_at": _now_iso()}
-    else:
-        col = _get_col()
-        doc = await col.find_one({"_id": client_id})
-        datos = doc or {"nombre": "Cliente Desconocido", "color_primario": "#f97316", "created_at": _now_iso()}
+
+    col = _get_col()
+    doc = await col.find_one({"_id": client_id})
+    datos = doc or {"nombre": "Cliente Desconocido", "color_primario": "#f97316", "created_at": _now_iso()}
     datos.pop("_id", None)
     ACTIVE_SESSIONS[client_id] = _now_iso()
     return JSONResponse(content={"client_id": client_id, **datos})
@@ -137,18 +126,6 @@ async def session_start(client_id: str = Form(None), token: str = Form(None)):
 
 @router.get("/api/keys")
 async def api_keys():
-    if not MONGODB_URI:
-        keys = [
-            {
-                "client_id": d["_id"],
-                "nombre": d.get("nombre", ""),
-                "color_primario": d.get("color_primario", ""),
-                "created_at": d.get("created_at", ""),
-            }
-            for d in _DEFAULT_CLIENTS
-        ]
-        return JSONResponse(content={"keys": keys, "count": len(keys)})
-
     col = _get_col()
     docs = await col.find({}).to_list(length=500)
     keys = [
@@ -167,11 +144,8 @@ async def api_keys():
 async def generate_key(request: Request, nombre: str = Form(...), color_primario: str = Form("#8b5cf6")):
     new_key = f"CLIENTE_{uuid4().hex[:8].upper()}"
     doc = {"_id": new_key, "nombre": nombre, "color_primario": color_primario, "created_at": _now_iso()}
-    if not MONGODB_URI:
-        _DEFAULT_CLIENTS.append(doc)
-    else:
-        col = _get_col()
-        await col.insert_one(doc)
+    col = _get_col()
+    await col.insert_one(doc)
     base_url = str(request.base_url).rstrip("/")
     if request.headers.get("x-forwarded-proto") == "https" and base_url.startswith("http://"):
         base_url = "https://" + base_url[7:]
@@ -190,13 +164,6 @@ async def generate_key(request: Request, nombre: str = Form(...), color_primario
 
 @router.delete("/api/keys/{client_id}")
 async def delete_key(client_id: str):
-    if not MONGODB_URI:
-        before = len(_DEFAULT_CLIENTS)
-        _DEFAULT_CLIENTS[:] = [c for c in _DEFAULT_CLIENTS if c["_id"] != client_id]
-        if len(_DEFAULT_CLIENTS) == before:
-            return JSONResponse(content={"error": "client_id no encontrado"}, status_code=404)
-        return JSONResponse(content={"status": "eliminado", "client_id": client_id})
-
     col = _get_col()
     result = await col.delete_one({"_id": client_id})
     if result.deleted_count == 0:
diff --git a/backend/routers/catalog.py b/backend/routers/catalog.py
index 978c6be94108390b28ea660ab7387774ebeb0730..d13e3edd80331a3a2cea6c1abefb92d794d54e8c 100644
--- a/backend/routers/catalog.py
+++ b/backend/routers/catalog.py
@@ -1,240 +1,240 @@
-import os
-from datetime import datetime
-
-from fastapi import APIRouter
-from fastapi.responses import JSONResponse
-from motor.motor_asyncio import AsyncIOMotorClient
-from pydantic import BaseModel
-
-router = APIRouter(prefix="/api/catalog")
-
-MONGODB_URI = os.getenv("MONGODB_URI", "")
-_client: AsyncIOMotorClient | None = None
-_db = None
-_col = None
-
-
-def _get_col():
-    global _client, _db, _col
-    if _col is None:
-        if not MONGODB_URI:
-            raise RuntimeError("MONGODB_URI no configurado")
-        _client = AsyncIOMotorClient(MONGODB_URI)
-        _db = _client["hyper_reality"]
-        _col = _db["catalog"]
-    return _col
-
-
-# ── Datos iniciales (se insertan solo si la colección está vacía) ─────────────
-_SEED = [
-    {
-        "_id": "acm",
-        "nombre": "ACM (Aluminio Compuesto)",
-        "tipo": "paredes",
-        "descripcion": "Paneles de aluminio compuesto para fachadas y exteriores",
-        "especificaciones": [
-            "Espesor de ACM 4mm.",
-            "Medida 1.22m x 2.44m",
-            "Facil Mantenimiento.",
-            "Espesor de Aluminio 0.40mm.",
-            "Se puede doblar o biselar",
-        ],
-        "url_detalle": "https://heyzine.com/flip-book/447fe3eb8e.html#page/16",
-        "productos": [
-            {"id": "acm_white",       "nombre": "Glossy White",     "textura": "Texture_ACM/ACM_White.png",          "url_preview": "/seg/texture-preview/Texture_ACM/ACM_White.png",          "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_amarillo",    "nombre": "Amarillo",          "textura": "Texture_ACM/ACM_Amarillo.png",       "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Amarillo.png",       "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_orange",      "nombre": "Glossy Orange",     "textura": "Texture_ACM/ACM_Orange.png",         "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Orange.png",         "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_red",         "nombre": "Glossy Red",        "textura": "Texture_ACM/ACM_Glossy_Red.png",    "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Glossy_Red.png",    "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_light_blue",  "nombre": "Light Blue",        "textura": "Texture_ACM/ACM_Light_Blue.png",     "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Light_Blue.png",     "dimensiones": ["1.22x2.44"]},
-            {"id": "acm_azul",        "nombre": "Azul",              "textura": "Texture_ACM/ACM_Azul.png",           "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Azul.png",           "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_verde_hn",    "nombre": "Verde HN",          "textura": "Texture_ACM/ACM_Verde_HN.png",       "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Verde_HN.png",       "dimensiones": ["1.22x2.44"]},
-            {"id": "acm_verde_lima",  "nombre": "Verde Lima",        "textura": "Texture_ACM/ACM_Verde_Lima.png",     "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Verde_Lima.png",     "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_verde",       "nombre": "Verde",             "textura": "Texture_ACM/ACM_Verde.png",          "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Verde.png",          "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_madera_clara","nombre": "Madera Clara",      "textura": "Texture_ACM/ACM_Madera_Clara.png",   "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Madera_Clara.png",   "dimensiones": ["1.22x2.44"]},
-            {"id": "acm_roble",       "nombre": "Roble (Oak)",       "textura": "Texture_ACM/ACM_ROBLE(OAK).png",    "url_preview": "/seg/texture-preview/Texture_ACM/ACM_ROBLE(OAK).png",    "dimensiones": ["1.22x2.44"]},
-            {"id": "acm_grafito",     "nombre": "Grafito",           "textura": "Texture_ACM/ACM_Grafito.png",        "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Grafito.png",        "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_metalic",     "nombre": "Silver Metallic",   "textura": "Texture_ACM/ACM_Metalic.png",        "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Metalic.png",        "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_mouse_grey",  "nombre": "Mouse Grey",        "textura": "Texture_ACM/ACM_MouseGrey.png",      "url_preview": "/seg/texture-preview/Texture_ACM/ACM_MouseGrey.png",      "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_matte_black", "nombre": "Matte Black",       "textura": "Texture_ACM/ACM_Matteblack.png",    "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Matteblack.png",    "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-            {"id": "acm_glossy_black","nombre": "Glossy Black",      "textura": "Texture_ACM/ACM_Glossy_Black.png",  "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Glossy_Black.png",  "dimensiones": ["1.22x2.44", "1.50x4.98"]},
-        ],
-        "created_at": "2026-04-20T00:00:00Z",
-    },
-    {
-        "_id": "wpc",
-        "nombre": "WPC (Exterior e Interior)",
-        "tipo": "paredes",
-        "descripcion": "Los paneles de WPC se utilizan como revestimiento decorativo para paredes. No se deforma, no requiere mantenimiento constante y tiene mayor durabilidad. Crea mayor estetica e instalacion rapida.",
-        "especificaciones": [
-            "Revestimiento decorativo para paredes.",
-            "No se deforma ni requiere mantenimiento constante.",
-            "Mayor durabilidad y estetica.",
-            "Instalacion rapida.",
-            "Ideal para: sala principal (pared protagonista), comedor, interior de oficina, pasillo o entradas.",
-        ],
-        "url_detalle": "https://heyzine.com/flip-book/447fe3eb8e.html#page/39",
-        "productos": [
-            {"id": "WPC_madera_oscuro", "nombre": "WPC Madera Oscuro", "textura": "Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_oscuro.png", "url_preview": "/seg/texture-preview/Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_oscuro.png", "dimensiones": ["2.90x0.25"]},
-            {"id": "WPC_madera_claro",  "nombre": "WPC Madera Claro",  "textura": "Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_claro.png",  "url_preview": "/seg/texture-preview/Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_claro.png",  "dimensiones": ["2.90x0.25"]},
-            {"id": "WPC_madera_gris",   "nombre": "WPC Madera Gris",   "textura": "Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_gris.png",   "url_preview": "/seg/texture-preview/Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_gris.png",   "dimensiones": ["2.90x0.25"]},
-            {"id": "WPC_negro",         "nombre": "WPC Negro",          "textura": "Texture_WPC_EXTERIOR_INTERIOR/WPC_negro.png",          "url_preview": "/seg/texture-preview/Texture_WPC_EXTERIOR_INTERIOR/WPC_negro.png",          "dimensiones": ["2.90x0.25"]},
-        ],
-        "created_at": "2026-05-07T00:00:00Z",
-    },
-    {
-        "_id": "wpc_deck",
-        "nombre": "WPC Deck",
-        "tipo": "suelos",
-        "descripcion": "Deck de WPC para exteriores e interiores. Ideal para terrazas, jardines, bordes de piscina y espacios al aire libre.",
-        "especificaciones": [
-            "Resistencia a la intemperie.",
-            "Bajo mantenimiento.",
-            "Respetuosa con el medio ambiente.",
-            "Esteticamente agradable.",
-        ],
-        "url_detalle": "https://heyzine.com/flip-book/447fe3eb8e.html#page/38",
-        "productos": [
-            {"id": "DECK_madera",        "nombre": "Deck Madera",        "textura": "Texture_WPC_DECK/DECK_madera.png",        "url_preview": "/seg/texture-preview/Texture_WPC_DECK/DECK_madera.png",        "dimensiones": ["2.90x0.14"]},
-            {"id": "DECK_madera_oscuro", "nombre": "Deck Madera Oscuro", "textura": "Texture_WPC_DECK/DECK_madera_oscuro.png", "url_preview": "/seg/texture-preview/Texture_WPC_DECK/DECK_madera_oscuro.png", "dimensiones": ["2.90x0.14"]},
-            {"id": "DECK_gris",          "nombre": "Deck Gris",           "textura": "Texture_WPC_DECK/DECK_gris.png",          "url_preview": "/seg/texture-preview/Texture_WPC_DECK/DECK_gris.png",          "dimensiones": ["2.90x0.14"]},
-        ],
-        "created_at": "2026-05-08T00:00:00Z",
-    },
-]
-
-
-async def seed_catalog() -> None:
-    col = _get_col()
-    count = await col.count_documents({})
-    if count == 0:
-        await col.insert_many(_SEED)
-        return
-
-    # Migrar documentos existentes: añadir campos que falten según _SEED
-    for seed_item in _SEED:
-        doc = await col.find_one({"_id": seed_item["_id"]})
-        if not doc:
-            continue
-        patch = {k: v for k, v in seed_item.items() if k not in doc and k != "_id"}
-        if patch:
-            await col.update_one({"_id": seed_item["_id"]}, {"$set": patch})
-
-
-def _serialize(doc: dict) -> dict:
-    out = dict(doc)
-    out["id"] = str(out.pop("_id"))
-    return out
-
-
-def _seed_as_response() -> list[dict]:
-    return [{**{k: v for k, v in item.items() if k != "_id"}, "id": item["_id"]} for item in _SEED]
-
-
-# ── Endpoints de lectura ──────────────────────────────────────────────────────
-
-@router.get("/textures")
-async def get_texture_catalog() -> JSONResponse:
-    try:
-        col = _get_col()
-        docs = await col.find({}).to_list(length=200)
-        if docs:
-            return JSONResponse(content={"categories": [_serialize(d) for d in docs]})
-    except Exception:
-        pass
-    # Fallback a datos estáticos si MongoDB no está disponible o la colección está vacía
-    return JSONResponse(content={"categories": _seed_as_response()})
-
-
-@router.get("/textures/{category_id}")
-async def get_texture_category(category_id: str) -> JSONResponse:
-    try:
-        col = _get_col()
-        doc = await col.find_one({"_id": category_id})
-        if doc:
-            return JSONResponse(content=_serialize(doc))
-    except Exception:
-        pass
-    fallback = next((item for item in _SEED if item["_id"] == category_id), None)
-    if fallback:
-        return JSONResponse(content=_seed_as_response()[_SEED.index(fallback)])
-    return JSONResponse(content={"detail": f"Categoria '{category_id}' no encontrada"}, status_code=404)
-
-
-# ── Modelos ───────────────────────────────────────────────────────────────────
-
-class ProductoItem(BaseModel):
-    id: str
-    nombre: str
-    textura: str
-    url_preview: str
-    dimensiones: list[str] = []
-
-
-class CategoriaBody(BaseModel):
-    id: str
-    nombre: str
-    tipo: str = "paredes"
-    descripcion: str = ""
-    especificaciones: list[str] = []
-    url_detalle: str = ""
-    productos: list[ProductoItem] = []
-
-
-# ── Endpoints de escritura ────────────────────────────────────────────────────
-
-@router.post("/category")
-async def add_category(body: CategoriaBody) -> JSONResponse:
-    col = _get_col()
-    existing = await col.find_one({"_id": body.id})
-    if existing:
-        return JSONResponse(content={"error": f"Categoria '{body.id}' ya existe"}, status_code=409)
-    doc = body.model_dump()
-    doc["_id"] = doc.pop("id")
-    doc["created_at"] = datetime.utcnow().isoformat() + "Z"
-    await col.insert_one(doc)
-    return JSONResponse(content={"ok": True, "id": body.id}, status_code=201)
-
-
-@router.put("/category/{category_id}")
-async def update_category(category_id: str, body: CategoriaBody) -> JSONResponse:
-    col = _get_col()
-    doc = body.model_dump()
-    doc.pop("id", None)
-    doc["updated_at"] = datetime.utcnow().isoformat() + "Z"
-    result = await col.update_one({"_id": category_id}, {"$set": doc})
-    if result.matched_count == 0:
-        return JSONResponse(content={"error": "Categoria no encontrada"}, status_code=404)
-    return JSONResponse(content={"ok": True})
-
-
-@router.delete("/category/{category_id}")
-async def delete_category(category_id: str) -> JSONResponse:
-    col = _get_col()
-    result = await col.delete_one({"_id": category_id})
-    if result.deleted_count == 0:
-        return JSONResponse(content={"error": "Categoria no encontrada"}, status_code=404)
-    return JSONResponse(content={"ok": True, "deleted": category_id})
-
-
-@router.post("/category/{category_id}/product")
-async def add_product(category_id: str, product: ProductoItem) -> JSONResponse:
-    col = _get_col()
-    result = await col.update_one(
-        {"_id": category_id, "productos.id": {"$ne": product.id}},
-        {"$push": {"productos": product.model_dump()}, "$set": {"updated_at": datetime.utcnow().isoformat() + "Z"}},
-    )
-    if result.matched_count == 0:
-        return JSONResponse(content={"error": "Categoria no encontrada o producto duplicado"}, status_code=409)
-    return JSONResponse(content={"ok": True}, status_code=201)
-
-
-@router.delete("/category/{category_id}/product/{product_id}")
-async def delete_product(category_id: str, product_id: str) -> JSONResponse:
-    col = _get_col()
-    result = await col.update_one(
-        {"_id": category_id},
-        {"$pull": {"productos": {"id": product_id}}, "$set": {"updated_at": datetime.utcnow().isoformat() + "Z"}},
-    )
-    if result.matched_count == 0:
-        return JSONResponse(content={"error": "Categoria no encontrada"}, status_code=404)
-    return JSONResponse(content={"ok": True})
+import os
+from datetime import datetime
+
+from fastapi import APIRouter
+from fastapi.responses import JSONResponse
+from motor.motor_asyncio import AsyncIOMotorClient
+from pydantic import BaseModel
+
+router = APIRouter(prefix="/api/catalog")
+
+MONGODB_URI = os.getenv("MONGODB_URI", "")
+_client: AsyncIOMotorClient | None = None
+_db = None
+_col = None
+
+
+def _get_col():
+    global _client, _db, _col
+    if _col is None:
+        if not MONGODB_URI:
+            raise RuntimeError("MONGODB_URI no configurado")
+        _client = AsyncIOMotorClient(MONGODB_URI)
+        _db = _client["hyper_reality"]
+        _col = _db["catalog"]
+    return _col
+
+
+# ── Datos iniciales (se insertan solo si la colección está vacía) ─────────────
+_SEED = [
+    {
+        "_id": "acm",
+        "nombre": "ACM (Aluminio Compuesto)",
+        "tipo": "paredes",
+        "descripcion": "Paneles de aluminio compuesto para fachadas y exteriores",
+        "especificaciones": [
+            "Espesor de ACM 4mm.",
+            "Medida 1.22m x 2.44m",
+            "Facil Mantenimiento.",
+            "Espesor de Aluminio 0.40mm.",
+            "Se puede doblar o biselar",
+        ],
+        "url_detalle": "https://heyzine.com/flip-book/447fe3eb8e.html#page/16",
+        "productos": [
+            {"id": "acm_white",       "nombre": "Glossy White",     "textura": "Texture_ACM/ACM_White.png",          "url_preview": "/seg/texture-preview/Texture_ACM/ACM_White.png",          "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_amarillo",    "nombre": "Amarillo",          "textura": "Texture_ACM/ACM_Amarillo.png",       "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Amarillo.png",       "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_orange",      "nombre": "Glossy Orange",     "textura": "Texture_ACM/ACM_Orange.png",         "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Orange.png",         "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_red",         "nombre": "Glossy Red",        "textura": "Texture_ACM/ACM_Glossy_Red.png",    "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Glossy_Red.png",    "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_light_blue",  "nombre": "Light Blue",        "textura": "Texture_ACM/ACM_Light_Blue.png",     "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Light_Blue.png",     "dimensiones": ["1.22x2.44"]},
+            {"id": "acm_azul",        "nombre": "Azul",              "textura": "Texture_ACM/ACM_Azul.png",           "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Azul.png",           "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_verde_hn",    "nombre": "Verde HN",          "textura": "Texture_ACM/ACM_Verde_HN.png",       "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Verde_HN.png",       "dimensiones": ["1.22x2.44"]},
+            {"id": "acm_verde_lima",  "nombre": "Verde Lima",        "textura": "Texture_ACM/ACM_Verde_Lima.png",     "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Verde_Lima.png",     "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_verde",       "nombre": "Verde",             "textura": "Texture_ACM/ACM_Verde.png",          "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Verde.png",          "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_madera_clara","nombre": "Madera Clara",      "textura": "Texture_ACM/ACM_Madera_Clara.png",   "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Madera_Clara.png",   "dimensiones": ["1.22x2.44"]},
+            {"id": "acm_roble",       "nombre": "Roble (Oak)",       "textura": "Texture_ACM/ACM_ROBLE(OAK).png",    "url_preview": "/seg/texture-preview/Texture_ACM/ACM_ROBLE(OAK).png",    "dimensiones": ["1.22x2.44"]},
+            {"id": "acm_grafito",     "nombre": "Grafito",           "textura": "Texture_ACM/ACM_Grafito.png",        "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Grafito.png",        "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_metalic",     "nombre": "Silver Metallic",   "textura": "Texture_ACM/ACM_Metalic.png",        "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Metalic.png",        "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_mouse_grey",  "nombre": "Mouse Grey",        "textura": "Texture_ACM/ACM_MouseGrey.png",      "url_preview": "/seg/texture-preview/Texture_ACM/ACM_MouseGrey.png",      "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_matte_black", "nombre": "Matte Black",       "textura": "Texture_ACM/ACM_Matteblack.png",    "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Matteblack.png",    "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+            {"id": "acm_glossy_black","nombre": "Glossy Black",      "textura": "Texture_ACM/ACM_Glossy_Black.png",  "url_preview": "/seg/texture-preview/Texture_ACM/ACM_Glossy_Black.png",  "dimensiones": ["1.22x2.44", "1.50x4.98"]},
+        ],
+        "created_at": "2026-04-20T00:00:00Z",
+    },
+    {
+        "_id": "wpc",
+        "nombre": "WPC (Exterior e Interior)",
+        "tipo": "paredes",
+        "descripcion": "Los paneles de WPC se utilizan como revestimiento decorativo para paredes. No se deforma, no requiere mantenimiento constante y tiene mayor durabilidad. Crea mayor estetica e instalacion rapida.",
+        "especificaciones": [
+            "Revestimiento decorativo para paredes.",
+            "No se deforma ni requiere mantenimiento constante.",
+            "Mayor durabilidad y estetica.",
+            "Instalacion rapida.",
+            "Ideal para: sala principal (pared protagonista), comedor, interior de oficina, pasillo o entradas.",
+        ],
+        "url_detalle": "https://heyzine.com/flip-book/447fe3eb8e.html#page/39",
+        "productos": [
+            {"id": "WPC_madera_oscuro", "nombre": "WPC Madera Oscuro", "textura": "Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_oscuro.png", "url_preview": "/seg/texture-preview/Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_oscuro.png", "dimensiones": ["2.90x0.25"]},
+            {"id": "WPC_madera_claro",  "nombre": "WPC Madera Claro",  "textura": "Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_claro.png",  "url_preview": "/seg/texture-preview/Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_claro.png",  "dimensiones": ["2.90x0.25"]},
+            {"id": "WPC_madera_gris",   "nombre": "WPC Madera Gris",   "textura": "Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_gris.png",   "url_preview": "/seg/texture-preview/Texture_WPC_EXTERIOR_INTERIOR/WPC_madera_gris.png",   "dimensiones": ["2.90x0.25"]},
+            {"id": "WPC_negro",         "nombre": "WPC Negro",          "textura": "Texture_WPC_EXTERIOR_INTERIOR/WPC_negro.png",          "url_preview": "/seg/texture-preview/Texture_WPC_EXTERIOR_INTERIOR/WPC_negro.png",          "dimensiones": ["2.90x0.25"]},
+        ],
+        "created_at": "2026-05-07T00:00:00Z",
+    },
+    {
+        "_id": "wpc_deck",
+        "nombre": "WPC Deck",
+        "tipo": "suelos",
+        "descripcion": "Deck de WPC para exteriores e interiores. Ideal para terrazas, jardines, bordes de piscina y espacios al aire libre.",
+        "especificaciones": [
+            "Resistencia a la intemperie.",
+            "Bajo mantenimiento.",
+            "Respetuosa con el medio ambiente.",
+            "Esteticamente agradable.",
+        ],
+        "url_detalle": "https://heyzine.com/flip-book/447fe3eb8e.html#page/38",
+        "productos": [
+            {"id": "DECK_madera",        "nombre": "Deck Madera",        "textura": "Texture_wpc_deck/DECK_madera.png",        "url_preview": "/seg/texture-preview/Texture_wpc_deck/DECK_madera.png",        "dimensiones": ["2.90x0.14"]},
+            {"id": "DECK_madera_oscuro", "nombre": "Deck Madera Oscuro", "textura": "Texture_wpc_deck/DECK_madera_oscuro.png", "url_preview": "/seg/texture-preview/Texture_wpc_deck/DECK_madera_oscuro.png", "dimensiones": ["2.90x0.14"]},
+            {"id": "DECK_gris",          "nombre": "Deck Gris",           "textura": "Texture_wpc_deck/DECK_gris.png",          "url_preview": "/seg/texture-preview/Texture_wpc_deck/DECK_gris.png",          "dimensiones": ["2.90x0.14"]},
+        ],
+        "created_at": "2026-05-08T00:00:00Z",
+    },
+]
+
+
+async def seed_catalog() -> None:
+    col = _get_col()
+    count = await col.count_documents({})
+    if count == 0:
+        await col.insert_many(_SEED)
+        return
+
+    # Migrar documentos existentes: añadir campos que falten según _SEED
+    for seed_item in _SEED:
+        doc = await col.find_one({"_id": seed_item["_id"]})
+        if not doc:
+            continue
+        patch = {k: v for k, v in seed_item.items() if k not in doc and k != "_id"}
+        if patch:
+            await col.update_one({"_id": seed_item["_id"]}, {"$set": patch})
+
+
+def _serialize(doc: dict) -> dict:
+    out = dict(doc)
+    out["id"] = str(out.pop("_id"))
+    return out
+
+
+def _seed_as_response() -> list[dict]:
+    return [{**{k: v for k, v in item.items() if k != "_id"}, "id": item["_id"]} for item in _SEED]
+
+
+# ── Endpoints de lectura ──────────────────────────────────────────────────────
+
+@router.get("/textures")
+async def get_texture_catalog() -> JSONResponse:
+    try:
+        col = _get_col()
+        docs = await col.find({}).to_list(length=200)
+        if docs:
+            return JSONResponse(content={"categories": [_serialize(d) for d in docs]})
+    except Exception:
+        pass
+    # Fallback a datos estáticos si MongoDB no está disponible o la colección está vacía
+    return JSONResponse(content={"categories": _seed_as_response()})
+
+
+@router.get("/textures/{category_id}")
+async def get_texture_category(category_id: str) -> JSONResponse:
+    try:
+        col = _get_col()
+        doc = await col.find_one({"_id": category_id})
+        if doc:
+            return JSONResponse(content=_serialize(doc))
+    except Exception:
+        pass
+    fallback = next((item for item in _SEED if item["_id"] == category_id), None)
+    if fallback:
+        return JSONResponse(content=_seed_as_response()[_SEED.index(fallback)])
+    return JSONResponse(content={"detail": f"Categoria '{category_id}' no encontrada"}, status_code=404)
+
+
+# ── Modelos ───────────────────────────────────────────────────────────────────
+
+class ProductoItem(BaseModel):
+    id: str
+    nombre: str
+    textura: str
+    url_preview: str
+    dimensiones: list[str] = []
+
+
+class CategoriaBody(BaseModel):
+    id: str
+    nombre: str
+    tipo: str = "paredes"
+    descripcion: str = ""
+    especificaciones: list[str] = []
+    url_detalle: str = ""
+    productos: list[ProductoItem] = []
+
+
+# ── Endpoints de escritura ────────────────────────────────────────────────────
+
+@router.post("/category")
+async def add_category(body: CategoriaBody) -> JSONResponse:
+    col = _get_col()
+    existing = await col.find_one({"_id": body.id})
+    if existing:
+        return JSONResponse(content={"error": f"Categoria '{body.id}' ya existe"}, status_code=409)
+    doc = body.model_dump()
+    doc["_id"] = doc.pop("id")
+    doc["created_at"] = datetime.utcnow().isoformat() + "Z"
+    await col.insert_one(doc)
+    return JSONResponse(content={"ok": True, "id": body.id}, status_code=201)
+
+
+@router.put("/category/{category_id}")
+async def update_category(category_id: str, body: CategoriaBody) -> JSONResponse:
+    col = _get_col()
+    doc = body.model_dump()
+    doc.pop("id", None)
+    doc["updated_at"] = datetime.utcnow().isoformat() + "Z"
+    result = await col.update_one({"_id": category_id}, {"$set": doc})
+    if result.matched_count == 0:
+        return JSONResponse(content={"error": "Categoria no encontrada"}, status_code=404)
+    return JSONResponse(content={"ok": True})
+
+
+@router.delete("/category/{category_id}")
+async def delete_category(category_id: str) -> JSONResponse:
+    col = _get_col()
+    result = await col.delete_one({"_id": category_id})
+    if result.deleted_count == 0:
+        return JSONResponse(content={"error": "Categoria no encontrada"}, status_code=404)
+    return JSONResponse(content={"ok": True, "deleted": category_id})
+
+
+@router.post("/category/{category_id}/product")
+async def add_product(category_id: str, product: ProductoItem) -> JSONResponse:
+    col = _get_col()
+    result = await col.update_one(
+        {"_id": category_id, "productos.id": {"$ne": product.id}},
+        {"$push": {"productos": product.model_dump()}, "$set": {"updated_at": datetime.utcnow().isoformat() + "Z"}},
+    )
+    if result.matched_count == 0:
+        return JSONResponse(content={"error": "Categoria no encontrada o producto duplicado"}, status_code=409)
+    return JSONResponse(content={"ok": True}, status_code=201)
+
+
+@router.delete("/category/{category_id}/product/{product_id}")
+async def delete_product(category_id: str, product_id: str) -> JSONResponse:
+    col = _get_col()
+    result = await col.update_one(
+        {"_id": category_id},
+        {"$pull": {"productos": {"id": product_id}}, "$set": {"updated_at": datetime.utcnow().isoformat() + "Z"}},
+    )
+    if result.matched_count == 0:
+        return JSONResponse(content={"error": "Categoria no encontrada"}, status_code=404)
+    return JSONResponse(content={"ok": True})
diff --git a/backend/routers/segmentation.py b/backend/routers/segmentation.py
index 11b5612b2d7355abf7dcd9348b6677f3a227fe98..b36dbba70bc7ac99405b8d4b9e485a4e63aa9f4d 100644
--- a/backend/routers/segmentation.py
+++ b/backend/routers/segmentation.py
@@ -1,760 +1,723 @@
-"""
-Segmentation router - todos los endpoints del editor de texturas con SAM2.
-Prefijo: /seg
-"""
-import asyncio
-import uuid
-from datetime import datetime, timezone
-from pathlib import Path
-from typing import Any, cast
-
-from fastapi import APIRouter, BackgroundTasks, File, HTTPException, UploadFile
-from fastapi.responses import FileResponse, HTMLResponse, Response
-
-from core.config import (
-    FRONTEND_DEBUG,
-    OUTPUT_DIR,
-    SD_JOB_STALE_SECONDS,
-    SD_QUICK_TIMEOUT_SECONDS,
-    UPLOAD_DIR,
-    UPLOAD_JOB_STALE_SECONDS,
-    VIDEO_OUTPUT_DIR,
-    VIDEO_UPLOAD_DIR,
-    load_classic_dashboard_html,
-    log_timing_end,
-    log_timing_start,
-    logger,
-    utc_now_iso,
-)
-from pydantic import BaseModel
-
-from models.schemas import (
-    ApplyColorRequest,
-    ApplyTextureAIRequest,
-    ApplyTextureRequest,
-    ExteriorBrickRequest,
-    ExteriorDepthRequest,
-    ExteriorGrabCutRequest,
-    ExteriorHybridRequest,
-    ExteriorSuggestRequest,
-    GuidedSegmentRequest,
-    SceneAnalyzeRequest,
-    SegmentAdaptiveRequest,
-    SegmentVideoRequest,
-)
-from services.image_service import (
-    prepare_and_store_upload,
-    run_upload_job,
-    save_label_map_for_owner,
-)
-from services.inpainting_service import run_inpainting_job, run_inpainting_sync
-from services.sam2_service import jobs, jobs_lock, release_resources
-from services.openai_service import generate_image_with_openai
-from PIL import Image
-from services.scene_service import (
-    build_adaptive_plan,
-    generate_label_map,
-    infer_scene_type,
-    normalize_priority,
-    normalize_scene_hint,
-    rank_exterior_candidates,
-    rank_interior_candidates,
-)
-from services.segmentation_service import (
-    generate_guided_label_map,
-    parse_mask_index,
-    parse_rgb_color,
-    segment_exterior_brick_sync,
-    segment_exterior_depth_sync,
-    segment_exterior_grabcut_sync,
-    segment_exterior_hybrid_sync,
-    segment_video_sync,
-)
-from services.texture_service import (
-    apply_local_texture_sync,
-    build_texture_preview_jpeg,
-    generate_texture_variations,
-    list_available_textures,
-    resolve_texture_path,
-)
-
-import cv2
-
-router = APIRouter(prefix="/seg")
-
-
-@router.get("/", response_class=HTMLResponse)
-async def home() -> HTMLResponse:
-    dashboard_html = load_classic_dashboard_html().replace(
-        "__FRONTEND_DEBUG_ENABLED__",
-        "true" if FRONTEND_DEBUG else "false",
-    )
-    return HTMLResponse(content=dashboard_html)
-
-
-@router.post("/upload_video")
-async def upload_video(file: UploadFile = File(...)) -> dict[str, Any]:
-    if not file.content_type or not file.content_type.startswith("video/"):
-        raise HTTPException(status_code=400, detail="Only video files are allowed")
-
-    safe_name = Path(file.filename or "uploaded_video").name
-    if not safe_name:
-        raise HTTPException(status_code=400, detail="Invalid filename")
-
-    destination = VIDEO_UPLOAD_DIR / safe_name
-    content = await file.read()
-    if not content:
-        raise HTTPException(status_code=400, detail="Uploaded video is empty")
-
-    destination.write_bytes(content)
-    return {
-        "message": "Video uploaded successfully",
-        "filename": safe_name,
-        "url": f"/seg/video/{safe_name}",
-    }
-
-
-@router.post("/upload_async")
-async def upload_image_async(
-    background_tasks: BackgroundTasks,
-    file: UploadFile = File(...),
-) -> dict[str, Any]:
-    if not file.content_type or not file.content_type.startswith("image/"):
-        raise HTTPException(status_code=400, detail="Only image files are allowed")
-
-    content = await file.read()
-    job_id = uuid.uuid4().hex
-    with jobs_lock:
-        jobs[job_id] = {
-            "kind": "upload",
-            "status": "processing",
-            "stage": "queued",
-            "progress": 2,
-            "message": "Queued for segmentation",
-            "created_at": utc_now_iso(),
-            "updated_at": utc_now_iso(),
-        }
-
-    background_tasks.add_task(run_upload_job, job_id, content, file.filename or "uploaded_image")
-    return {
-        "processing": True,
-        "job_id": job_id,
-        "status": "processing",
-        "stage": "queued",
-        "progress": 2,
-        "message": "Upload accepted. Segmentation started in background.",
-        "status_url": f"/seg/jobs/{job_id}",
-    }
-
-
-@router.post("/segment_guided")
-async def segment_guided(payload: GuidedSegmentRequest) -> dict[str, Any]:
-    started = log_timing_start("SEGMENT_GUIDED")
-    try:
-        from services.image_service import load_image_rgb_for_edit
-        safe_name, image_rgb = await asyncio.to_thread(load_image_rgb_for_edit, payload.filename)
-        label_map, ranked_scores = await asyncio.to_thread(
-            generate_guided_label_map,
-            image_rgb,
-            [list(point) for point in payload.point_coords],
-            list(payload.point_labels),
-            list(payload.box_xyxy) if payload.box_xyxy is not None else [],
-            payload.multimask_output,
-        )
-
-        guided_owner = f"{Path(safe_name).stem}_guided.jpg"
-        label_owner = await asyncio.to_thread(save_label_map_for_owner, guided_owner, label_map)
-        available_indices = list(range(1, len(ranked_scores) + 1))
-
-        return {
-            "message": "Guided segmentation completed",
-            "filename": safe_name,
-            "original_filename_for_apply": label_owner,
-            "mask_count": len(ranked_scores),
-            "available_mask_indices": available_indices,
-            "recommended_mask_index": 1,
-            "scores": [round(score, 6) for score in ranked_scores],
-        }
-    finally:
-        log_timing_end("SEGMENT_GUIDED", started)
-        try:
-            release_resources()
-        except Exception:
-            logger.exception("Error releasing resources after SEGMENT_GUIDED")
-
-
-@router.post("/suggest_exterior_masks")
-async def suggest_exterior_masks(payload: ExteriorSuggestRequest) -> dict[str, Any]:
-    started = log_timing_start("EXTERIOR_SUGGEST")
-    try:
-        from services.image_service import load_image_rgb_for_edit
-        safe_name, image_rgb = await asyncio.to_thread(load_image_rgb_for_edit, payload.filename)
-
-        label_owner_name = Path(payload.original_filename).name if payload.original_filename else safe_name
-
-        masks_dir = UPLOAD_DIR / "masks"
-        label_path = masks_dir / f"{label_owner_name}_labels.png"
-        if not label_path.exists():
-            label_map, _ = await asyncio.to_thread(generate_label_map, image_rgb)
-            label_owner_name = await asyncio.to_thread(save_label_map_for_owner, label_owner_name, label_map)
-            label_path = masks_dir / f"{label_owner_name}_labels.png"
-
-        label_map_arr = cv2.imread(str(label_path), cv2.IMREAD_GRAYSCALE)
-        if label_map_arr is None:
-            raise HTTPException(status_code=404, detail="Label map not found")
-
-        candidates = rank_exterior_candidates(
-            label_map_arr,
-            payload.top_k,
-            target=payload.target,
-            min_area_ratio=payload.min_area_ratio,
-            max_area_ratio=payload.max_area_ratio,
-        )
-
-        return {
-            "message": "Exterior mask suggestions generated",
-            "filename": safe_name,
-            "original_filename_for_apply": label_owner_name,
-            "suggestions": candidates,
-            "target": payload.target,
-        }
-    finally:
-        log_timing_end("EXTERIOR_SUGGEST", started)
-        try:
-            release_resources()
-        except Exception:
-            logger.exception("Error releasing resources after EXTERIOR_SUGGEST")
-
-
-@router.post("/analyze_scene")
-async def analyze_scene(payload: SceneAnalyzeRequest) -> dict[str, Any]:
-    started = log_timing_start("ANALYZE_SCENE")
-    try:
-        from services.image_service import load_image_rgb_for_edit
-        safe_name, image_rgb = await asyncio.to_thread(load_image_rgb_for_edit, payload.filename)
-
-        label_owner_name = Path(payload.original_filename).name if payload.original_filename else safe_name
-        masks_dir = UPLOAD_DIR / "masks"
-        label_path = masks_dir / f"{label_owner_name}_labels.png"
-
-        if not label_path.exists():
-            label_map, _ = await asyncio.to_thread(generate_label_map, image_rgb)
-            label_owner_name = await asyncio.to_thread(save_label_map_for_owner, label_owner_name, label_map)
-
-        scene_info = await asyncio.to_thread(
-            infer_scene_type,
-            image_rgb,
-            payload.semantic_keywords,
-            payload.exterior_target,
-            payload.min_area_ratio,
-            payload.max_area_ratio,
-        )
-        scene_type = scene_info["scene_type"]
-        scene_hint = normalize_scene_hint(payload.scene_hint)
-        effective_scene = scene_hint if scene_hint != "auto" else scene_type
-
-        adaptive_plan = build_adaptive_plan(effective_scene, payload.priority, payload.exterior_target)
-
-        label_map_arr = cv2.imread(str(masks_dir / f"{label_owner_name}_labels.png"), cv2.IMREAD_GRAYSCALE)
-        suggestions: list[dict[str, Any]] = []
-        if label_map_arr is not None:
-            if effective_scene == "exterior":
-                suggestions = rank_exterior_candidates(
-                    label_map_arr, payload.top_k,
-                    target=payload.exterior_target,
-                    min_area_ratio=payload.min_area_ratio,
-                    max_area_ratio=payload.max_area_ratio,
-                )
-            else:
-                suggestions = rank_interior_candidates(label_map_arr, payload.top_k)
-
-        return {
-            "message": "Scene analysis completed",
-            "filename": safe_name,
-            "original_filename_for_apply": label_owner_name,
-            "scene_type": scene_type,
-            "effective_scene": effective_scene,
-            "confidence": scene_info["confidence"],
-            "signals": scene_info["signals"],
-            "adaptive_plan": adaptive_plan,
-            "suggestions": suggestions,
-            "priority": normalize_priority(payload.priority),
-        }
-    finally:
-        log_timing_end("ANALYZE_SCENE", started)
-        try:
-            release_resources()
-        except Exception:
-            logger.exception("Error releasing resources after ANALYZE_SCENE")
-
-
-@router.post("/segment_adaptive")
-async def segment_adaptive(payload: SegmentAdaptiveRequest) -> dict[str, Any]:
-    started = log_timing_start("SEGMENT_ADAPTIVE")
-    try:
-        from services.image_service import load_image_rgb_for_edit
-        safe_name, image_rgb = await asyncio.to_thread(load_image_rgb_for_edit, payload.filename)
-
-        scene_info = await asyncio.to_thread(
-            infer_scene_type,
-            image_rgb,
-            payload.semantic_keywords,
-            payload.exterior_target,
-        )
-        scene_hint = normalize_scene_hint(payload.scene_hint)
-        effective_scene = scene_hint if scene_hint != "auto" else scene_info["scene_type"]
-        priority = normalize_priority(payload.priority)
-        adaptive_plan = build_adaptive_plan(effective_scene, priority, payload.exterior_target)
-
-        label_owner_name = Path(payload.original_filename).name if payload.original_filename else safe_name
-
-        if effective_scene == "exterior":
-            from services.segmentation_service import segment_exterior_depth_sync as seg_depth
-            from models.schemas import ExteriorDepthRequest as DepthReq
-
-            depth_payload = DepthReq(
-                filename=payload.filename,
-                exterior_target=payload.exterior_target,
-                rect_xywh=payload.rect_xywh,
-                smooth_strength=1,
-                sam2_merge_top_k=12,
-                iterations=6,
-                use_semantic_hint=True,
-                use_depth_hint=True,
-                semantic_keywords=payload.semantic_keywords,
-            )
-            result = await asyncio.to_thread(seg_depth, depth_payload)
-        else:
-            label_map, _ = await asyncio.to_thread(generate_label_map, image_rgb)
-            label_owner_name = await asyncio.to_thread(save_label_map_for_owner, label_owner_name, label_map)
-            top_k = 4 if priority == "speed" else (10 if priority == "quality" else 6)
-            candidates = rank_interior_candidates(label_map, top_k)
-            result = {
-                "message": "Interior adaptive segmentation completed",
-                "filename": safe_name,
-                "original_filename_for_apply": label_owner_name,
-                "scene_type": effective_scene,
-                "suggestions": candidates,
-            }
-
-        result["adaptive_plan"] = adaptive_plan
-        result["detected_scene_type"] = scene_info["scene_type"]
-        result["effective_scene"] = effective_scene
-        result["scene_confidence"] = scene_info["confidence"]
-        return result
-    finally:
-        log_timing_end("SEGMENT_ADAPTIVE", started)
-        try:
-            release_resources()
-        except Exception:
-            logger.exception("Error releasing resources after SEGMENT_ADAPTIVE")
-
-
-@router.post("/segment_video")
-async def segment_video(payload: SegmentVideoRequest) -> dict[str, Any]:
-    try:
-        return await asyncio.to_thread(segment_video_sync, payload)
-    except HTTPException:
-        raise
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Video segmentation failed: {exc}") from exc
-
-
-@router.post("/segment_exterior_grabcut")
-async def segment_exterior_grabcut(payload: ExteriorGrabCutRequest) -> dict[str, Any]:
-    try:
-        return await asyncio.to_thread(segment_exterior_grabcut_sync, payload)
-    except HTTPException:
-        raise
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"GrabCut segmentation failed: {exc}") from exc
-
-
-@router.post("/segment_exterior_hybrid")
-async def segment_exterior_hybrid(payload: ExteriorHybridRequest) -> dict[str, Any]:
-    try:
-        return await asyncio.to_thread(segment_exterior_hybrid_sync, payload)
-    except HTTPException:
-        raise
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Hybrid exterior segmentation failed: {exc}") from exc
-
-
-@router.post("/segment_exterior_brick")
-async def segment_exterior_brick(payload: ExteriorBrickRequest) -> dict[str, Any]:
-    try:
-        return await asyncio.to_thread(segment_exterior_brick_sync, payload)
-    except HTTPException:
-        raise
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Brick segmentation failed: {exc}") from exc
-
-
-@router.post("/segment_exterior_depth")
-async def segment_exterior_depth(payload: ExteriorDepthRequest) -> dict[str, Any]:
-    try:
-        return await asyncio.to_thread(segment_exterior_depth_sync, payload)
-    except HTTPException:
-        raise
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Depth exterior segmentation failed: {exc}") from exc
-
-
-@router.post("/apply_texture_ai")
-async def apply_texture_ai(
-    payload: ApplyTextureAIRequest,
-    background_tasks: BackgroundTasks,
-) -> dict[str, Any]:
-    started = log_timing_start("APPLY_TEXTURE_AI")
-    try:
-        # Try to run OpenAI generation synchronously within the quick timeout
-        def _run_openai():
-            safe_name = Path(payload.filename).name
-            image_path = UPLOAD_DIR / safe_name
-            if not image_path.exists():
-                image_path = OUTPUT_DIR / safe_name
-
-            if not image_path.exists():
-                return {"error": f"Image not found: {payload.filename}"}
-
-            try:
-                pil = Image.open(str(image_path)).convert("RGBA")
-            except Exception as e:
-                return {"error": f"Cannot open image: {e}"}
-
-            texture = payload.texture_name or payload.prompt or ""
-            png_bytes, msg = generate_image_with_openai(None, pil, texture)
-            if png_bytes is None:
-                return {"error": msg}
-
-            out_name = f"{Path(safe_name).stem}_ai_{uuid.uuid4().hex}.png"
-            out_path = OUTPUT_DIR / out_name
-            out_path.write_bytes(png_bytes)
-            return {"message": msg, "filename": out_name, "url": f"/seg/ai/{out_name}", "processing": False}
-
-        result = await asyncio.wait_for(asyncio.to_thread(_run_openai), timeout=SD_QUICK_TIMEOUT_SECONDS)
-        log_timing_end("APPLY_TEXTURE_AI", started)
-        try:
-            release_resources()
-        except Exception:
-            logger.exception("Error releasing resources after APPLY_TEXTURE_AI")
-        result["processing"] = False
-        return result
-    except asyncio.TimeoutError:
-        job_id = uuid.uuid4().hex
-        with jobs_lock:
-            jobs[job_id] = {"status": "processing", "created_at": utc_now_iso(), "updated_at": utc_now_iso()}
-        # enqueue background job that runs the OpenAI generation
-        def _run_openai_job(job_id_inner: str, payload_inner: ApplyTextureAIRequest) -> None:
-            try:
-                res = _run_openai()
-                with jobs_lock:
-                    if "error" in res:
-                        jobs[job_id_inner] = {"status": "failed", "error": res.get("error"), "updated_at": utc_now_iso()}
-                    else:
-                        jobs[job_id_inner] = {"status": "done", "result": res, "updated_at": utc_now_iso()}
-            except Exception as exc:
-                with jobs_lock:
-                    jobs[job_id_inner] = {"status": "failed", "error": str(exc), "updated_at": utc_now_iso()}
-
-        background_tasks.add_task(_run_openai_job, job_id, payload)
-        log_timing_end("APPLY_TEXTURE_AI", started)
-        try:
-            release_resources()
-        except Exception:
-            pass
-        return {
-            "processing": True,
-            "job_id": job_id,
-            "message": "Inpainting is taking longer than expected and continues in background.",
-            "status_url": f"/seg/jobs/{job_id}",
-        }
-    except HTTPException:
-        log_timing_end("APPLY_TEXTURE_AI", started)
-        try:
-            release_resources()
-        except Exception:
-            pass
-        raise
-    except Exception as exc:
-        log_timing_end("APPLY_TEXTURE_AI", started)
-        try:
-            release_resources()
-        except Exception:
-            pass
-        raise HTTPException(status_code=500, detail=f"Inpainting failed: {exc}") from exc
-
-
-@router.get("/jobs/{job_id}")
-async def get_job_status(job_id: str) -> dict[str, Any]:
-    with jobs_lock:
-        job = jobs.get(job_id)
-
-    if job is None:
-        raise HTTPException(status_code=404, detail="Job not found")
-
-    if job.get("status") == "processing":
-        kind = str(job.get("kind", "generic"))
-        stage = str(job.get("stage", "processing"))
-        progress = int(job.get("progress", 0) or 0)
-        eta_seconds: int | None = None
-
-        if kind == "upload" and stage == "segmenting_with_sam2":
-            stage_started_at_text = job.get("stage_started_at")
-            estimated_seconds = float(job.get("estimated_seconds", 0.0) or 0.0)
-            if stage_started_at_text and estimated_seconds > 0:
-                try:
-                    stage_started_at = datetime.fromisoformat(str(stage_started_at_text))
-                    elapsed = (datetime.now(timezone.utc) - stage_started_at).total_seconds()
-                    eta_seconds = max(0, int(estimated_seconds - elapsed))
-                    estimated_progress = int(min(95, 30 + (max(0.0, elapsed) / estimated_seconds) * 60))
-                    progress = max(progress, estimated_progress)
-                except ValueError:
-                    pass
-
-        stale_limit_seconds = UPLOAD_JOB_STALE_SECONDS if kind == "upload" else SD_JOB_STALE_SECONDS
-        created_at_text = job.get("created_at")
-        if created_at_text:
-            try:
-                created_at = datetime.fromisoformat(str(created_at_text))
-                age_seconds = (datetime.now(timezone.utc) - created_at).total_seconds()
-                if age_seconds > stale_limit_seconds:
-                    return {
-                        "processing": False,
-                        "status": "timeout",
-                        "message": "The process is taking too long. Please retry.",
-                        "job_id": job_id,
-                    }
-            except ValueError:
-                pass
-
-        response: dict[str, Any] = {
-            "processing": True,
-            "status": "processing",
-            "job_id": job_id,
-            "kind": kind,
-            "stage": stage,
-            "progress": progress,
-            "message": str(job.get("message", "Still processing.")),
-        }
-        if eta_seconds is not None:
-            response["eta_seconds"] = eta_seconds
-        return response
-
-    if job.get("status") == "done":
-        result = cast(dict[str, Any], job.get("result", {}))
-        result["processing"] = False
-        result["job_id"] = job_id
-        result["status"] = "done"
-        return result
-
-    if job.get("status") == "failed":
-        return {
-            "processing": False,
-            "status": "failed",
-            "job_id": job_id,
-            "message": job.get("error", "Background task failed"),
-        }
-
-    return {"processing": True, "status": "processing", "job_id": job_id, "message": "Still processing."}
-
-
-@router.post("/apply_color")
-async def apply_color(payload: ApplyColorRequest) -> dict[str, Any]:
-    started = log_timing_start("APPLY_COLOR")
-    try:
-        safe_name = Path(payload.filename).name
-        if not safe_name:
-            raise HTTPException(status_code=400, detail="Invalid filename")
-
-        label_safe_name = Path(payload.original_filename).name if payload.original_filename else safe_name
-
-        image_path = UPLOAD_DIR / safe_name
-        if not image_path.exists():
-            image_path = OUTPUT_DIR / safe_name
-        if not image_path.exists() or not image_path.is_file():
-            raise HTTPException(status_code=404, detail=f"Image not found: {safe_name}")
-
-        image_bgr = cv2.imread(str(image_path))
-        if image_bgr is None:
-            raise HTTPException(status_code=400, detail="Image could not be read")
-
-        mask_index = parse_mask_index(payload.mask_filename)
-        red, green, blue = parse_rgb_color(payload.color)
-
-        label_path = UPLOAD_DIR / "masks" / f"{label_safe_name}_labels.png"
-        label_map = cv2.imread(str(label_path), cv2.IMREAD_GRAYSCALE)
-        if label_map is None:
-            raise HTTPException(
-                status_code=404,
-                detail="Label map not found. Upload the image first to generate segments.",
-            )
-
-        segmentation = label_map == mask_index
-        if not segmentation.any():
-            raise HTTPException(status_code=400, detail=f"Segment index {mask_index} not found in label map.")
-
-        edited_image = image_bgr.copy()
-        edited_image[segmentation] = (blue, green, red)
-
-        original_stem = Path(label_safe_name).stem
-        out_filename = f"{original_stem}_edit.jpg"
-        out_path = UPLOAD_DIR / out_filename
-        if not cv2.imwrite(str(out_path), edited_image):
-            raise HTTPException(status_code=500, detail="Failed to save edited image")
-
-        return {
-            "message": "Color applied successfully",
-            "output_filename": out_filename,
-            "output_url": f"/seg/image/{out_filename}",
-        }
-    finally:
-        log_timing_end("APPLY_COLOR", started)
-        try:
-            release_resources()
-        except Exception:
-            logger.exception("Error releasing resources after APPLY_COLOR")
-
-
-@router.post("/apply_texture")
-async def apply_texture(payload: ApplyTextureRequest) -> dict[str, Any]:
-    try:
-        result = await asyncio.to_thread(apply_local_texture_sync, payload)
-        result["processing"] = False
-        return result
-    except HTTPException:
-        raise
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Texture apply failed: {exc}") from exc
-
-
-@router.get("/textures")
-async def get_textures() -> dict[str, Any]:
-    return {"textures": list_available_textures()}
-
-
-class _GenerateVariationsRequest(BaseModel):
-    texture_name: str
-
-    class Config:
-        extra = "ignore"
-
-
-@router.post("/textures/generate")
-async def generate_variations(payload: _GenerateVariationsRequest) -> dict[str, Any]:
-    if not payload.texture_name:
-        raise HTTPException(status_code=400, detail="texture_name is required")
-    try:
-        variations = await asyncio.to_thread(generate_texture_variations, payload.texture_name)
-        return {"variations": variations}
-    except HTTPException:
-        raise
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Variation generation failed: {exc}") from exc
-
-
-@router.get("/texture-preview/{filename:path}")
-async def get_texture_preview(filename: str) -> Response:
-    texture_path = resolve_texture_path(filename)
-    jpeg = await asyncio.to_thread(build_texture_preview_jpeg, texture_path)
-    return Response(content=jpeg, media_type="image/jpeg", headers={"Cache-Control": "public, max-age=3600"})
-
-
-@router.get("/video/{filename}")
-async def get_video(filename: str) -> FileResponse:
-    if Path(filename).name != filename:
-        raise HTTPException(status_code=400, detail="Invalid file name")
-    video_path = VIDEO_UPLOAD_DIR / filename
-    if not video_path.exists() or not video_path.is_file():
-        raise HTTPException(status_code=404, detail="Video not found")
-    return FileResponse(video_path)
-
-
-@router.get("/output-video/{filename}")
-async def get_output_video(filename: str) -> FileResponse:
-    if Path(filename).name != filename:
-        raise HTTPException(status_code=400, detail="Invalid file name")
-    video_path = VIDEO_OUTPUT_DIR / filename
-    if not video_path.exists() or not video_path.is_file():
-        raise HTTPException(status_code=404, detail="Output video not found")
-    return FileResponse(video_path)
-
-
-@router.get("/image/{filename}")
-async def get_image(filename: str) -> FileResponse:
-    if Path(filename).name != filename:
-        raise HTTPException(status_code=400, detail="Invalid file name")
-    image_path = UPLOAD_DIR / filename
-    if not image_path.exists() or not image_path.is_file():
-        raise HTTPException(status_code=404, detail="Image not found")
-    return FileResponse(image_path)
-
-
-@router.post("/masks/reclassify/{filename}")
-async def reclassify_mask_metadata(filename: str) -> dict[str, Any]:
-    """Re-run semantic classification on an already-segmented image and overwrite its metadata JSON."""
-    import json as _json
-    safe = Path(filename).name
-    if not safe:
-        raise HTTPException(status_code=400, detail="Invalid filename")
-
-    masks_dir = UPLOAD_DIR / "masks"
-    label_path = masks_dir / f"{safe}_labels.png"
-    if not label_path.exists():
-        raise HTTPException(status_code=404, detail="Label map not found — upload the image first")
-
-    label_map = cv2.imread(str(label_path), cv2.IMREAD_GRAYSCALE)
-    if label_map is None:
-        raise HTTPException(status_code=500, detail="Could not read label map")
-
-    image_path = UPLOAD_DIR / safe
-    image_rgb: Any = None
-    if image_path.exists():
-        img_bgr = cv2.imread(str(image_path))
-        if img_bgr is not None:
-            image_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
-
-    from services.scene_service import classify_all_label_map_segments
-    h, w = label_map.shape[:2]
-    segments_meta = await asyncio.to_thread(
-        classify_all_label_map_segments, label_map, w, h, image_rgb
-    )
-    meta_path = masks_dir / f"{safe}_labels_meta.json"
-    meta_path.write_text(_json.dumps({"segments": segments_meta}, ensure_ascii=False), encoding="utf-8")
-
-    return {"segments": segments_meta, "count": len(segments_meta)}
-
-
-@router.get("/masks/meta/{filename}")
-async def get_mask_metadata(filename: str) -> dict:
-    import json as _json
-    safe = Path(filename).name
-    if not safe:
-        raise HTTPException(status_code=400, detail="Invalid filename")
-    meta_path = UPLOAD_DIR / "masks" / f"{safe}_labels_meta.json"
-    if not meta_path.exists() or not meta_path.is_file():
-        raise HTTPException(status_code=404, detail="Segment metadata not found")
-    try:
-        return _json.loads(meta_path.read_text(encoding="utf-8"))
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Failed to read metadata: {exc}") from exc
-
-
-@router.get("/masks/{filename}")
-async def get_mask_labels(filename: str) -> FileResponse:
-    if Path(filename).name != filename:
-        raise HTTPException(status_code=400, detail="Invalid file name")
-    label_path = UPLOAD_DIR / "masks" / f"{filename}_labels.png"
-    if not label_path.exists() or not label_path.is_file():
-        raise HTTPException(status_code=404, detail="Label map not found")
-    return FileResponse(label_path)
-
-
-@router.get("/ai/{filename}")
-async def get_ai_image(filename: str) -> FileResponse:
-    if Path(filename).name != filename:
-        raise HTTPException(status_code=400, detail="Invalid file name")
-    out_path = OUTPUT_DIR / filename
-    if not out_path.exists() or not out_path.is_file():
-        raise HTTPException(status_code=404, detail="AI output image not found")
-    return FileResponse(out_path)
+"""
+Segmentation router - todos los endpoints del editor de texturas con SAM2.
+Prefijo: /seg
+"""
+import asyncio
+import uuid
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, cast
+
+from fastapi import APIRouter, BackgroundTasks, File, HTTPException, UploadFile
+from fastapi.responses import FileResponse, HTMLResponse, Response
+
+from core.config import (
+    FRONTEND_DEBUG,
+    OUTPUT_DIR,
+    SD_JOB_STALE_SECONDS,
+    SD_QUICK_TIMEOUT_SECONDS,
+    UPLOAD_DIR,
+    UPLOAD_JOB_STALE_SECONDS,
+    VIDEO_OUTPUT_DIR,
+    VIDEO_UPLOAD_DIR,
+    load_classic_dashboard_html,
+    log_timing_end,
+    log_timing_start,
+    logger,
+    utc_now_iso,
+)
+from pydantic import BaseModel
+
+from models.schemas import (
+    ApplyColorRequest,
+    ApplyTextureAIRequest,
+    ApplyTextureRequest,
+    ExteriorBrickRequest,
+    ExteriorDepthRequest,
+    ExteriorGrabCutRequest,
+    ExteriorHybridRequest,
+    ExteriorSuggestRequest,
+    GuidedSegmentRequest,
+    SceneAnalyzeRequest,
+    SegmentAdaptiveRequest,
+    SegmentVideoRequest,
+)
+from services.image_service import (
+    prepare_and_store_upload,
+    run_upload_job,
+    save_label_map_for_owner,
+)
+from services.inpainting_service import run_inpainting_job, run_inpainting_sync
+from services.sam2_service import jobs, jobs_lock, release_resources
+from services.scene_service import (
+    build_adaptive_plan,
+    generate_label_map,
+    infer_scene_type,
+    normalize_priority,
+    normalize_scene_hint,
+    rank_exterior_candidates,
+    rank_interior_candidates,
+)
+from services.segmentation_service import (
+    generate_guided_label_map,
+    parse_mask_index,
+    parse_rgb_color,
+    segment_exterior_brick_sync,
+    segment_exterior_depth_sync,
+    segment_exterior_grabcut_sync,
+    segment_exterior_hybrid_sync,
+    segment_video_sync,
+)
+from services.texture_service import (
+    apply_local_texture_sync,
+    build_texture_preview_jpeg,
+    generate_texture_variations,
+    list_available_textures,
+    resolve_texture_path,
+)
+
+import cv2
+
+router = APIRouter(prefix="/seg")
+
+
+@router.get("/", response_class=HTMLResponse)
+async def home() -> HTMLResponse:
+    dashboard_html = load_classic_dashboard_html().replace(
+        "__FRONTEND_DEBUG_ENABLED__",
+        "true" if FRONTEND_DEBUG else "false",
+    )
+    return HTMLResponse(content=dashboard_html)
+
+
+@router.post("/upload_video")
+async def upload_video(file: UploadFile = File(...)) -> dict[str, Any]:
+    if not file.content_type or not file.content_type.startswith("video/"):
+        raise HTTPException(status_code=400, detail="Only video files are allowed")
+
+    safe_name = Path(file.filename or "uploaded_video").name
+    if not safe_name:
+        raise HTTPException(status_code=400, detail="Invalid filename")
+
+    destination = VIDEO_UPLOAD_DIR / safe_name
+    content = await file.read()
+    if not content:
+        raise HTTPException(status_code=400, detail="Uploaded video is empty")
+
+    destination.write_bytes(content)
+    return {
+        "message": "Video uploaded successfully",
+        "filename": safe_name,
+        "url": f"/seg/video/{safe_name}",
+    }
+
+
+@router.post("/upload_async")
+async def upload_image_async(
+    background_tasks: BackgroundTasks,
+    file: UploadFile = File(...),
+) -> dict[str, Any]:
+    if not file.content_type or not file.content_type.startswith("image/"):
+        raise HTTPException(status_code=400, detail="Only image files are allowed")
+
+    content = await file.read()
+    job_id = uuid.uuid4().hex
+    with jobs_lock:
+        jobs[job_id] = {
+            "kind": "upload",
+            "status": "processing",
+            "stage": "queued",
+            "progress": 2,
+            "message": "Queued for segmentation",
+            "created_at": utc_now_iso(),
+            "updated_at": utc_now_iso(),
+        }
+
+    background_tasks.add_task(run_upload_job, job_id, content, file.filename or "uploaded_image")
+    return {
+        "processing": True,
+        "job_id": job_id,
+        "status": "processing",
+        "stage": "queued",
+        "progress": 2,
+        "message": "Upload accepted. Segmentation started in background.",
+        "status_url": f"/seg/jobs/{job_id}",
+    }
+
+
+@router.post("/segment_guided")
+async def segment_guided(payload: GuidedSegmentRequest) -> dict[str, Any]:
+    started = log_timing_start("SEGMENT_GUIDED")
+    try:
+        from services.image_service import load_image_rgb_for_edit
+        safe_name, image_rgb = await asyncio.to_thread(load_image_rgb_for_edit, payload.filename)
+        label_map, ranked_scores = await asyncio.to_thread(
+            generate_guided_label_map,
+            image_rgb,
+            [list(point) for point in payload.point_coords],
+            list(payload.point_labels),
+            list(payload.box_xyxy) if payload.box_xyxy is not None else [],
+            payload.multimask_output,
+        )
+
+        guided_owner = f"{Path(safe_name).stem}_guided.jpg"
+        label_owner = await asyncio.to_thread(save_label_map_for_owner, guided_owner, label_map)
+        available_indices = list(range(1, len(ranked_scores) + 1))
+
+        return {
+            "message": "Guided segmentation completed",
+            "filename": safe_name,
+            "original_filename_for_apply": label_owner,
+            "mask_count": len(ranked_scores),
+            "available_mask_indices": available_indices,
+            "recommended_mask_index": 1,
+            "scores": [round(score, 6) for score in ranked_scores],
+        }
+    finally:
+        log_timing_end("SEGMENT_GUIDED", started)
+        try:
+            release_resources()
+        except Exception:
+            logger.exception("Error releasing resources after SEGMENT_GUIDED")
+
+
+@router.post("/suggest_exterior_masks")
+async def suggest_exterior_masks(payload: ExteriorSuggestRequest) -> dict[str, Any]:
+    started = log_timing_start("EXTERIOR_SUGGEST")
+    try:
+        from services.image_service import load_image_rgb_for_edit
+        safe_name, image_rgb = await asyncio.to_thread(load_image_rgb_for_edit, payload.filename)
+
+        label_owner_name = Path(payload.original_filename).name if payload.original_filename else safe_name
+
+        masks_dir = UPLOAD_DIR / "masks"
+        label_path = masks_dir / f"{label_owner_name}_labels.png"
+        if not label_path.exists():
+            label_map, _ = await asyncio.to_thread(generate_label_map, image_rgb)
+            label_owner_name = await asyncio.to_thread(save_label_map_for_owner, label_owner_name, label_map)
+            label_path = masks_dir / f"{label_owner_name}_labels.png"
+
+        label_map_arr = cv2.imread(str(label_path), cv2.IMREAD_GRAYSCALE)
+        if label_map_arr is None:
+            raise HTTPException(status_code=404, detail="Label map not found")
+
+        candidates = rank_exterior_candidates(
+            label_map_arr,
+            payload.top_k,
+            target=payload.target,
+            min_area_ratio=payload.min_area_ratio,
+            max_area_ratio=payload.max_area_ratio,
+        )
+
+        return {
+            "message": "Exterior mask suggestions generated",
+            "filename": safe_name,
+            "original_filename_for_apply": label_owner_name,
+            "suggestions": candidates,
+            "target": payload.target,
+        }
+    finally:
+        log_timing_end("EXTERIOR_SUGGEST", started)
+        try:
+            release_resources()
+        except Exception:
+            logger.exception("Error releasing resources after EXTERIOR_SUGGEST")
+
+
+@router.post("/analyze_scene")
+async def analyze_scene(payload: SceneAnalyzeRequest) -> dict[str, Any]:
+    started = log_timing_start("ANALYZE_SCENE")
+    try:
+        from services.image_service import load_image_rgb_for_edit
+        safe_name, image_rgb = await asyncio.to_thread(load_image_rgb_for_edit, payload.filename)
+
+        label_owner_name = Path(payload.original_filename).name if payload.original_filename else safe_name
+        masks_dir = UPLOAD_DIR / "masks"
+        label_path = masks_dir / f"{label_owner_name}_labels.png"
+
+        if not label_path.exists():
+            label_map, _ = await asyncio.to_thread(generate_label_map, image_rgb)
+            label_owner_name = await asyncio.to_thread(save_label_map_for_owner, label_owner_name, label_map)
+
+        scene_info = await asyncio.to_thread(
+            infer_scene_type,
+            image_rgb,
+            payload.semantic_keywords,
+            payload.exterior_target,
+            payload.min_area_ratio,
+            payload.max_area_ratio,
+        )
+        scene_type = scene_info["scene_type"]
+        scene_hint = normalize_scene_hint(payload.scene_hint)
+        effective_scene = scene_hint if scene_hint != "auto" else scene_type
+
+        adaptive_plan = build_adaptive_plan(effective_scene, payload.priority, payload.exterior_target)
+
+        label_map_arr = cv2.imread(str(masks_dir / f"{label_owner_name}_labels.png"), cv2.IMREAD_GRAYSCALE)
+        suggestions: list[dict[str, Any]] = []
+        if label_map_arr is not None:
+            if effective_scene == "exterior":
+                suggestions = rank_exterior_candidates(
+                    label_map_arr, payload.top_k,
+                    target=payload.exterior_target,
+                    min_area_ratio=payload.min_area_ratio,
+                    max_area_ratio=payload.max_area_ratio,
+                )
+            else:
+                suggestions = rank_interior_candidates(label_map_arr, payload.top_k)
+
+        return {
+            "message": "Scene analysis completed",
+            "filename": safe_name,
+            "original_filename_for_apply": label_owner_name,
+            "scene_type": scene_type,
+            "effective_scene": effective_scene,
+            "confidence": scene_info["confidence"],
+            "signals": scene_info["signals"],
+            "adaptive_plan": adaptive_plan,
+            "suggestions": suggestions,
+            "priority": normalize_priority(payload.priority),
+        }
+    finally:
+        log_timing_end("ANALYZE_SCENE", started)
+        try:
+            release_resources()
+        except Exception:
+            logger.exception("Error releasing resources after ANALYZE_SCENE")
+
+
+@router.post("/segment_adaptive")
+async def segment_adaptive(payload: SegmentAdaptiveRequest) -> dict[str, Any]:
+    started = log_timing_start("SEGMENT_ADAPTIVE")
+    try:
+        from services.image_service import load_image_rgb_for_edit
+        safe_name, image_rgb = await asyncio.to_thread(load_image_rgb_for_edit, payload.filename)
+
+        scene_info = await asyncio.to_thread(
+            infer_scene_type,
+            image_rgb,
+            payload.semantic_keywords,
+            payload.exterior_target,
+        )
+        scene_hint = normalize_scene_hint(payload.scene_hint)
+        effective_scene = scene_hint if scene_hint != "auto" else scene_info["scene_type"]
+        priority = normalize_priority(payload.priority)
+        adaptive_plan = build_adaptive_plan(effective_scene, priority, payload.exterior_target)
+
+        label_owner_name = Path(payload.original_filename).name if payload.original_filename else safe_name
+
+        if effective_scene == "exterior":
+            from services.segmentation_service import segment_exterior_depth_sync as seg_depth
+            from models.schemas import ExteriorDepthRequest as DepthReq
+
+            depth_payload = DepthReq(
+                filename=payload.filename,
+                exterior_target=payload.exterior_target,
+                rect_xywh=payload.rect_xywh,
+                smooth_strength=1,
+                sam2_merge_top_k=12,
+                iterations=6,
+                use_semantic_hint=True,
+                use_depth_hint=True,
+                semantic_keywords=payload.semantic_keywords,
+            )
+            result = await asyncio.to_thread(seg_depth, depth_payload)
+        else:
+            label_map, _ = await asyncio.to_thread(generate_label_map, image_rgb)
+            label_owner_name = await asyncio.to_thread(save_label_map_for_owner, label_owner_name, label_map)
+            top_k = 4 if priority == "speed" else (10 if priority == "quality" else 6)
+            candidates = rank_interior_candidates(label_map, top_k)
+            result = {
+                "message": "Interior adaptive segmentation completed",
+                "filename": safe_name,
+                "original_filename_for_apply": label_owner_name,
+                "scene_type": effective_scene,
+                "suggestions": candidates,
+            }
+
+        result["adaptive_plan"] = adaptive_plan
+        result["detected_scene_type"] = scene_info["scene_type"]
+        result["effective_scene"] = effective_scene
+        result["scene_confidence"] = scene_info["confidence"]
+        return result
+    finally:
+        log_timing_end("SEGMENT_ADAPTIVE", started)
+        try:
+            release_resources()
+        except Exception:
+            logger.exception("Error releasing resources after SEGMENT_ADAPTIVE")
+
+
+@router.post("/segment_video")
+async def segment_video(payload: SegmentVideoRequest) -> dict[str, Any]:
+    try:
+        return await asyncio.to_thread(segment_video_sync, payload)
+    except HTTPException:
+        raise
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"Video segmentation failed: {exc}") from exc
+
+
+@router.post("/segment_exterior_grabcut")
+async def segment_exterior_grabcut(payload: ExteriorGrabCutRequest) -> dict[str, Any]:
+    try:
+        return await asyncio.to_thread(segment_exterior_grabcut_sync, payload)
+    except HTTPException:
+        raise
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"GrabCut segmentation failed: {exc}") from exc
+
+
+@router.post("/segment_exterior_hybrid")
+async def segment_exterior_hybrid(payload: ExteriorHybridRequest) -> dict[str, Any]:
+    try:
+        return await asyncio.to_thread(segment_exterior_hybrid_sync, payload)
+    except HTTPException:
+        raise
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"Hybrid exterior segmentation failed: {exc}") from exc
+
+
+@router.post("/segment_exterior_brick")
+async def segment_exterior_brick(payload: ExteriorBrickRequest) -> dict[str, Any]:
+    try:
+        return await asyncio.to_thread(segment_exterior_brick_sync, payload)
+    except HTTPException:
+        raise
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"Brick segmentation failed: {exc}") from exc
+
+
+@router.post("/segment_exterior_depth")
+async def segment_exterior_depth(payload: ExteriorDepthRequest) -> dict[str, Any]:
+    try:
+        return await asyncio.to_thread(segment_exterior_depth_sync, payload)
+    except HTTPException:
+        raise
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"Depth exterior segmentation failed: {exc}") from exc
+
+
+@router.post("/apply_texture_ai")
+async def apply_texture_ai(
+    payload: ApplyTextureAIRequest,
+    background_tasks: BackgroundTasks,
+) -> dict[str, Any]:
+    started = log_timing_start("APPLY_TEXTURE_AI")
+    try:
+        result = await asyncio.wait_for(
+            asyncio.to_thread(run_inpainting_sync, payload),
+            timeout=SD_QUICK_TIMEOUT_SECONDS,
+        )
+        log_timing_end("APPLY_TEXTURE_AI", started)
+        try:
+            release_resources()
+        except Exception:
+            logger.exception("Error releasing resources after APPLY_TEXTURE_AI")
+        result["processing"] = False
+        return result
+    except asyncio.TimeoutError:
+        job_id = uuid.uuid4().hex
+        with jobs_lock:
+            jobs[job_id] = {"status": "processing", "created_at": utc_now_iso(), "updated_at": utc_now_iso()}
+        background_tasks.add_task(run_inpainting_job, job_id, payload)
+        log_timing_end("APPLY_TEXTURE_AI", started)
+        try:
+            release_resources()
+        except Exception:
+            pass
+        return {
+            "processing": True,
+            "job_id": job_id,
+            "message": "Inpainting is taking longer than expected and continues in background.",
+            "status_url": f"/seg/jobs/{job_id}",
+        }
+    except HTTPException:
+        log_timing_end("APPLY_TEXTURE_AI", started)
+        try:
+            release_resources()
+        except Exception:
+            pass
+        raise
+    except Exception as exc:
+        log_timing_end("APPLY_TEXTURE_AI", started)
+        try:
+            release_resources()
+        except Exception:
+            pass
+        raise HTTPException(status_code=500, detail=f"Inpainting failed: {exc}") from exc
+
+
+@router.get("/jobs/{job_id}")
+async def get_job_status(job_id: str) -> dict[str, Any]:
+    with jobs_lock:
+        job = jobs.get(job_id)
+
+    if job is None:
+        raise HTTPException(status_code=404, detail="Job not found")
+
+    if job.get("status") == "processing":
+        kind = str(job.get("kind", "generic"))
+        stage = str(job.get("stage", "processing"))
+        progress = int(job.get("progress", 0) or 0)
+        eta_seconds: int | None = None
+
+        if kind == "upload" and stage == "segmenting_with_sam2":
+            stage_started_at_text = job.get("stage_started_at")
+            estimated_seconds = float(job.get("estimated_seconds", 0.0) or 0.0)
+            if stage_started_at_text and estimated_seconds > 0:
+                try:
+                    stage_started_at = datetime.fromisoformat(str(stage_started_at_text))
+                    elapsed = (datetime.now(timezone.utc) - stage_started_at).total_seconds()
+                    eta_seconds = max(0, int(estimated_seconds - elapsed))
+                    estimated_progress = int(min(95, 30 + (max(0.0, elapsed) / estimated_seconds) * 60))
+                    progress = max(progress, estimated_progress)
+                except ValueError:
+                    pass
+
+        stale_limit_seconds = UPLOAD_JOB_STALE_SECONDS if kind == "upload" else SD_JOB_STALE_SECONDS
+        created_at_text = job.get("created_at")
+        if created_at_text:
+            try:
+                created_at = datetime.fromisoformat(str(created_at_text))
+                age_seconds = (datetime.now(timezone.utc) - created_at).total_seconds()
+                if age_seconds > stale_limit_seconds:
+                    return {
+                        "processing": False,
+                        "status": "timeout",
+                        "message": "The process is taking too long. Please retry.",
+                        "job_id": job_id,
+                    }
+            except ValueError:
+                pass
+
+        response: dict[str, Any] = {
+            "processing": True,
+            "status": "processing",
+            "job_id": job_id,
+            "kind": kind,
+            "stage": stage,
+            "progress": progress,
+            "message": str(job.get("message", "Still processing.")),
+        }
+        if eta_seconds is not None:
+            response["eta_seconds"] = eta_seconds
+        return response
+
+    if job.get("status") == "done":
+        result = cast(dict[str, Any], job.get("result", {}))
+        result["processing"] = False
+        result["job_id"] = job_id
+        result["status"] = "done"
+        return result
+
+    if job.get("status") == "failed":
+        return {
+            "processing": False,
+            "status": "failed",
+            "job_id": job_id,
+            "message": job.get("error", "Background task failed"),
+        }
+
+    return {"processing": True, "status": "processing", "job_id": job_id, "message": "Still processing."}
+
+
+@router.post("/apply_color")
+async def apply_color(payload: ApplyColorRequest) -> dict[str, Any]:
+    started = log_timing_start("APPLY_COLOR")
+    try:
+        safe_name = Path(payload.filename).name
+        if not safe_name:
+            raise HTTPException(status_code=400, detail="Invalid filename")
+
+        label_safe_name = Path(payload.original_filename).name if payload.original_filename else safe_name
+
+        image_path = UPLOAD_DIR / safe_name
+        if not image_path.exists():
+            image_path = OUTPUT_DIR / safe_name
+        if not image_path.exists() or not image_path.is_file():
+            raise HTTPException(status_code=404, detail=f"Image not found: {safe_name}")
+
+        image_bgr = cv2.imread(str(image_path))
+        if image_bgr is None:
+            raise HTTPException(status_code=400, detail="Image could not be read")
+
+        mask_index = parse_mask_index(payload.mask_filename)
+        red, green, blue = parse_rgb_color(payload.color)
+
+        label_path = UPLOAD_DIR / "masks" / f"{label_safe_name}_labels.png"
+        label_map = cv2.imread(str(label_path), cv2.IMREAD_GRAYSCALE)
+        if label_map is None:
+            raise HTTPException(
+                status_code=404,
+                detail="Label map not found. Upload the image first to generate segments.",
+            )
+
+        segmentation = label_map == mask_index
+        if not segmentation.any():
+            raise HTTPException(status_code=400, detail=f"Segment index {mask_index} not found in label map.")
+
+        edited_image = image_bgr.copy()
+        edited_image[segmentation] = (blue, green, red)
+
+        original_stem = Path(label_safe_name).stem
+        out_filename = f"{original_stem}_edit.jpg"
+        out_path = UPLOAD_DIR / out_filename
+        if not cv2.imwrite(str(out_path), edited_image):
+            raise HTTPException(status_code=500, detail="Failed to save edited image")
+
+        return {
+            "message": "Color applied successfully",
+            "output_filename": out_filename,
+            "output_url": f"/seg/image/{out_filename}",
+        }
+    finally:
+        log_timing_end("APPLY_COLOR", started)
+        try:
+            release_resources()
+        except Exception:
+            logger.exception("Error releasing resources after APPLY_COLOR")
+
+
+@router.post("/apply_texture")
+async def apply_texture(payload: ApplyTextureRequest) -> dict[str, Any]:
+    try:
+        result = await asyncio.to_thread(apply_local_texture_sync, payload)
+        result["processing"] = False
+        return result
+    except HTTPException:
+        raise
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"Texture apply failed: {exc}") from exc
+
+
+@router.get("/textures")
+async def get_textures() -> dict[str, Any]:
+    return {"textures": list_available_textures()}
+
+
+class _GenerateVariationsRequest(BaseModel):
+    texture_name: str
+
+    class Config:
+        extra = "ignore"
+
+
+@router.post("/textures/generate")
+async def generate_variations(payload: _GenerateVariationsRequest) -> dict[str, Any]:
+    if not payload.texture_name:
+        raise HTTPException(status_code=400, detail="texture_name is required")
+    try:
+        variations = await asyncio.to_thread(generate_texture_variations, payload.texture_name)
+        return {"variations": variations}
+    except HTTPException:
+        raise
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"Variation generation failed: {exc}") from exc
+
+
+@router.get("/texture-preview/{filename:path}")
+async def get_texture_preview(filename: str) -> Response:
+    texture_path = resolve_texture_path(filename)
+    jpeg = await asyncio.to_thread(build_texture_preview_jpeg, texture_path)
+    return Response(content=jpeg, media_type="image/jpeg", headers={"Cache-Control": "public, max-age=3600"})
+
+
+@router.get("/video/{filename}")
+async def get_video(filename: str) -> FileResponse:
+    if Path(filename).name != filename:
+        raise HTTPException(status_code=400, detail="Invalid file name")
+    video_path = VIDEO_UPLOAD_DIR / filename
+    if not video_path.exists() or not video_path.is_file():
+        raise HTTPException(status_code=404, detail="Video not found")
+    return FileResponse(video_path)
+
+
+@router.get("/output-video/{filename}")
+async def get_output_video(filename: str) -> FileResponse:
+    if Path(filename).name != filename:
+        raise HTTPException(status_code=400, detail="Invalid file name")
+    video_path = VIDEO_OUTPUT_DIR / filename
+    if not video_path.exists() or not video_path.is_file():
+        raise HTTPException(status_code=404, detail="Output video not found")
+    return FileResponse(video_path)
+
+
+@router.get("/image/{filename}")
+async def get_image(filename: str) -> FileResponse:
+    if Path(filename).name != filename:
+        raise HTTPException(status_code=400, detail="Invalid file name")
+    image_path = UPLOAD_DIR / filename
+    if not image_path.exists() or not image_path.is_file():
+        raise HTTPException(status_code=404, detail="Image not found")
+    return FileResponse(image_path)
+
+
+@router.post("/masks/reclassify/{filename}")
+async def reclassify_mask_metadata(filename: str) -> dict[str, Any]:
+    """Re-run semantic classification on an already-segmented image and overwrite its metadata JSON."""
+    import json as _json
+    safe = Path(filename).name
+    if not safe:
+        raise HTTPException(status_code=400, detail="Invalid filename")
+
+    masks_dir = UPLOAD_DIR / "masks"
+    label_path = masks_dir / f"{safe}_labels.png"
+    if not label_path.exists():
+        raise HTTPException(status_code=404, detail="Label map not found — upload the image first")
+
+    label_map = cv2.imread(str(label_path), cv2.IMREAD_GRAYSCALE)
+    if label_map is None:
+        raise HTTPException(status_code=500, detail="Could not read label map")
+
+    image_path = UPLOAD_DIR / safe
+    image_rgb: Any = None
+    if image_path.exists():
+        img_bgr = cv2.imread(str(image_path))
+        if img_bgr is not None:
+            image_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
+
+    from services.scene_service import classify_all_label_map_segments
+    h, w = label_map.shape[:2]
+    segments_meta = await asyncio.to_thread(
+        classify_all_label_map_segments, label_map, w, h, image_rgb
+    )
+    meta_path = masks_dir / f"{safe}_labels_meta.json"
+    meta_path.write_text(_json.dumps({"segments": segments_meta}, ensure_ascii=False), encoding="utf-8")
+
+    return {"segments": segments_meta, "count": len(segments_meta)}
+
+
+@router.get("/masks/meta/{filename}")
+async def get_mask_metadata(filename: str) -> dict:
+    import json as _json
+    safe = Path(filename).name
+    if not safe:
+        raise HTTPException(status_code=400, detail="Invalid filename")
+    meta_path = UPLOAD_DIR / "masks" / f"{safe}_labels_meta.json"
+    if not meta_path.exists() or not meta_path.is_file():
+        raise HTTPException(status_code=404, detail="Segment metadata not found")
+    try:
+        return _json.loads(meta_path.read_text(encoding="utf-8"))
+    except Exception as exc:
+        raise HTTPException(status_code=500, detail=f"Failed to read metadata: {exc}") from exc
+
+
+@router.get("/masks/{filename}")
+async def get_mask_labels(filename: str) -> FileResponse:
+    if Path(filename).name != filename:
+        raise HTTPException(status_code=400, detail="Invalid file name")
+    label_path = UPLOAD_DIR / "masks" / f"{filename}_labels.png"
+    if not label_path.exists() or not label_path.is_file():
+        raise HTTPException(status_code=404, detail="Label map not found")
+    return FileResponse(label_path)
+
+
+@router.get("/ai/{filename}")
+async def get_ai_image(filename: str) -> FileResponse:
+    if Path(filename).name != filename:
+        raise HTTPException(status_code=400, detail="Invalid file name")
+    out_path = OUTPUT_DIR / filename
+    if not out_path.exists() or not out_path.is_file():
+        raise HTTPException(status_code=404, detail="AI output image not found")
+    return FileResponse(out_path)
diff --git a/backend/run_server.bat b/backend/run_server.bat
index bcc1a54cdd83f00d54f2fcbcee22c0e209047b7f..10921a1271c2fb24847837ef5c5c96c87d8bf546 100644
--- a/backend/run_server.bat
+++ b/backend/run_server.bat
@@ -1,12 +1,12 @@
-@echo off
-REM Usa el Python del entorno virtual local dentro de backend y arranca uvicorn con recarga en caliente.
-if exist .venv\Scripts\python.exe (
-  set "PYTHON_EXE=.venv\Scripts\python.exe"
-) else if exist .venv\bin\python.exe (
-  set "PYTHON_EXE=.venv\bin\python.exe"
-) else (
-  echo No se encontró Python en .venv. Crea el entorno virtual primero.
-  pause
-  exit /b 1
-)
-%PYTHON_EXE% -m uvicorn main:app --reload --host 0.0.0.0 --port 8000
+@echo off
+REM Usa el Python del entorno virtual local dentro de backend y arranca uvicorn con recarga en caliente.
+if exist .venv\Scripts\python.exe (
+  set "PYTHON_EXE=.venv\Scripts\python.exe"
+) else if exist .venv\bin\python.exe (
+  set "PYTHON_EXE=.venv\bin\python.exe"
+) else (
+  echo No se encontró Python en .venv. Crea el entorno virtual primero.
+  pause
+  exit /b 1
+)
+%PYTHON_EXE% -m uvicorn main:app --reload --host 0.0.0.0 --port 8000
diff --git a/backend/services/gradio_client_service.py b/backend/services/gradio_client_service.py
index 21592fb3a212ae553affec2c3a943e8d7c778b7e..95d162080ba3a6d3da0255b056993f3d874b09e2 100644
--- a/backend/services/gradio_client_service.py
+++ b/backend/services/gradio_client_service.py
@@ -1,108 +1,104 @@
-"""
-Cliente para llamar al Gradio Space de ZeroGPU (SAM2 + SegFormer + DINO).
-Se activa solo si GRADIO_SPACE_URL está definido en el entorno.
-"""
-import asyncio
-import base64
-import io
-import json
-import logging
-from pathlib import Path
-
-import numpy as np
-from PIL import Image
-
-from core.config import GRADIO_CPU_FALLBACK_URL, GRADIO_SPACE_URL
-
-logger = logging.getLogger(__name__)
-
-
-def is_gradio_enabled() -> bool:
-    # Desactivado por petición del usuario para usar el nuevo flujo simplificado con OpenAI
-    return False
-
-
-
-def _call_gradio_sync(image_path: Path, space_url: str) -> tuple[np.ndarray, int]:
-    """
-    Synchronous Gradio call — safe to invoke from a background thread.
-    Returns (label_map, mask_count).
-    Raises on any error so the caller can handle fallback.
-    """
-    from gradio_client import Client, file  # type: ignore
-
-    # 300s timeout: ZeroGPU cold start + SAM2+DINO inference can take 60-120s
-    # client = Client(space_url, httpx_kwargs={"timeout": 300.0})
-    client = Client(space_url) # httpx_kwargs no es compatible con todas las versiones
-
-
-    # segment_for_backend returns (overlay_image, combined_json_str)
-    _overlay_file, combined_json_str = client.predict(
-        file(str(image_path)),
-        api_name="/segment",
-    )
-
-    if not isinstance(combined_json_str, str):
-        raise ValueError(f"Unexpected response type from Gradio Space: {type(combined_json_str)}")
-
-    combined: dict = json.loads(combined_json_str)
-
-    if "error" in combined:
-        raise RuntimeError(f"Gradio Space error: {combined['error'][:500]}")
-
-    label_map_b64: str = combined.get("label_map_b64", "")
-    if not label_map_b64:
-        return np.zeros((1, 1), dtype=np.uint8), 0
-
-    # Decode PNG-encoded label map (lossless uint8 grayscale)
-    label_map_bytes = base64.b64decode(label_map_b64)
-    pil_label = Image.open(io.BytesIO(label_map_bytes))
-    label_map = np.array(pil_label, dtype=np.uint8)
-    mask_count = int(label_map.max())
-
-    entorno = combined.get("entorno", "?")
-    motor = combined.get("motor", "?")
-    logger.info(
-        "Gradio Space segmentation: entorno=%s motor=%s mask_count=%d",
-        entorno, motor, mask_count,
-    )
-
-    return label_map, mask_count
-
-
-def segment_via_gradio_sync(image_path: Path) -> tuple[np.ndarray, int]:
-    """
-    Blocking call to the Gradio Space from a sync context (background task thread).
-    Tries the GPU Space first; if it fails, falls back to the CPU Space.
-    Raises RuntimeError if both fail or neither is configured.
-    """
-    if not is_gradio_enabled():
-        raise RuntimeError("GRADIO_SPACE_URL is not configured")
-
-    gpu_error: Exception | None = None
-    try:
-        logger.info("Calling GPU Gradio Space: %s", GRADIO_SPACE_URL)
-        return _call_gradio_sync(image_path, GRADIO_SPACE_URL)
-    except Exception as e:
-        gpu_error = e
-        logger.warning("GPU Space failed (%s), trying CPU fallback...", gpu_error)
-
-    if not GRADIO_CPU_FALLBACK_URL:
-        raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
-
-    try:
-        logger.info("Calling CPU fallback Space: %s", GRADIO_CPU_FALLBACK_URL)
-        return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
-    except Exception as exc_cpu:
-        raise RuntimeError(
-            f"Both Gradio Spaces failed.\n"
-            f"  GPU ({GRADIO_SPACE_URL}): {gpu_error}\n"
-            f"  CPU ({GRADIO_CPU_FALLBACK_URL}): {exc_cpu}"
-        ) from exc_cpu
-
-
-async def segment_via_gradio(image_path: Path) -> tuple[np.ndarray, int]:
-    """
-    Async wrapper — offloads the blocking call (with GPU→CPU fallback) to a thread.
-    """
-    return await asyncio.to_thread(segment_via_gradio_sync, image_path)
+"""
+Cliente para llamar al Gradio Space de ZeroGPU (SAM2 + SegFormer + DINO).
+Se activa solo si GRADIO_SPACE_URL está definido en el entorno.
+"""
+import asyncio
+import base64
+import io
+import json
+import logging
+from pathlib import Path
+
+import numpy as np
+from PIL import Image
+
+from core.config import GRADIO_CPU_FALLBACK_URL, GRADIO_SPACE_URL
+
+logger = logging.getLogger(__name__)
+
+
+def is_gradio_enabled() -> bool:
+    return bool(GRADIO_SPACE_URL)
+
+
+def _call_gradio_sync(image_path: Path, space_url: str) -> tuple[np.ndarray, int]:
+    """
+    Synchronous Gradio call — safe to invoke from a background thread.
+    Returns (label_map, mask_count).
+    Raises on any error so the caller can handle fallback.
+    """
+    from gradio_client import Client, file  # type: ignore
+
+    # 300s timeout: ZeroGPU cold start + SAM2+DINO inference can take 60-120s
+    client = Client(space_url, httpx_kwargs={"timeout": 300.0})
+
+    # segment_for_backend returns (overlay_image, combined_json_str)
+    _overlay_file, combined_json_str = client.predict(
+        file(str(image_path)),
+        api_name="/segment",
+    )
+
+    if not isinstance(combined_json_str, str):
+        raise ValueError(f"Unexpected response type from Gradio Space: {type(combined_json_str)}")
+
+    combined: dict = json.loads(combined_json_str)
+
+    if "error" in combined:
+        raise RuntimeError(f"Gradio Space error: {combined['error'][:500]}")
+
+    label_map_b64: str = combined.get("label_map_b64", "")
+    if not label_map_b64:
+        return np.zeros((1, 1), dtype=np.uint8), 0
+
+    # Decode PNG-encoded label map (lossless uint8 grayscale)
+    label_map_bytes = base64.b64decode(label_map_b64)
+    pil_label = Image.open(io.BytesIO(label_map_bytes))
+    label_map = np.array(pil_label, dtype=np.uint8)
+    mask_count = int(label_map.max())
+
+    entorno = combined.get("entorno", "?")
+    motor = combined.get("motor", "?")
+    logger.info(
+        "Gradio Space segmentation: entorno=%s motor=%s mask_count=%d",
+        entorno, motor, mask_count,
+    )
+
+    return label_map, mask_count
+
+
+def segment_via_gradio_sync(image_path: Path) -> tuple[np.ndarray, int]:
+    """
+    Blocking call to the Gradio Space from a sync context (background task thread).
+    Tries the GPU Space first; if it fails, falls back to the CPU Space.
+    Raises RuntimeError if both fail or neither is configured.
+    """
+    if not is_gradio_enabled():
+        raise RuntimeError("GRADIO_SPACE_URL is not configured")
+
+    gpu_error: Exception | None = None
+    try:
+        logger.info("Calling GPU Gradio Space: %s", GRADIO_SPACE_URL)
+        return _call_gradio_sync(image_path, GRADIO_SPACE_URL)
+    except Exception as e:
+        gpu_error = e
+        logger.warning("GPU Space failed (%s), trying CPU fallback...", gpu_error)
+
+    if not GRADIO_CPU_FALLBACK_URL:
+        raise RuntimeError(f"GPU Gradio Space failed and no CPU fallback configured. Error: {gpu_error}")
+
+    try:
+        logger.info("Calling CPU fallback Space: %s", GRADIO_CPU_FALLBACK_URL)
+        return _call_gradio_sync(image_path, GRADIO_CPU_FALLBACK_URL)
+    except Exception as exc_cpu:
+        raise RuntimeError(
+            f"Both Gradio Spaces failed.\n"
+            f"  GPU ({GRADIO_SPACE_URL}): {gpu_error}\n"
+            f"  CPU ({GRADIO_CPU_FALLBACK_URL}): {exc_cpu}"
+        ) from exc_cpu
+
+
+async def segment_via_gradio(image_path: Path) -> tuple[np.ndarray, int]:
+    """
+    Async wrapper — offloads the blocking call (with GPU→CPU fallback) to a thread.
+    """
+    return await asyncio.to_thread(segment_via_gradio_sync, image_path)
diff --git a/backend/services/image_service.py b/backend/services/image_service.py
index 5e6621f71d4e9f681be29e58924fd5d9fe8b90d3..08265d2eb68bb2ba6388f1207b71e0da92cbd3b3 100644
--- a/backend/services/image_service.py
+++ b/backend/services/image_service.py
@@ -18,13 +18,13 @@ from core.config import (
     logger,
     utc_now_iso,
 )
+from services.gradio_client_service import is_gradio_enabled, segment_via_gradio_sync
 from services.sam2_service import (
     jobs,
     jobs_lock,
     release_resources,
 )
 
-
 # Imported lazily to avoid circular imports
 def _get_generate_label_map():
     from services.scene_service import generate_label_map
@@ -134,15 +134,47 @@ def run_upload_job(job_id: str, content: bytes, original_name: str) -> None:
         logger.info(f"[JOB {job_id}] segmenting_with_sam2 progress=30 estimated_seconds={estimated_seconds}")
 
         image_path = UPLOAD_DIR / safe_name
-        
-        # We are simplifying the flow: skipping SAM 2 segmentation.
-        # The result will have 0 masks.
-        
+        if is_gradio_enabled():
+            label_map, mask_count = segment_via_gradio_sync(image_path)
+        else:
+            generate_label_map = _get_generate_label_map()
+            label_map, mask_count = generate_label_map(image_rgb)
+
+        with jobs_lock:
+            job = jobs.setdefault(job_id, {})
+            job.update({
+                "stage": "saving_masks",
+                "progress": 92,
+                "message": "Saving mask map",
+                "updated_at": utc_now_iso(),
+            })
+        logger.info(f"[JOB {job_id}] saving_masks progress=92")
+
+        masks_dir = UPLOAD_DIR / "masks"
+        masks_dir.mkdir(exist_ok=True)
+        label_path = masks_dir / f"{safe_name}_labels.png"
+        if not cv2.imwrite(str(label_path), label_map):
+            raise HTTPException(status_code=500, detail="Failed to save label map")
+
+        # Classify each segment and save metadata
+        try:
+            from services.scene_service import classify_all_label_map_segments
+            h, w = image_rgb.shape[:2]
+            segments_meta = classify_all_label_map_segments(label_map, w, h, image_rgb)
+            meta_path = masks_dir / f"{safe_name}_labels_meta.json"
+            meta_path.write_text(
+                json.dumps({"segments": segments_meta}, ensure_ascii=False),
+                encoding="utf-8",
+            )
+            logger.info(f"[JOB {job_id}] segments_meta saved ({len(segments_meta)} segments)")
+        except Exception:
+            logger.exception(f"[JOB {job_id}] Failed to save segment metadata")
+
         result: dict[str, Any] = {
             "message": "Image uploaded successfully",
             "filename": safe_name,
             "url": f"/seg/image/{safe_name}",
-            "mask_count": 0,
+            "mask_count": mask_count,
         }
 
         with jobs_lock:
@@ -151,15 +183,11 @@ def run_upload_job(job_id: str, content: bytes, original_name: str) -> None:
                 "status": "done",
                 "stage": "done",
                 "progress": 100,
-                "message": "Upload complete (Simplified flow)",
+                "message": "Segmentation complete",
                 "result": result,
                 "updated_at": utc_now_iso(),
             }
-        logger.info(f"[JOB {job_id}] done (simplified, 0 masks)")
-
-        # Segmentation-related files (masks, metadata) are skipped in the simplified flow.
-        pass
-
+        logger.info(f"[JOB {job_id}] done mask_count={mask_count}")
 
     except Exception as exc:
         logger.exception(f"[JOB {job_id}] failed: {exc}")
diff --git a/backend/services/inpainting_service.py b/backend/services/inpainting_service.py
index 6409dbf0b5d4cd73103fddeef5310887a172eced..476c0190851ae1ef169939a88dc442adddbbf5cd 100644
--- a/backend/services/inpainting_service.py
+++ b/backend/services/inpainting_service.py
@@ -1,220 +1,28 @@
-import io
-import os
-import base64
-import openai
-from pathlib import Path
-from PIL import Image, ImageOps
 from typing import Any
-import numpy as np
 
-from core.config import UPLOAD_DIR, OUTPUT_DIR, logger, utc_now_iso
-from services.openai_service import _get_texture_hex
+from core.config import utc_now_iso
 from models.schemas import ApplyTextureAIRequest
 from services.sam2_service import jobs, jobs_lock
 
-# ─── Descripciones en inglés para el prompt de DALL-E ─────────────────────────
-TEXTURE_DESCRIPTIONS = {
-    "ACM_Amarillo":          "bright yellow smooth aluminum composite panel exterior cladding",
-    "ACM_Azul":              "blue aluminum composite panel exterior cladding",
-    "ACM_Glossy_Black":      "glossy black aluminum composite panel exterior cladding",
-    "ACM_Glossy_Red":        "glossy red aluminum composite panel exterior cladding",
-    "ACM_Grafito":           "graphite dark grey aluminum composite panel exterior cladding",
-    "ACM_Light_Blue":        "light sky blue aluminum composite panel exterior cladding",
-    "ACM_Madera_Clara":      "light wood grain aluminum composite panel exterior cladding",
-    "ACM_Matteblack":        "matte black aluminum composite panel exterior cladding",
-    "ACM_Metalic":           "metallic silver brushed aluminum composite panel exterior cladding",
-    "ACM_MouseGrey":         "mouse grey aluminum composite panel exterior cladding",
-    "ACM_Orange":            "orange aluminum composite panel exterior cladding",
-    "ACM_ROBLE(OAK)":        "oak wood grain aluminum composite panel exterior cladding",
-    "ACM_Verde":             "green aluminum composite panel exterior cladding",
-    "ACM_Verde_HN":          "dark forest green aluminum composite panel exterior cladding",
-    "ACM_Verde_Lima":        "lime yellow-green aluminum composite panel exterior cladding",
-    "ACM_White":             "white aluminum composite panel exterior cladding",
-    "DECK_gris":             "grey WPC wood-plastic composite deck boards",
-    "DECK_madera":           "natural wood-look WPC composite deck boards",
-    "DECK_madera_oscuro":    "dark brown WPC composite deck boards",
-    "WPC_madera_claro":      "light beige wood-grain WPC exterior wall cladding",
-    "WPC_madera_gris":       "grey weathered wood-look WPC exterior wall cladding",
-    "WPC_madera_oscuro":     "dark espresso wood-grain WPC exterior wall cladding",
-    "WPC_negro":             "black WPC exterior wall cladding",
-}
-
-def prepare_image_square(pil_img, size=1024):
-    """
-    Ajusta la imagen a un cuadrado de 1024x1024 añadiendo padding 
-    para no deformar la imagen original.
-    """
-    orig_w, orig_h = pil_img.size
-    ratio = orig_w / orig_h
-    
-    if ratio > 1: # Es más ancha que alta (Horizontal)
-        new_w = size
-        new_h = int(size / ratio)
-        padding = (0, (size - new_h) // 2)
-    else: # Es más alta que ancha (Vertical)
-        new_h = size
-        new_w = int(size * ratio)
-        padding = ((size - new_w) // 2, 0)
-        
-    # Redimensionar manteniendo proporción
-    resized_img = pil_img.resize((new_w, new_h), Image.LANCZOS)
-    
-    # Crear fondo cuadrado con transparencia
-    new_img = Image.new("RGBA", (size, size), (255, 255, 255, 0))
-    new_img.paste(resized_img, padding)
-    
-    return new_img, padding, (new_w, new_h)
 
 def run_inpainting_sync(payload: ApplyTextureAIRequest) -> dict[str, Any]:
-    """
-    Usa DALL-E 2 para editar la imagen de la casa reemplazando las texturas.
-    Inspirado en la lógica de 'imagneConaI/app.py'.
-    """
-    api_key = os.getenv("OPENAI_API_KEY")
-    if not api_key:
-        return {"error": "OpenAI API Key not found in environment"}
-
-    safe_name = Path(payload.filename).name
-    image_path = UPLOAD_DIR / safe_name
-    if not image_path.exists():
-        image_path = OUTPUT_DIR / safe_name
-    
-    if not image_path.exists():
-        return {"error": f"Image not found: {payload.filename}"}
-
-    # Determinar descripción de textura
-    texture_name = payload.texture_name or "ACM_White"
-    texture_stem = Path(texture_name).stem
-    texture_desc = TEXTURE_DESCRIPTIONS.get(texture_stem, texture_name)
-
-    # Specs técnicas para el prompt
-    acm_specs = ""
-    if texture_stem.startswith("ACM"):
-        acm_specs = (
-            "ACM aluminum composite panel 4mm thick, 0.40mm aluminum layers, "
-            "panels sized 1.22m x 2.44m, clean precision-cut joints between panels, "
-        )
-    elif "WPC" in texture_stem or "DECK" in texture_stem:
-        acm_specs = "WPC wood-plastic composite profile boards, "
-
-    try:
-        client = openai.OpenAI(api_key=api_key)
-
-        pil_img_orig = Image.open(str(image_path)).convert("RGBA")
-        orig_size = pil_img_orig.size
-        
-        square_img, padding, resized_dims = prepare_image_square(pil_img_orig)
-        
-        buf = io.BytesIO()
-        square_img.save(buf, format="PNG")
-        buf.seek(0)
-
-        # Usar el prompt enviado o generar uno por defecto
-        prompt = payload.prompt or (
-            f"Edit ONLY the exterior wall cladding material of this house. "
-            f"Replace all facade wall surfaces with {acm_specs}{texture_desc}. "
-            f"Keep EVERYTHING ELSE exactly the same: the house structure, shape, proportions, "
-            f"roof, windows, doors, garage, balcony railings, garden, plants, sky and lighting. "
-            f"Only change the wall surface material. "
-            f"Result must look like a photorealistic architectural photo. "
-            f"CRITICAL: Do NOT stylize, do NOT apply artistic filters, do NOT add painterly or CGI effects. "
-            f"Preserve photographic grain, camera exposure, highlights and shadows, and match original lighting and perspective. "
-            f"Avoid oversmoothing — keep realistic texture detail and crisp panel edges."
-        )
-
-        # If texture file exists, compute representative hex and request exact color match
-        tex_hex = _get_texture_hex(texture_name or "") if texture_name else None
-        if tex_hex:
-            prompt += f" Use the exact color sample {tex_hex} from the reference texture and match its hue, saturation and brightness precisely. Do not alter the color tone."
+    return {
+        "message": "Inpainting not configured",
+        "filename": payload.filename,
+        "prompt": payload.prompt,
+        "processing": False,
+    }
 
-        # gpt-image-1 solo acepta 1024x1024
-        # If a texture file exists, attach it as a reference image when possible
-        tex_path = None
-        if texture_name:
-            try:
-                from services.texture_service import resolve_texture_path as _resolve
-                tex_path = _resolve(texture_name)
-            except Exception:
-                tex_path = None
-
-        if tex_path:
-            try:
-                with open(tex_path, "rb") as tf:
-                    tex_buf = io.BytesIO(tf.read())
-                    tex_buf.seek(0)
-                    response = client.images.edit(
-                        model="gpt-image-1",
-                        image=("house.png", buf, "image/png"),
-                        reference_image=(Path(tex_path).name, tex_buf, "image/png"),
-                        prompt=prompt,
-                        n=1,
-                        size="1024x1024",
-                        response_format="b64_json",
-                    )
-            except Exception:
-                response = client.images.edit(
-                    model="gpt-image-1",
-                    image=("house.png", buf, "image/png"),
-                    prompt=prompt,
-                    n=1,
-                    size="1024x1024",
-                    response_format="b64_json",
-                )
-        else:
-            response = client.images.edit(
-                model="gpt-image-1",
-                image=("house.png", buf, "image/png"),
-                prompt=prompt,
-                n=1,
-                size="1024x1024",
-                response_format="b64_json",
-            )
-
-        img_data = base64.b64decode(response.data[0].b64_json)
-        result_square = Image.open(io.BytesIO(img_data)).convert("RGBA")
-        
-        # 2. Recortar el resultado para volver al aspecto original (quitar padding)
-        left, top = padding
-        right, bottom = left + resized_dims[0], top + resized_dims[1]
-        result_cropped = result_square.crop((left, top, right, bottom))
-        
-        # 3. Redimensionar al tamaño original exacto
-        result = result_cropped.resize(orig_size, Image.LANCZOS).convert("RGB")
-
-        # Return generated result without blending with original image
-        final = result
-
-        out_filename = f"{Path(safe_name).stem}_ai_{texture_stem}.jpg"
-        out_path = OUTPUT_DIR / out_filename
-        final.save(str(out_path), "JPEG", quality=90)
-
-        return {
-            "message": f"AI Texture applied: {texture_name}",
-            "filename": out_filename,
-            "url": f"/seg/ai/{out_filename}",
-            "processing": False
-        }
-
-    except Exception as e:
-        logger.error(f"DALL-E Error: {e}")
-        return {"error": str(e)}
 
 def run_inpainting_job(job_id: str, payload: ApplyTextureAIRequest) -> None:
     try:
         result = run_inpainting_sync(payload)
         with jobs_lock:
-            if "error" in result:
-                jobs[job_id] = {
-                    "status": "failed",
-                    "error": result["error"],
-                    "updated_at": utc_now_iso(),
-                }
-            else:
-                jobs[job_id] = {
-                    "status": "done",
-                    "result": result,
-                    "updated_at": utc_now_iso(),
-                }
+            jobs[job_id] = {
+                "status": "done",
+                "result": result,
+                "updated_at": utc_now_iso(),
+            }
     except Exception as exc:
         with jobs_lock:
             jobs[job_id] = {
diff --git a/backend/services/sam2_service.py b/backend/services/sam2_service.py
index a455a74fde940f78ed21527a7e7caa6c6c6b6f1f..dc729c9e48607fa82e02bb2f52be8542ca98d44a 100644
--- a/backend/services/sam2_service.py
+++ b/backend/services/sam2_service.py
@@ -112,9 +112,6 @@ def find_sam2_model_path() -> Path:
 
 def load_sam2_model() -> None:
     global sam2_mask_generator, sam2_image_predictor, sam2_load_error
-    sam2_load_error = "SAM2 disabled (using Simplified OpenAI flow)"
-    logger.info(f"[SAM2] {sam2_load_error}")
-    return
 
     if not _TORCH_AVAILABLE:
         sam2_load_error = "torch not installed — SAM2 unavailable (using Gradio Space)"
diff --git a/backend/services/texture_service.py b/backend/services/texture_service.py
index 61914b709052fd339c9205b052b2da7f2a7e4d5f..70c4d96d96ff16ce0b66e46210abaf64076d8955 100644
--- a/backend/services/texture_service.py
+++ b/backend/services/texture_service.py
@@ -1,851 +1,851 @@
-import io
-import shutil
-import uuid
-from pathlib import Path
-from typing import Any
-
-import cv2
-import numpy as np
-from fastapi import HTTPException
-from PIL import Image
-
-from core.config import (
-    OUTPUT_DIR,
-    TEXTURE_DIR,
-    UPLOAD_DIR,
-    UPLOAD_JPEG_QUALITY,
-    log_timing_end,
-    log_timing_start,
-    logger,
-)
-from models.schemas import ApplyTextureRequest
-
-
-def generate_texture_variations(texture_name: str) -> list[dict[str, str]]:
-    """
-    Genera variaciones de color/brillo/saturación de una textura de referencia usando HSV.
-    Los archivos se cachean en TEXTURE_DIR/generated/ — si ya existen no se regeneran.
-    Devuelve lista de {ref, label, preview_url}.
-    """
-    texture_path = resolve_texture_path(texture_name)
-    generated_dir = TEXTURE_DIR / "generated"
-    generated_dir.mkdir(parents=True, exist_ok=True)
-
-    tex_pil = load_texture_pil_rgb(texture_path)
-    tex_bgr = cv2.cvtColor(np.array(tex_pil, dtype=np.uint8), cv2.COLOR_RGB2BGR)
-    tex_hsv = cv2.cvtColor(tex_bgr, cv2.COLOR_BGR2HSV).astype(np.int32)
-
-    base_stem = Path(texture_name).stem
-    results: list[dict[str, str]] = []
-
-    def _save(hsv: np.ndarray, suffix: str, label: str) -> None:
-        fname = f"{base_stem}__{suffix}.jpg"
-        out_path = generated_dir / fname
-        if not out_path.exists():
-            bgr = cv2.cvtColor(np.clip(hsv, 0, 255).astype(np.uint8), cv2.COLOR_HSV2BGR)
-            rgb = cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB)
-            Image.fromarray(rgb).save(str(out_path), format="JPEG", quality=92, optimize=True)
-        ref = f"generated/{fname}"
-        results.append({"ref": ref, "label": label, "preview_url": f"/seg/texture-preview/{ref}"})
-
-    # Rotaciones de tono: 12 pasos de 30° recorriendo el círculo cromático
-    # En OpenCV HSV, H ∈ [0,179] → shift en grados / 2
-    for deg, label in [
-        (30,  "Naranja"),
-        (60,  "Amarillo"),
-        (90,  "Verde lima"),
-        (120, "Verde"),
-        (150, "Verde agua"),
-        (165, "Cyan"),
-        (180, "Azul cielo"),
-        (210, "Azul"),
-        (240, "Índigo"),
-        (270, "Violeta"),
-        (300, "Magenta"),
-        (330, "Rosa"),
-    ]:
-        v = tex_hsv.copy()
-        v[:, :, 0] = (v[:, :, 0] + deg // 2) % 180
-        _save(v, f"hue{deg}", label)
-
-    # Variaciones de brillo
-    for factor, label, suffix in [
-        (0.45, "Oscuro",  "dark"),
-        (1.55, "Claro",   "light"),
-    ]:
-        v = tex_hsv.copy()
-        v[:, :, 2] = np.clip(v[:, :, 2] * factor, 0, 255)
-        _save(v, suffix, label)
-
-    # Variaciones de saturación
-    for factor, label, suffix in [
-        (0.0,  "Gris",    "gray"),
-        (0.45, "Apagado", "muted"),
-        (1.75, "Vívido",  "vivid"),
-    ]:
-        v = tex_hsv.copy()
-        v[:, :, 1] = np.clip(v[:, :, 1] * factor, 0, 255)
-        _save(v, suffix, label)
-
-    return results
-
-
-def list_available_textures() -> list[str]:
-    allowed = {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".tif", ".tiff", ".exr"}
-    return [
-        str(path.relative_to(TEXTURE_DIR)).replace("\\", "/")
-        for path in sorted(TEXTURE_DIR.rglob("*"))
-        if path.is_file() and path.suffix.lower() in allowed
-    ]
-
-
-def resolve_texture_path(texture_name: str) -> Path:
-    if not texture_name:
-        raise HTTPException(status_code=400, detail="Invalid texture_name")
-
-    normalized = texture_name.replace("\\", "/").strip("/")
-    candidate = (TEXTURE_DIR / normalized).resolve()
-    base = TEXTURE_DIR.resolve()
-
-    try:
-        candidate.relative_to(base)
-    except ValueError as exc:
-        raise HTTPException(status_code=400, detail="Invalid texture_name") from exc
-
-    if not candidate.exists() or not candidate.is_file():
-        raise HTTPException(status_code=404, detail=f"Texture not found: {normalized}")
-
-    return candidate
-
-
-def build_texture_preview_jpeg(texture_path: Path, max_size: int = 320) -> bytes:
-    pil_img = load_texture_pil_rgb(texture_path)
-    pil_img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
-    out = io.BytesIO()
-    pil_img.save(out, format="JPEG", quality=88, optimize=True)
-    return out.getvalue()
-
-
-def load_texture_pil_rgb(texture_path: Path) -> Image.Image:
-    suffix = texture_path.suffix.lower()
-
-    if suffix != ".exr":
-        try:
-            return Image.open(str(texture_path)).convert("RGB")
-        except Exception as exc:
-            raise HTTPException(status_code=500, detail=f"Could not read texture file: {exc}") from exc
-
-    exr = cv2.imread(str(texture_path), cv2.IMREAD_UNCHANGED)
-    if exr is None:
-        raise HTTPException(status_code=500, detail="Could not decode EXR texture")
-
-    if exr.ndim == 2:
-        exr = np.stack([exr, exr, exr], axis=-1)
-    if exr.ndim != 3:
-        raise HTTPException(status_code=500, detail="EXR texture has unsupported shape")
-    if exr.shape[2] > 3:
-        exr = exr[:, :, :3]
-
-    exr = np.nan_to_num(exr, nan=0.0, posinf=0.0, neginf=0.0)
-    exr = np.maximum(exr, 0)
-
-    if np.issubdtype(exr.dtype, np.floating):
-        scale = float(np.percentile(exr, 99.0))
-        if scale <= 1e-8:
-            scale = float(np.max(exr))
-        if scale <= 1e-8:
-            scale = 1.0
-        img = np.clip(exr / scale, 0.0, 1.0)
-        img = np.power(img, 1.0 / 2.2)
-        img_u8 = (img * 255.0).astype(np.uint8)
-    elif exr.dtype == np.uint16:
-        img_u8 = (exr / 257.0).astype(np.uint8)
-    else:
-        img_u8 = np.clip(exr, 0, 255).astype(np.uint8)
-
-    img_rgb = cv2.cvtColor(img_u8, cv2.COLOR_BGR2RGB)
-    return Image.fromarray(img_rgb).convert("RGB")
-
-
-def estimate_mask_orientation_degrees(binary_mask: np.ndarray) -> float:
-    mask_u8 = (binary_mask > 0).astype(np.uint8)
-    contours, _ = cv2.findContours(mask_u8, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-    if not contours:
-        return 0.0
-
-    largest = max(contours, key=cv2.contourArea)
-    if cv2.contourArea(largest) < 25.0:
-        return 0.0
-
-    rect = cv2.minAreaRect(largest)
-    (_, _), (width, height), angle = rect
-
-    dominant_angle = float(angle)
-    if width < height:
-        dominant_angle += 90.0
-
-    dominant_angle %= 180.0
-    return dominant_angle
-
-
-def _compute_trapezoid_score_from_mask(
-    binary_mask: np.ndarray,
-    ys: np.ndarray,
-    xs: np.ndarray,
-    min_y: int,
-    max_y: int,
-    bbox_h: int,
-) -> float:
-    """Return 0..1 indicating how floor-like (wider at bottom) the mask shape is."""
-    quarter = max(1, bbox_h // 4)
-    top_xs = xs[ys <= (min_y + quarter)]
-    bot_xs = xs[ys >= (max_y - quarter)]
-    if len(top_xs) < 3 or len(bot_xs) < 3:
-        return 0.0
-    top_w = float(top_xs.max() - top_xs.min())
-    bot_w = float(bot_xs.max() - bot_xs.min())
-    if top_w < 5.0:
-        return 1.0 if bot_w > 20.0 else 0.0
-    ratio = bot_w / top_w
-    return float(np.clip((ratio - 1.0) / 1.8, 0.0, 1.0))
-
-
-def _sort_quad_corners(pts: np.ndarray) -> np.ndarray:
-    """Sort 4 points into [TL, TR, BR, BL] order."""
-    result = np.zeros((4, 2), dtype=np.float32)
-    s = pts[:, 0] + pts[:, 1]
-    d = pts[:, 0] - pts[:, 1]
-    result[0] = pts[np.argmin(s)]
-    result[1] = pts[np.argmax(d)]
-    result[2] = pts[np.argmax(s)]
-    result[3] = pts[np.argmin(d)]
-    return result
-
-
-def _extract_mask_quad(binary_mask: np.ndarray) -> np.ndarray | None:
-    """Approximate mask as 4-corner polygon sorted [TL, TR, BR, BL], or None."""
-    mask_u8 = (binary_mask > 0).astype(np.uint8)
-    contours, _ = cv2.findContours(mask_u8, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-    if not contours:
-        return None
-    largest = max(contours, key=cv2.contourArea)
-    if cv2.contourArea(largest) < 400.0:
-        return None
-    hull = cv2.convexHull(largest)
-    peri = cv2.arcLength(hull, True)
-    for eps_frac in (0.03, 0.05, 0.08, 0.10, 0.13):
-        approx = cv2.approxPolyDP(hull, eps_frac * peri, True)
-        if len(approx) == 4:
-            return _sort_quad_corners(approx.reshape(4, 2).astype(np.float32))
-    return None
-
-
-def _tile_texture_perspective(
-    tex_pil: Image.Image,
-    quad: np.ndarray,
-    image_width: int,
-    image_height: int,
-) -> Image.Image | None:
-    """
-    Tile texture with perspective correction for a floor surface.
-    quad: [TL, TR, BR, BL] in image coordinates.
-    Returns full-image-size PIL image with warped tiled texture, or None on failure.
-    Pixels outside the perspective quad are filled with regular tiling to avoid black gaps.
-    """
-    tl, tr, br, bl = quad
-    bot_w = float(np.linalg.norm(br.astype(float) - bl.astype(float)))
-    top_w = float(np.linalg.norm(tr.astype(float) - tl.astype(float)))
-    left_h = float(np.linalg.norm(bl.astype(float) - tl.astype(float)))
-    right_h = float(np.linalg.norm(br.astype(float) - tr.astype(float)))
-    rect_w = min(int(max(bot_w, top_w)) + 1, image_width * 2)
-    rect_h = min(int(max(left_h, right_h)) + 1, image_height * 2)
-    if rect_w < 8 or rect_h < 8:
-        return None
-    tex_arr = np.array(tex_pil.convert("RGB"), dtype=np.uint8)
-    th, tw = tex_arr.shape[:2]
-    if tw < 1 or th < 1:
-        return None
-    rect_tiled = np.zeros((rect_h, rect_w, 3), dtype=np.uint8)
-    for ry in range(0, rect_h, th):
-        for rx in range(0, rect_w, tw):
-            py = min(th, rect_h - ry)
-            px = min(tw, rect_w - rx)
-            rect_tiled[ry : ry + py, rx : rx + px] = tex_arr[:py, :px]
-    src_pts = np.array(
-        [[0.0, 0.0], [float(rect_w - 1), 0.0], [float(rect_w - 1), float(rect_h - 1)], [0.0, float(rect_h - 1)]],
-        dtype=np.float32,
-    )
-    dst_pts = quad.astype(np.float32)
-    try:
-        H = cv2.getPerspectiveTransform(src_pts, dst_pts)
-        warped = cv2.warpPerspective(rect_tiled, H, (image_width, image_height))
-        # Mapa de cobertura: píxeles realmente cubiertos por el warp
-        cov_src = np.ones((rect_h, rect_w), dtype=np.uint8) * 255
-        coverage = cv2.warpPerspective(cov_src, H, (image_width, image_height))
-    except cv2.error:
-        return None
-
-    # Rellenar píxeles sin cobertura (fuera del quad) con tiling regular
-    # para evitar espacios negros donde la máscara supera el quad aproximado
-    regular = np.zeros((image_height, image_width, 3), dtype=np.uint8)
-    for ry in range(0, image_height, th):
-        for rx in range(0, image_width, tw):
-            py = min(th, image_height - ry)
-            px = min(tw, image_width - rx)
-            regular[ry : ry + py, rx : rx + px] = tex_arr[:py, :px]
-
-    uncovered = coverage < 128
-    warped[uncovered] = regular[uncovered]
-
-    return Image.fromarray(warped)
-
-
-def classify_texture_material(texture_name: str) -> str:
-    texture_key = texture_name.lower()
-    if "acm" in texture_key or "wpc" in texture_key:
-        return "acm"
-    if any(hint in texture_key for hint in ("deck", "wood", "plank", "laminate", "floor")):
-        return "wood"
-    if any(hint in texture_key for hint in ("marble", "granite", "tile", "brick", "cobblestone", "stone", "cartago", "riverbed")):
-        return "stone"
-    if any(hint in texture_key for hint in ("metal", "rust", "iron", "steel")):
-        return "metal"
-    return "generic"
-
-
-def infer_surface_type_and_direction(
-    binary_mask: np.ndarray,
-    image_width: int,
-    image_height: int,
-    texture_name: str,
-) -> tuple[str, float, float, int]:
-    mask_u8 = (binary_mask > 0).astype(np.uint8)
-    ys, xs = np.where(mask_u8 > 0)
-    if ys.size == 0 or xs.size == 0:
-        return ("wall", 0.0, 0.78, max(180, image_width // 4))
-
-    min_x, max_x = int(xs.min()), int(xs.max())
-    min_y, max_y = int(ys.min()), int(ys.max())
-    bbox_w = max(1, max_x - min_x + 1)
-    bbox_h = max(1, max_y - min_y + 1)
-    aspect = bbox_w / max(1.0, float(bbox_h))
-    center_y = float(ys.mean()) / max(1.0, float(image_height))
-    dominant_angle = estimate_mask_orientation_degrees(binary_mask)
-    material = classify_texture_material(texture_name)
-
-    # Trapezoid score: floor in perspective is wider at the bottom than the top
-    trapezoid_score = _compute_trapezoid_score_from_mask(binary_mask, ys, xs, min_y, max_y, bbox_h)
-
-    is_ceiling = center_y < 0.26 and aspect > 1.35
-    # Floor: low center + trapezoidal shape, OR clearly low + wide
-    is_floor = (
-        (center_y > 0.55 and aspect >= 0.9 and trapezoid_score > 0.30)
-        or (center_y > 0.68 and aspect > 1.15)
-    )
-
-    if is_ceiling:
-        surface_type = "ceiling"
-        angle = 0.0
-        blend_alpha = 0.58
-        tile_width = max(128, image_width // 5)
-    elif is_floor:
-        if material == "wood":
-            surface_type = "deck"
-            angle = dominant_angle if 8.0 <= dominant_angle <= 172.0 else 0.0
-            blend_alpha = 0.82
-            tile_width = max(320, int(bbox_w * 0.95), image_width // 2)
-        else:
-            surface_type = "floor"
-            angle = 0.0
-            blend_alpha = 0.80
-            # ACM floor: ~3 large-format panels visible on the near edge
-            tile_width = max(200, int(bbox_w * 0.35)) if material == "acm" else max(144, image_width // 3)
-    else:
-        surface_type = "wall"
-        angle = 0.0
-        if material == "acm":
-            blend_alpha = 0.78
-            # ACM wall panels: ~3 panels across the surface width
-            tile_width = max(180, int(bbox_w * 0.33))
-        elif material == "wood":
-            blend_alpha = 0.70
-            tile_width = max(220, int(bbox_w * 0.55), image_width // 4)
-        elif material == "stone":
-            blend_alpha = 0.84
-            tile_width = max(128, image_width // 4)
-        else:
-            blend_alpha = 0.66
-            tile_width = max(128, image_width // 4)
-
-    return (surface_type, float(angle % 180.0), float(blend_alpha), int(tile_width))
-
-
-def choose_auto_texture_settings(material: str, surface_type: str) -> tuple[float, float, float]:
-    strength_map = {"acm": 0.98, "stone": 0.96, "wood": 0.88, "metal": 0.91, "generic": 0.9}
-    intensity_map = {"acm": 0.08, "stone": 0.36, "wood": 0.3, "metal": 0.34, "generic": 0.32}
-
-    strength = float(strength_map.get(material, 0.9))
-    intensity = float(intensity_map.get(material, 0.32))
-
-    if surface_type in {"wall", "facade"}:
-        strength += 0.02
-        angle = 28.0
-    elif surface_type in {"roof"}:
-        angle = 42.0
-        intensity += 0.03
-    elif surface_type in {"floor", "deck"}:
-        angle = 24.0
-        intensity += 0.02
-    else:
-        angle = 35.0
-
-    return (
-        float(np.clip(strength, 0.55, 0.99)),
-        float(angle % 360.0),
-        float(np.clip(intensity, 0.0, 1.0)),
-    )
-
-
-def build_feather_mask(binary_mask: np.ndarray, sigma: float = 2.2) -> np.ndarray:
-    mask = (binary_mask > 0).astype(np.float32)
-    if mask.max() <= 0:
-        return mask
-    feather = cv2.GaussianBlur(mask, (0, 0), sigmaX=sigma, sigmaY=sigma)
-    return np.clip(feather, 0.0, 1.0)
-
-
-def build_scene_luminance_map(orig_rgb: np.ndarray) -> np.ndarray:
-    orig_u8 = orig_rgb.astype(np.uint8)
-    orig_lab = cv2.cvtColor(orig_u8, cv2.COLOR_RGB2LAB).astype(np.float32)
-    l_channel = orig_lab[:, :, 0] / 255.0
-    broad_light = cv2.GaussianBlur(l_channel, (0, 0), sigmaX=18.0, sigmaY=18.0)
-    local_detail = l_channel - cv2.GaussianBlur(l_channel, (0, 0), sigmaX=4.0, sigmaY=4.0)
-    light_map = 0.82 + (broad_light * 0.36) + (local_detail * 0.18)
-    return np.clip(light_map, 0.72, 1.22)
-
-
-def build_texture_relief_map(tex_rgb: np.ndarray, material: str = "generic") -> np.ndarray:
-    tex_u8 = tex_rgb.astype(np.uint8)
-    tex_gray = cv2.cvtColor(tex_u8, cv2.COLOR_RGB2GRAY).astype(np.float32) / 255.0
-    micro_relief = tex_gray - cv2.GaussianBlur(tex_gray, (0, 0), sigmaX=3.0, sigmaY=3.0)
-
-    relief_scale = {"acm": 0.35, "stone": 2.8, "wood": 2.2, "metal": 1.8}.get(material, 2.0)
-    return np.clip(micro_relief * relief_scale, -1.0, 1.0)
-
-
-def build_directional_light_map(
-    tex_rgb: np.ndarray,
-    material: str,
-    light_angle_degrees: float,
-    light_intensity: float,
-) -> np.ndarray:
-    tex_u8 = tex_rgb.astype(np.uint8)
-    tex_gray = cv2.cvtColor(tex_u8, cv2.COLOR_RGB2GRAY).astype(np.float32) / 255.0
-    height_map = cv2.GaussianBlur(tex_gray, (0, 0), sigmaX=1.4, sigmaY=1.4)
-    grad_x = cv2.Sobel(height_map, cv2.CV_32F, 1, 0, ksize=3)
-    grad_y = cv2.Sobel(height_map, cv2.CV_32F, 0, 1, ksize=3)
-
-    relief_scale = {"acm": 0.45, "stone": 3.0, "wood": 2.4, "metal": 1.6}.get(material, 2.0)
-
-    nx = -grad_x * relief_scale
-    ny = -grad_y * relief_scale
-    nz = np.ones_like(nx, dtype=np.float32)
-    norm = np.sqrt((nx * nx) + (ny * ny) + (nz * nz)) + 1e-6
-    nx = nx / norm
-    ny = ny / norm
-    nz = nz / norm
-
-    theta = np.deg2rad(float(light_angle_degrees))
-    lx = float(np.cos(theta))
-    ly = float(-np.sin(theta))
-    lz = 0.82
-    light_norm = max(1e-6, float(np.sqrt((lx * lx) + (ly * ly) + (lz * lz))))
-    lx /= light_norm
-    ly /= light_norm
-    lz /= light_norm
-
-    diffuse = np.clip((nx * lx) + (ny * ly) + (nz * lz), 0.0, 1.0)
-    strength = float(np.clip(light_intensity, 0.0, 1.0))
-    if material == "acm":
-        return np.clip(0.97 + (diffuse * (0.03 + (0.12 * strength))), 0.95, 1.12)
-    return np.clip(0.86 + (diffuse * (0.14 + (0.60 * strength))), 0.72, 1.35)
-
-
-def build_mask_edge_occlusion(binary_mask: np.ndarray, light_intensity: float) -> np.ndarray:
-    mask_u8 = (binary_mask > 0).astype(np.uint8)
-    if mask_u8.max() == 0:
-        return np.ones(mask_u8.shape, dtype=np.float32)
-
-    distance = cv2.distanceTransform(mask_u8, cv2.DIST_L2, 5).astype(np.float32)
-    inner_values = distance[mask_u8 > 0]
-    if inner_values.size == 0:
-        return np.ones(mask_u8.shape, dtype=np.float32)
-
-    max_distance = max(1.0, float(np.percentile(inner_values, 95)))
-    normalized = np.clip(distance / (max_distance * 0.16), 0.0, 1.0)
-    edge_strength = 1.0 - normalized
-    occlusion = 1.0 - (edge_strength * (0.04 + (0.08 * float(np.clip(light_intensity, 0.0, 1.0)))))
-    occlusion[mask_u8 == 0] = 1.0
-    return np.clip(occlusion, 0.88, 1.0)
-
-
-def apply_surface_lighting(
-    tex_rgb: np.ndarray,
-    orig_rgb: np.ndarray,
-    binary_mask: np.ndarray,
-    material: str,
-    lighting_mode: str,
-    light_angle_degrees: float,
-    light_intensity: float,
-) -> np.ndarray:
-    scene_light = build_scene_luminance_map(orig_rgb)
-    directional_light = build_directional_light_map(tex_rgb, material, light_angle_degrees, light_intensity)
-    relief_map = build_texture_relief_map(tex_rgb, material)
-    edge_occlusion = build_mask_edge_occlusion(binary_mask, light_intensity)
-
-    if material == "acm":
-        if lighting_mode == "directional":
-            light_map = directional_light
-        elif lighting_mode == "flat":
-            light_map = np.ones(scene_light.shape, dtype=np.float32)
-        else:
-            # 45 % scene luminance so ACM panels inherit shadows/gradients from photo
-            light_map = (scene_light * 0.45) + (directional_light * 0.55)
-    elif lighting_mode == "directional":
-        light_map = directional_light
-    elif lighting_mode == "flat":
-        light_map = np.ones(scene_light.shape, dtype=np.float32)
-    else:
-        light_map = (scene_light * 0.78) + (directional_light * 0.22)
-
-    detail_scale = 0.02 + (0.05 * float(np.clip(light_intensity, 0.0, 1.0))) if material == "acm" else 0.08 + (0.18 * float(np.clip(light_intensity, 0.0, 1.0)))
-    detail_boost = 1.0 + (relief_map * detail_scale)
-    enhanced = tex_rgb.astype(np.float32)
-    enhanced *= light_map[:, :, None]
-    enhanced *= detail_boost[:, :, None]
-    enhanced *= edge_occlusion[:, :, None]
-    return np.clip(enhanced, 0, 255).astype(np.uint8)
-
-
-def blend_texture_preserve_shading(
-    orig_rgb: np.ndarray,
-    tex_rgb: np.ndarray,
-    alpha_mask: np.ndarray,
-    blend_alpha: float,
-    material: str = "generic",
-) -> np.ndarray:
-    orig_u8 = orig_rgb.astype(np.uint8)
-    tex_u8 = tex_rgb.astype(np.uint8)
-
-    orig_lab = cv2.cvtColor(orig_u8, cv2.COLOR_RGB2LAB).astype(np.float32)
-    tex_lab = cv2.cvtColor(tex_u8, cv2.COLOR_RGB2LAB).astype(np.float32)
-
-    mixed_lab = tex_lab.copy()
-    if material == "acm":
-        # 30 % original luminance → panels inherit scene shadows while keeping panel colour
-        mixed_lab[:, :, 0] = (0.30 * orig_lab[:, :, 0]) + (0.70 * tex_lab[:, :, 0])
-        mixed_lab[:, :, 1] = (0.97 * tex_lab[:, :, 1]) + (0.03 * orig_lab[:, :, 1])
-        mixed_lab[:, :, 2] = (0.97 * tex_lab[:, :, 2]) + (0.03 * orig_lab[:, :, 2])
-    elif material == "wood":
-        mixed_lab[:, :, 0] = (0.78 * orig_lab[:, :, 0]) + (0.22 * tex_lab[:, :, 0])
-        mixed_lab[:, :, 1] = (0.9 * tex_lab[:, :, 1]) + (0.1 * orig_lab[:, :, 1])
-        mixed_lab[:, :, 2] = (0.9 * tex_lab[:, :, 2]) + (0.1 * orig_lab[:, :, 2])
-    elif material == "stone":
-        orig_l_base = cv2.GaussianBlur(orig_lab[:, :, 0], (0, 0), sigmaX=11.0, sigmaY=11.0)
-        mixed_lab[:, :, 0] = (0.18 * orig_l_base) + (0.82 * tex_lab[:, :, 0])
-        mixed_lab[:, :, 1] = (0.95 * tex_lab[:, :, 1]) + (0.05 * orig_lab[:, :, 1])
-        mixed_lab[:, :, 2] = (0.95 * tex_lab[:, :, 2]) + (0.05 * orig_lab[:, :, 2])
-    else:
-        mixed_lab[:, :, 0] = orig_lab[:, :, 0]
-        mixed_lab[:, :, 1] = (0.8 * tex_lab[:, :, 1]) + (0.2 * orig_lab[:, :, 1])
-        mixed_lab[:, :, 2] = (0.8 * tex_lab[:, :, 2]) + (0.2 * orig_lab[:, :, 2])
-
-    shaded_tex = cv2.cvtColor(np.clip(mixed_lab, 0, 255).astype(np.uint8), cv2.COLOR_LAB2RGB).astype(np.float32)
-    if material == "wood":
-        tex_gray = cv2.cvtColor(tex_u8, cv2.COLOR_RGB2GRAY).astype(np.float32)
-        tex_base = cv2.GaussianBlur(tex_gray, (0, 0), sigmaX=9.0, sigmaY=9.0)
-        tex_detail = np.clip((tex_gray - tex_base) / 255.0, -0.35, 0.35)
-        shaded_tex *= (1.0 + (tex_detail[:, :, None] * 0.28))
-
-    alpha = np.clip(alpha_mask[:, :, None] * float(blend_alpha), 0.0, 1.0)
-    composite = (orig_rgb * (1.0 - alpha)) + (shaded_tex * alpha)
-    return np.clip(composite, 0, 255).astype(np.uint8)
-
-
-def blend_texture_direct(
-    orig_rgb: np.ndarray,
-    tex_rgb: np.ndarray,
-    alpha_mask: np.ndarray,
-    blend_alpha: float,
-) -> np.ndarray:
-    alpha = np.clip(alpha_mask[:, :, None] * float(blend_alpha), 0.0, 1.0)
-    composite = (orig_rgb * (1.0 - alpha)) + (tex_rgb * alpha)
-    return np.clip(composite, 0, 255).astype(np.uint8)
-
-
-def apply_local_texture_sync(payload: ApplyTextureRequest) -> dict[str, Any]:
-    step = "APPLY_TEXTURE"
-    started = log_timing_start(step)
-    try:
-        safe_name = Path(payload.filename).name
-        if not safe_name:
-            raise HTTPException(status_code=400, detail="Invalid filename")
-
-        label_safe_name = Path(payload.original_filename).name if payload.original_filename else safe_name
-
-        image_path = UPLOAD_DIR / safe_name
-        if not image_path.exists() or not image_path.is_file():
-            image_path = OUTPUT_DIR / safe_name
-
-        if (not image_path.exists() or not image_path.is_file()) and payload.original_filename:
-            orig_name = Path(payload.original_filename).name
-            image_path = UPLOAD_DIR / orig_name
-            if not image_path.exists() or not image_path.is_file():
-                image_path = OUTPUT_DIR / orig_name
-
-        if not image_path.exists() or not image_path.is_file():
-            raise HTTPException(
-                status_code=404,
-                detail=f"Image not found: {safe_name} (also tried original: {payload.original_filename or 'n/a'})",
-            )
-
-        masks_dir = UPLOAD_DIR / "masks"
-        masks_dir.mkdir(exist_ok=True)
-        label_owner = Path(image_path).stem
-        label_path = masks_dir / f"{label_owner}_labels.png"
-        if not label_path.exists() and payload.original_filename:
-            alt_owner = Path(payload.original_filename).name
-            alt_label = masks_dir / f"{alt_owner}_labels.png"
-            if alt_label.exists():
-                label_path = alt_label
-
-        if not label_path.exists():
-            raise HTTPException(
-                status_code=404,
-                detail=f"Label map not found for {label_owner}. Upload/segment the image first.",
-            )
-
-        if not payload.mask_indices:
-            raise HTTPException(status_code=400, detail="No mask indices provided")
-
-        texture_path = resolve_texture_path(payload.texture_name)
-        orig_pil = Image.open(str(image_path)).convert("RGB")
-        width, height = orig_pil.size
-
-        label_map = cv2.imread(str(label_path), cv2.IMREAD_GRAYSCALE)
-        if label_map is None:
-            raise HTTPException(status_code=500, detail="Could not read label map")
-
-        binary_mask = np.zeros((label_map.shape[0], label_map.shape[1]), dtype=np.uint8)
-        for idx in payload.mask_indices:
-            binary_mask |= (label_map == idx).astype(np.uint8)
-
-        if binary_mask.max() == 0:
-            raise HTTPException(status_code=400, detail="None of the selected segments were found in the label map.")
-
-        direction_mode = str(payload.direction_mode or "auto").strip().lower()
-        if direction_mode not in {"auto", "manual", "none"}:
-            raise HTTPException(status_code=400, detail="Invalid direction_mode. Use auto, manual, or none.")
-
-        replace_mode = str(getattr(payload, "replace_mode", "realistic") or "realistic").strip().lower()
-        lighting_mode = str(getattr(payload, "lighting_mode", "scene") or "scene").strip().lower()
-
-        material = classify_texture_material(payload.texture_name)
-        surface_type, inferred_angle, blend_alpha, target_w = infer_surface_type_and_direction(
-            binary_mask, width, height, payload.texture_name,
-        )
-        replace_strength, light_angle_degrees, light_intensity = choose_auto_texture_settings(material, surface_type)
-        effective_alpha = float(np.clip(blend_alpha * (0.55 + (0.75 * replace_strength)), 0.0, 0.98))
-        if material == "acm":
-            effective_alpha = float(max(effective_alpha, 0.92))
-
-        applied_angle = 0.0
-        if direction_mode == "auto":
-            applied_angle = inferred_angle
-        elif direction_mode == "manual":
-            applied_angle = float(payload.angle_degrees)
-
-        tex_pil = load_texture_pil_rgb(texture_path)
-
-        # Escalar al tamaño de tile deseado ANTES de rotar
-        tex_w, tex_h = tex_pil.size
-        scale = target_w / max(1, tex_w)
-        if abs(scale - 1.0) > 0.05:
-            tex_pil = tex_pil.resize(
-                (max(1, int(tex_w * scale)), max(1, int(tex_h * scale))),
-                Image.Resampling.LANCZOS,
-            )
-            tex_w, tex_h = tex_pil.size
-
-        tiled: Image.Image | None = None
-
-        # Floor surfaces: perspective tiling solo cuando la perspectiva es fuerte.
-        # Para pisos de dormitorio/habitación (perspectiva suave) el quad aproximado
-        # no cubre bien el mask irregular → produce negro. Se usa tiling regular en esos casos.
-        if surface_type == "floor" and direction_mode in {"auto", "none"}:
-            ys_m, xs_m = np.where(binary_mask > 0)
-            if ys_m.size > 0:
-                min_y_m, max_y_m = int(ys_m.min()), int(ys_m.max())
-                bbox_h_m = max(1, max_y_m - min_y_m + 1)
-                trap_score = _compute_trapezoid_score_from_mask(
-                    binary_mask, ys_m, xs_m, min_y_m, max_y_m, bbox_h_m
-                )
-                if trap_score > 0.35:
-                    quad = _extract_mask_quad(binary_mask)
-                    if quad is not None:
-                        tiled = _tile_texture_perspective(tex_pil, quad, width, height)
-                        if tiled is not None:
-                            logger.info(f"[APPLY_TEXTURE] perspective floor tiling applied (trap={trap_score:.2f})")
-                else:
-                    logger.info(f"[APPLY_TEXTURE] flat floor tiling (trap={trap_score:.2f} < 0.35, skip perspective)")
-
-        # Wall / ceiling surfaces: perspective tiling cuando el quad es significativamente
-        # no-rectangular (pared fotografiada en ángulo). Un ratio > 1.20 entre lado mayor
-        # y lado menor indica distorsión perspectiva visible.
-        if surface_type in {"wall", "ceiling"} and tiled is None and direction_mode in {"auto", "none"}:
-            quad = _extract_mask_quad(binary_mask)
-            if quad is not None:
-                tl, tr, br, bl = quad
-                top_w   = float(np.linalg.norm(tr.astype(float) - tl.astype(float)))
-                bot_w   = float(np.linalg.norm(br.astype(float) - bl.astype(float)))
-                left_h  = float(np.linalg.norm(bl.astype(float) - tl.astype(float)))
-                right_h = float(np.linalg.norm(br.astype(float) - tr.astype(float)))
-                w_ratio = max(top_w, bot_w) / max(1.0, min(top_w, bot_w))
-                h_ratio = max(left_h, right_h) / max(1.0, min(left_h, right_h))
-                if w_ratio > 1.20 or h_ratio > 1.20:
-                    tiled = _tile_texture_perspective(tex_pil, quad, width, height)
-                    if tiled is not None:
-                        logger.info(
-                            f"[APPLY_TEXTURE] perspective wall tiling applied "
-                            f"(w_ratio={w_ratio:.2f}, h_ratio={h_ratio:.2f})"
-                        )
-
-        if tiled is None:
-            if abs(applied_angle) > 0.01:
-                # Tile on a large canvas first, then rotate the full canvas to avoid black corners
-                diag = int(np.ceil(np.sqrt(width ** 2 + height ** 2))) + max(tex_w, tex_h)
-                large_w = width + diag
-                large_h = height + diag
-                large = Image.new("RGB", (large_w, large_h))
-                for y in range(0, large_h, tex_h):
-                    for x in range(0, large_w, tex_w):
-                        large.paste(tex_pil, (x, y))
-                large = large.rotate(-applied_angle, resample=Image.Resampling.BICUBIC, expand=False)
-                cx = (large_w - width) // 2
-                cy = (large_h - height) // 2
-                tiled = large.crop((cx, cy, cx + width, cy + height))
-            else:
-                tiled = Image.new("RGB", (width, height))
-                for y in range(0, height, tex_h):
-                    for x in range(0, width, tex_w):
-                        tiled.paste(tex_pil, (x, y))
-
-        orig_u8 = np.array(orig_pil, dtype=np.uint8)
-
-        try:
-            if bool(getattr(payload, "clear_mask_before_apply", False)):
-                orig_candidate = None
-                if payload.original_filename:
-                    cand = UPLOAD_DIR / Path(payload.original_filename).name
-                    if cand.exists() and cand.is_file():
-                        orig_candidate = cand
-                    else:
-                        cand2 = OUTPUT_DIR / Path(payload.original_filename).name
-                        if cand2.exists() and cand2.is_file():
-                            orig_candidate = cand2
-                if orig_candidate is None:
-                    stem = Path(image_path).stem
-                    if "_edit_" in stem:
-                        base_name = stem.split("_edit_")[0] + ".jpg"
-                        cand = UPLOAD_DIR / base_name
-                        if cand.exists() and cand.is_file():
-                            orig_candidate = cand
-                        else:
-                            cand2 = OUTPUT_DIR / base_name
-                            if cand2.exists() and cand2.is_file():
-                                orig_candidate = cand2
-
-                if orig_candidate is not None:
-                    try:
-                        base_pil = Image.open(str(orig_candidate)).convert("RGB")
-                        if base_pil.size != (width, height):
-                            base_pil = base_pil.resize((width, height), Image.Resampling.LANCZOS)
-                        base_arr = np.array(base_pil, dtype=np.uint8)
-                        mask_bool = (binary_mask > 0)
-                        orig_u8[mask_bool] = base_arr[mask_bool]
-                        logger.info(f"[APPLY_TEXTURE] cleared mask from original source: {orig_candidate}")
-                    except Exception:
-                        logger.exception("Failed to restore original pixels for clear_mask_before_apply")
-        except Exception:
-            logger.exception("Error handling clear_mask_before_apply")
-
-        tiled_arr = np.array(tiled, dtype=np.uint8)
-
-        # Parchar píxeles muy oscuros (suma R+G+B < 20) dentro de la máscara.
-        # Cubren tanto negro exacto (0,0,0) como píxeles casi negros que el warp
-        # de perspectiva puede generar en bordes del quad o zonas sin cobertura.
-        mask_bool = binary_mask > 0
-        dark_in_mask = mask_bool & (tiled_arr.sum(axis=2) < 20)
-        if dark_in_mask.any():
-            th_f, tw_f = tex_pil.size[1], tex_pil.size[0]
-            tex_np = np.array(tex_pil, dtype=np.uint8)
-            ys_b, xs_b = np.where(dark_in_mask)
-            tiled_arr[ys_b, xs_b] = tex_np[ys_b % th_f, xs_b % tw_f]
-
-        lit_tex = apply_surface_lighting(
-            tiled_arr,
-            orig_u8,
-            binary_mask,
-            material,
-            lighting_mode,
-            light_angle_degrees,
-            light_intensity,
-        )
-
-        orig_arr = orig_u8.astype(np.float32)
-        tex_arr = lit_tex.astype(np.float32)
-
-        if replace_mode in {"hard", "absolute", "force", "replace"}:
-            mask_bool = (binary_mask > 0).astype(bool)
-            composite_arr = orig_arr.copy()
-            composite_arr[mask_bool] = tex_arr[mask_bool]
-            composite = np.clip(composite_arr, 0, 255).astype(np.uint8)
-        else:
-            feather_mask = build_feather_mask(binary_mask)
-            # All materials use shading-preservation so scene luminance (shadows/highlights)
-            # from the original photo is transferred onto the texture.
-            composite = blend_texture_preserve_shading(orig_arr, tex_arr, feather_mask, effective_alpha, material)
-
-        input_stem = Path(image_path).stem
-        edit_suffix = uuid.uuid4().hex[:8]
-        out_filename = f"{input_stem}_edit_{edit_suffix}.jpg"
-        out_path = UPLOAD_DIR / out_filename
-        Image.fromarray(composite).save(str(out_path), format="JPEG", quality=UPLOAD_JPEG_QUALITY, optimize=True)
-
-        try:
-            out_label_path = masks_dir / f"{Path(out_filename).stem}_labels.png"
-            if label_path.exists():
-                shutil.copyfile(str(label_path), str(out_label_path))
-        except Exception:
-            logger.exception("Failed to copy label map for output image")
-
-        return {
-            "message": "Texture applied successfully",
-            "original": safe_name,
-            "mask_indices": payload.mask_indices,
-            "texture_name": payload.texture_name,
-            "material": material,
-            "direction_mode": direction_mode,
-            "surface_type": surface_type,
-            "replace_mode": replace_mode,
-            "replace_strength": round(replace_strength, 3),
-            "lighting_mode": lighting_mode,
-            "light_angle_degrees": round(light_angle_degrees, 2),
-            "light_intensity": round(light_intensity, 3),
-            "blend_alpha": round(effective_alpha, 3),
-            "applied_angle_degrees": round(applied_angle, 2),
-            "output_filename": out_filename,
-            "output_url": f"/seg/image/{out_filename}",
-        }
-    finally:
-        log_timing_end(step, started)
+import io
+import shutil
+import uuid
+from pathlib import Path
+from typing import Any
+
+import cv2
+import numpy as np
+from fastapi import HTTPException
+from PIL import Image
+
+from core.config import (
+    OUTPUT_DIR,
+    TEXTURE_DIR,
+    UPLOAD_DIR,
+    UPLOAD_JPEG_QUALITY,
+    log_timing_end,
+    log_timing_start,
+    logger,
+)
+from models.schemas import ApplyTextureRequest
+
+
+def generate_texture_variations(texture_name: str) -> list[dict[str, str]]:
+    """
+    Genera variaciones de color/brillo/saturación de una textura de referencia usando HSV.
+    Los archivos se cachean en TEXTURE_DIR/generated/ — si ya existen no se regeneran.
+    Devuelve lista de {ref, label, preview_url}.
+    """
+    texture_path = resolve_texture_path(texture_name)
+    generated_dir = TEXTURE_DIR / "generated"
+    generated_dir.mkdir(parents=True, exist_ok=True)
+
+    tex_pil = load_texture_pil_rgb(texture_path)
+    tex_bgr = cv2.cvtColor(np.array(tex_pil, dtype=np.uint8), cv2.COLOR_RGB2BGR)
+    tex_hsv = cv2.cvtColor(tex_bgr, cv2.COLOR_BGR2HSV).astype(np.int32)
+
+    base_stem = Path(texture_name).stem
+    results: list[dict[str, str]] = []
+
+    def _save(hsv: np.ndarray, suffix: str, label: str) -> None:
+        fname = f"{base_stem}__{suffix}.jpg"
+        out_path = generated_dir / fname
+        if not out_path.exists():
+            bgr = cv2.cvtColor(np.clip(hsv, 0, 255).astype(np.uint8), cv2.COLOR_HSV2BGR)
+            rgb = cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB)
+            Image.fromarray(rgb).save(str(out_path), format="JPEG", quality=92, optimize=True)
+        ref = f"generated/{fname}"
+        results.append({"ref": ref, "label": label, "preview_url": f"/seg/texture-preview/{ref}"})
+
+    # Rotaciones de tono: 12 pasos de 30° recorriendo el círculo cromático
+    # En OpenCV HSV, H ∈ [0,179] → shift en grados / 2
+    for deg, label in [
+        (30,  "Naranja"),
+        (60,  "Amarillo"),
+        (90,  "Verde lima"),
+        (120, "Verde"),
+        (150, "Verde agua"),
+        (165, "Cyan"),
+        (180, "Azul cielo"),
+        (210, "Azul"),
+        (240, "Índigo"),
+        (270, "Violeta"),
+        (300, "Magenta"),
+        (330, "Rosa"),
+    ]:
+        v = tex_hsv.copy()
+        v[:, :, 0] = (v[:, :, 0] + deg // 2) % 180
+        _save(v, f"hue{deg}", label)
+
+    # Variaciones de brillo
+    for factor, label, suffix in [
+        (0.45, "Oscuro",  "dark"),
+        (1.55, "Claro",   "light"),
+    ]:
+        v = tex_hsv.copy()
+        v[:, :, 2] = np.clip(v[:, :, 2] * factor, 0, 255)
+        _save(v, suffix, label)
+
+    # Variaciones de saturación
+    for factor, label, suffix in [
+        (0.0,  "Gris",    "gray"),
+        (0.45, "Apagado", "muted"),
+        (1.75, "Vívido",  "vivid"),
+    ]:
+        v = tex_hsv.copy()
+        v[:, :, 1] = np.clip(v[:, :, 1] * factor, 0, 255)
+        _save(v, suffix, label)
+
+    return results
+
+
+def list_available_textures() -> list[str]:
+    allowed = {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".tif", ".tiff", ".exr"}
+    return [
+        str(path.relative_to(TEXTURE_DIR)).replace("\\", "/")
+        for path in sorted(TEXTURE_DIR.rglob("*"))
+        if path.is_file() and path.suffix.lower() in allowed
+    ]
+
+
+def resolve_texture_path(texture_name: str) -> Path:
+    if not texture_name:
+        raise HTTPException(status_code=400, detail="Invalid texture_name")
+
+    normalized = texture_name.replace("\\", "/").strip("/")
+    candidate = (TEXTURE_DIR / normalized).resolve()
+    base = TEXTURE_DIR.resolve()
+
+    try:
+        candidate.relative_to(base)
+    except ValueError as exc:
+        raise HTTPException(status_code=400, detail="Invalid texture_name") from exc
+
+    if not candidate.exists() or not candidate.is_file():
+        raise HTTPException(status_code=404, detail=f"Texture not found: {normalized}")
+
+    return candidate
+
+
+def build_texture_preview_jpeg(texture_path: Path, max_size: int = 320) -> bytes:
+    pil_img = load_texture_pil_rgb(texture_path)
+    pil_img.thumbnail((max_size, max_size), Image.Resampling.LANCZOS)
+    out = io.BytesIO()
+    pil_img.save(out, format="JPEG", quality=88, optimize=True)
+    return out.getvalue()
+
+
+def load_texture_pil_rgb(texture_path: Path) -> Image.Image:
+    suffix = texture_path.suffix.lower()
+
+    if suffix != ".exr":
+        try:
+            return Image.open(str(texture_path)).convert("RGB")
+        except Exception as exc:
+            raise HTTPException(status_code=500, detail=f"Could not read texture file: {exc}") from exc
+
+    exr = cv2.imread(str(texture_path), cv2.IMREAD_UNCHANGED)
+    if exr is None:
+        raise HTTPException(status_code=500, detail="Could not decode EXR texture")
+
+    if exr.ndim == 2:
+        exr = np.stack([exr, exr, exr], axis=-1)
+    if exr.ndim != 3:
+        raise HTTPException(status_code=500, detail="EXR texture has unsupported shape")
+    if exr.shape[2] > 3:
+        exr = exr[:, :, :3]
+
+    exr = np.nan_to_num(exr, nan=0.0, posinf=0.0, neginf=0.0)
+    exr = np.maximum(exr, 0)
+
+    if np.issubdtype(exr.dtype, np.floating):
+        scale = float(np.percentile(exr, 99.0))
+        if scale <= 1e-8:
+            scale = float(np.max(exr))
+        if scale <= 1e-8:
+            scale = 1.0
+        img = np.clip(exr / scale, 0.0, 1.0)
+        img = np.power(img, 1.0 / 2.2)
+        img_u8 = (img * 255.0).astype(np.uint8)
+    elif exr.dtype == np.uint16:
+        img_u8 = (exr / 257.0).astype(np.uint8)
+    else:
+        img_u8 = np.clip(exr, 0, 255).astype(np.uint8)
+
+    img_rgb = cv2.cvtColor(img_u8, cv2.COLOR_BGR2RGB)
+    return Image.fromarray(img_rgb).convert("RGB")
+
+
+def estimate_mask_orientation_degrees(binary_mask: np.ndarray) -> float:
+    mask_u8 = (binary_mask > 0).astype(np.uint8)
+    contours, _ = cv2.findContours(mask_u8, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    if not contours:
+        return 0.0
+
+    largest = max(contours, key=cv2.contourArea)
+    if cv2.contourArea(largest) < 25.0:
+        return 0.0
+
+    rect = cv2.minAreaRect(largest)
+    (_, _), (width, height), angle = rect
+
+    dominant_angle = float(angle)
+    if width < height:
+        dominant_angle += 90.0
+
+    dominant_angle %= 180.0
+    return dominant_angle
+
+
+def _compute_trapezoid_score_from_mask(
+    binary_mask: np.ndarray,
+    ys: np.ndarray,
+    xs: np.ndarray,
+    min_y: int,
+    max_y: int,
+    bbox_h: int,
+) -> float:
+    """Return 0..1 indicating how floor-like (wider at bottom) the mask shape is."""
+    quarter = max(1, bbox_h // 4)
+    top_xs = xs[ys <= (min_y + quarter)]
+    bot_xs = xs[ys >= (max_y - quarter)]
+    if len(top_xs) < 3 or len(bot_xs) < 3:
+        return 0.0
+    top_w = float(top_xs.max() - top_xs.min())
+    bot_w = float(bot_xs.max() - bot_xs.min())
+    if top_w < 5.0:
+        return 1.0 if bot_w > 20.0 else 0.0
+    ratio = bot_w / top_w
+    return float(np.clip((ratio - 1.0) / 1.8, 0.0, 1.0))
+
+
+def _sort_quad_corners(pts: np.ndarray) -> np.ndarray:
+    """Sort 4 points into [TL, TR, BR, BL] order."""
+    result = np.zeros((4, 2), dtype=np.float32)
+    s = pts[:, 0] + pts[:, 1]
+    d = pts[:, 0] - pts[:, 1]
+    result[0] = pts[np.argmin(s)]
+    result[1] = pts[np.argmax(d)]
+    result[2] = pts[np.argmax(s)]
+    result[3] = pts[np.argmin(d)]
+    return result
+
+
+def _extract_mask_quad(binary_mask: np.ndarray) -> np.ndarray | None:
+    """Approximate mask as 4-corner polygon sorted [TL, TR, BR, BL], or None."""
+    mask_u8 = (binary_mask > 0).astype(np.uint8)
+    contours, _ = cv2.findContours(mask_u8, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    if not contours:
+        return None
+    largest = max(contours, key=cv2.contourArea)
+    if cv2.contourArea(largest) < 400.0:
+        return None
+    hull = cv2.convexHull(largest)
+    peri = cv2.arcLength(hull, True)
+    for eps_frac in (0.03, 0.05, 0.08, 0.10, 0.13):
+        approx = cv2.approxPolyDP(hull, eps_frac * peri, True)
+        if len(approx) == 4:
+            return _sort_quad_corners(approx.reshape(4, 2).astype(np.float32))
+    return None
+
+
+def _tile_texture_perspective(
+    tex_pil: Image.Image,
+    quad: np.ndarray,
+    image_width: int,
+    image_height: int,
+) -> Image.Image | None:
+    """
+    Tile texture with perspective correction for a floor surface.
+    quad: [TL, TR, BR, BL] in image coordinates.
+    Returns full-image-size PIL image with warped tiled texture, or None on failure.
+    Pixels outside the perspective quad are filled with regular tiling to avoid black gaps.
+    """
+    tl, tr, br, bl = quad
+    bot_w = float(np.linalg.norm(br.astype(float) - bl.astype(float)))
+    top_w = float(np.linalg.norm(tr.astype(float) - tl.astype(float)))
+    left_h = float(np.linalg.norm(bl.astype(float) - tl.astype(float)))
+    right_h = float(np.linalg.norm(br.astype(float) - tr.astype(float)))
+    rect_w = min(int(max(bot_w, top_w)) + 1, image_width * 2)
+    rect_h = min(int(max(left_h, right_h)) + 1, image_height * 2)
+    if rect_w < 8 or rect_h < 8:
+        return None
+    tex_arr = np.array(tex_pil.convert("RGB"), dtype=np.uint8)
+    th, tw = tex_arr.shape[:2]
+    if tw < 1 or th < 1:
+        return None
+    rect_tiled = np.zeros((rect_h, rect_w, 3), dtype=np.uint8)
+    for ry in range(0, rect_h, th):
+        for rx in range(0, rect_w, tw):
+            py = min(th, rect_h - ry)
+            px = min(tw, rect_w - rx)
+            rect_tiled[ry : ry + py, rx : rx + px] = tex_arr[:py, :px]
+    src_pts = np.array(
+        [[0.0, 0.0], [float(rect_w - 1), 0.0], [float(rect_w - 1), float(rect_h - 1)], [0.0, float(rect_h - 1)]],
+        dtype=np.float32,
+    )
+    dst_pts = quad.astype(np.float32)
+    try:
+        H = cv2.getPerspectiveTransform(src_pts, dst_pts)
+        warped = cv2.warpPerspective(rect_tiled, H, (image_width, image_height))
+        # Mapa de cobertura: píxeles realmente cubiertos por el warp
+        cov_src = np.ones((rect_h, rect_w), dtype=np.uint8) * 255
+        coverage = cv2.warpPerspective(cov_src, H, (image_width, image_height))
+    except cv2.error:
+        return None
+
+    # Rellenar píxeles sin cobertura (fuera del quad) con tiling regular
+    # para evitar espacios negros donde la máscara supera el quad aproximado
+    regular = np.zeros((image_height, image_width, 3), dtype=np.uint8)
+    for ry in range(0, image_height, th):
+        for rx in range(0, image_width, tw):
+            py = min(th, image_height - ry)
+            px = min(tw, image_width - rx)
+            regular[ry : ry + py, rx : rx + px] = tex_arr[:py, :px]
+
+    uncovered = coverage < 128
+    warped[uncovered] = regular[uncovered]
+
+    return Image.fromarray(warped)
+
+
+def classify_texture_material(texture_name: str) -> str:
+    texture_key = texture_name.lower()
+    if "acm" in texture_key or "wpc" in texture_key:
+        return "acm"
+    if any(hint in texture_key for hint in ("deck", "wood", "plank", "laminate", "floor")):
+        return "wood"
+    if any(hint in texture_key for hint in ("marble", "granite", "tile", "brick", "cobblestone", "stone", "cartago", "riverbed")):
+        return "stone"
+    if any(hint in texture_key for hint in ("metal", "rust", "iron", "steel")):
+        return "metal"
+    return "generic"
+
+
+def infer_surface_type_and_direction(
+    binary_mask: np.ndarray,
+    image_width: int,
+    image_height: int,
+    texture_name: str,
+) -> tuple[str, float, float, int]:
+    mask_u8 = (binary_mask > 0).astype(np.uint8)
+    ys, xs = np.where(mask_u8 > 0)
+    if ys.size == 0 or xs.size == 0:
+        return ("wall", 0.0, 0.78, max(180, image_width // 4))
+
+    min_x, max_x = int(xs.min()), int(xs.max())
+    min_y, max_y = int(ys.min()), int(ys.max())
+    bbox_w = max(1, max_x - min_x + 1)
+    bbox_h = max(1, max_y - min_y + 1)
+    aspect = bbox_w / max(1.0, float(bbox_h))
+    center_y = float(ys.mean()) / max(1.0, float(image_height))
+    dominant_angle = estimate_mask_orientation_degrees(binary_mask)
+    material = classify_texture_material(texture_name)
+
+    # Trapezoid score: floor in perspective is wider at the bottom than the top
+    trapezoid_score = _compute_trapezoid_score_from_mask(binary_mask, ys, xs, min_y, max_y, bbox_h)
+
+    is_ceiling = center_y < 0.26 and aspect > 1.35
+    # Floor: low center + trapezoidal shape, OR clearly low + wide
+    is_floor = (
+        (center_y > 0.55 and aspect >= 0.9 and trapezoid_score > 0.30)
+        or (center_y > 0.68 and aspect > 1.15)
+    )
+
+    if is_ceiling:
+        surface_type = "ceiling"
+        angle = 0.0
+        blend_alpha = 0.58
+        tile_width = max(128, image_width // 5)
+    elif is_floor:
+        if material == "wood":
+            surface_type = "deck"
+            angle = dominant_angle if 8.0 <= dominant_angle <= 172.0 else 0.0
+            blend_alpha = 0.82
+            tile_width = max(320, int(bbox_w * 0.95), image_width // 2)
+        else:
+            surface_type = "floor"
+            angle = 0.0
+            blend_alpha = 0.80
+            # ACM floor: ~3 large-format panels visible on the near edge
+            tile_width = max(200, int(bbox_w * 0.35)) if material == "acm" else max(144, image_width // 3)
+    else:
+        surface_type = "wall"
+        angle = 0.0
+        if material == "acm":
+            blend_alpha = 0.78
+            # ACM wall panels: ~3 panels across the surface width
+            tile_width = max(180, int(bbox_w * 0.33))
+        elif material == "wood":
+            blend_alpha = 0.70
+            tile_width = max(220, int(bbox_w * 0.55), image_width // 4)
+        elif material == "stone":
+            blend_alpha = 0.84
+            tile_width = max(128, image_width // 4)
+        else:
+            blend_alpha = 0.66
+            tile_width = max(128, image_width // 4)
+
+    return (surface_type, float(angle % 180.0), float(blend_alpha), int(tile_width))
+
+
+def choose_auto_texture_settings(material: str, surface_type: str) -> tuple[float, float, float]:
+    strength_map = {"acm": 0.98, "stone": 0.96, "wood": 0.88, "metal": 0.91, "generic": 0.9}
+    intensity_map = {"acm": 0.08, "stone": 0.36, "wood": 0.3, "metal": 0.34, "generic": 0.32}
+
+    strength = float(strength_map.get(material, 0.9))
+    intensity = float(intensity_map.get(material, 0.32))
+
+    if surface_type in {"wall", "facade"}:
+        strength += 0.02
+        angle = 28.0
+    elif surface_type in {"roof"}:
+        angle = 42.0
+        intensity += 0.03
+    elif surface_type in {"floor", "deck"}:
+        angle = 24.0
+        intensity += 0.02
+    else:
+        angle = 35.0
+
+    return (
+        float(np.clip(strength, 0.55, 0.99)),
+        float(angle % 360.0),
+        float(np.clip(intensity, 0.0, 1.0)),
+    )
+
+
+def build_feather_mask(binary_mask: np.ndarray, sigma: float = 2.2) -> np.ndarray:
+    mask = (binary_mask > 0).astype(np.float32)
+    if mask.max() <= 0:
+        return mask
+    feather = cv2.GaussianBlur(mask, (0, 0), sigmaX=sigma, sigmaY=sigma)
+    return np.clip(feather, 0.0, 1.0)
+
+
+def build_scene_luminance_map(orig_rgb: np.ndarray) -> np.ndarray:
+    orig_u8 = orig_rgb.astype(np.uint8)
+    orig_lab = cv2.cvtColor(orig_u8, cv2.COLOR_RGB2LAB).astype(np.float32)
+    l_channel = orig_lab[:, :, 0] / 255.0
+    broad_light = cv2.GaussianBlur(l_channel, (0, 0), sigmaX=18.0, sigmaY=18.0)
+    local_detail = l_channel - cv2.GaussianBlur(l_channel, (0, 0), sigmaX=4.0, sigmaY=4.0)
+    light_map = 0.82 + (broad_light * 0.36) + (local_detail * 0.18)
+    return np.clip(light_map, 0.72, 1.22)
+
+
+def build_texture_relief_map(tex_rgb: np.ndarray, material: str = "generic") -> np.ndarray:
+    tex_u8 = tex_rgb.astype(np.uint8)
+    tex_gray = cv2.cvtColor(tex_u8, cv2.COLOR_RGB2GRAY).astype(np.float32) / 255.0
+    micro_relief = tex_gray - cv2.GaussianBlur(tex_gray, (0, 0), sigmaX=3.0, sigmaY=3.0)
+
+    relief_scale = {"acm": 0.35, "stone": 2.8, "wood": 2.2, "metal": 1.8}.get(material, 2.0)
+    return np.clip(micro_relief * relief_scale, -1.0, 1.0)
+
+
+def build_directional_light_map(
+    tex_rgb: np.ndarray,
+    material: str,
+    light_angle_degrees: float,
+    light_intensity: float,
+) -> np.ndarray:
+    tex_u8 = tex_rgb.astype(np.uint8)
+    tex_gray = cv2.cvtColor(tex_u8, cv2.COLOR_RGB2GRAY).astype(np.float32) / 255.0
+    height_map = cv2.GaussianBlur(tex_gray, (0, 0), sigmaX=1.4, sigmaY=1.4)
+    grad_x = cv2.Sobel(height_map, cv2.CV_32F, 1, 0, ksize=3)
+    grad_y = cv2.Sobel(height_map, cv2.CV_32F, 0, 1, ksize=3)
+
+    relief_scale = {"acm": 0.45, "stone": 3.0, "wood": 2.4, "metal": 1.6}.get(material, 2.0)
+
+    nx = -grad_x * relief_scale
+    ny = -grad_y * relief_scale
+    nz = np.ones_like(nx, dtype=np.float32)
+    norm = np.sqrt((nx * nx) + (ny * ny) + (nz * nz)) + 1e-6
+    nx = nx / norm
+    ny = ny / norm
+    nz = nz / norm
+
+    theta = np.deg2rad(float(light_angle_degrees))
+    lx = float(np.cos(theta))
+    ly = float(-np.sin(theta))
+    lz = 0.82
+    light_norm = max(1e-6, float(np.sqrt((lx * lx) + (ly * ly) + (lz * lz))))
+    lx /= light_norm
+    ly /= light_norm
+    lz /= light_norm
+
+    diffuse = np.clip((nx * lx) + (ny * ly) + (nz * lz), 0.0, 1.0)
+    strength = float(np.clip(light_intensity, 0.0, 1.0))
+    if material == "acm":
+        return np.clip(0.97 + (diffuse * (0.03 + (0.12 * strength))), 0.95, 1.12)
+    return np.clip(0.86 + (diffuse * (0.14 + (0.60 * strength))), 0.72, 1.35)
+
+
+def build_mask_edge_occlusion(binary_mask: np.ndarray, light_intensity: float) -> np.ndarray:
+    mask_u8 = (binary_mask > 0).astype(np.uint8)
+    if mask_u8.max() == 0:
+        return np.ones(mask_u8.shape, dtype=np.float32)
+
+    distance = cv2.distanceTransform(mask_u8, cv2.DIST_L2, 5).astype(np.float32)
+    inner_values = distance[mask_u8 > 0]
+    if inner_values.size == 0:
+        return np.ones(mask_u8.shape, dtype=np.float32)
+
+    max_distance = max(1.0, float(np.percentile(inner_values, 95)))
+    normalized = np.clip(distance / (max_distance * 0.16), 0.0, 1.0)
+    edge_strength = 1.0 - normalized
+    occlusion = 1.0 - (edge_strength * (0.04 + (0.08 * float(np.clip(light_intensity, 0.0, 1.0)))))
+    occlusion[mask_u8 == 0] = 1.0
+    return np.clip(occlusion, 0.88, 1.0)
+
+
+def apply_surface_lighting(
+    tex_rgb: np.ndarray,
+    orig_rgb: np.ndarray,
+    binary_mask: np.ndarray,
+    material: str,
+    lighting_mode: str,
+    light_angle_degrees: float,
+    light_intensity: float,
+) -> np.ndarray:
+    scene_light = build_scene_luminance_map(orig_rgb)
+    directional_light = build_directional_light_map(tex_rgb, material, light_angle_degrees, light_intensity)
+    relief_map = build_texture_relief_map(tex_rgb, material)
+    edge_occlusion = build_mask_edge_occlusion(binary_mask, light_intensity)
+
+    if material == "acm":
+        if lighting_mode == "directional":
+            light_map = directional_light
+        elif lighting_mode == "flat":
+            light_map = np.ones(scene_light.shape, dtype=np.float32)
+        else:
+            # 45 % scene luminance so ACM panels inherit shadows/gradients from photo
+            light_map = (scene_light * 0.45) + (directional_light * 0.55)
+    elif lighting_mode == "directional":
+        light_map = directional_light
+    elif lighting_mode == "flat":
+        light_map = np.ones(scene_light.shape, dtype=np.float32)
+    else:
+        light_map = (scene_light * 0.78) + (directional_light * 0.22)
+
+    detail_scale = 0.02 + (0.05 * float(np.clip(light_intensity, 0.0, 1.0))) if material == "acm" else 0.08 + (0.18 * float(np.clip(light_intensity, 0.0, 1.0)))
+    detail_boost = 1.0 + (relief_map * detail_scale)
+    enhanced = tex_rgb.astype(np.float32)
+    enhanced *= light_map[:, :, None]
+    enhanced *= detail_boost[:, :, None]
+    enhanced *= edge_occlusion[:, :, None]
+    return np.clip(enhanced, 0, 255).astype(np.uint8)
+
+
+def blend_texture_preserve_shading(
+    orig_rgb: np.ndarray,
+    tex_rgb: np.ndarray,
+    alpha_mask: np.ndarray,
+    blend_alpha: float,
+    material: str = "generic",
+) -> np.ndarray:
+    orig_u8 = orig_rgb.astype(np.uint8)
+    tex_u8 = tex_rgb.astype(np.uint8)
+
+    orig_lab = cv2.cvtColor(orig_u8, cv2.COLOR_RGB2LAB).astype(np.float32)
+    tex_lab = cv2.cvtColor(tex_u8, cv2.COLOR_RGB2LAB).astype(np.float32)
+
+    mixed_lab = tex_lab.copy()
+    if material == "acm":
+        # 30 % original luminance → panels inherit scene shadows while keeping panel colour
+        mixed_lab[:, :, 0] = (0.30 * orig_lab[:, :, 0]) + (0.70 * tex_lab[:, :, 0])
+        mixed_lab[:, :, 1] = (0.97 * tex_lab[:, :, 1]) + (0.03 * orig_lab[:, :, 1])
+        mixed_lab[:, :, 2] = (0.97 * tex_lab[:, :, 2]) + (0.03 * orig_lab[:, :, 2])
+    elif material == "wood":
+        mixed_lab[:, :, 0] = (0.78 * orig_lab[:, :, 0]) + (0.22 * tex_lab[:, :, 0])
+        mixed_lab[:, :, 1] = (0.9 * tex_lab[:, :, 1]) + (0.1 * orig_lab[:, :, 1])
+        mixed_lab[:, :, 2] = (0.9 * tex_lab[:, :, 2]) + (0.1 * orig_lab[:, :, 2])
+    elif material == "stone":
+        orig_l_base = cv2.GaussianBlur(orig_lab[:, :, 0], (0, 0), sigmaX=11.0, sigmaY=11.0)
+        mixed_lab[:, :, 0] = (0.18 * orig_l_base) + (0.82 * tex_lab[:, :, 0])
+        mixed_lab[:, :, 1] = (0.95 * tex_lab[:, :, 1]) + (0.05 * orig_lab[:, :, 1])
+        mixed_lab[:, :, 2] = (0.95 * tex_lab[:, :, 2]) + (0.05 * orig_lab[:, :, 2])
+    else:
+        mixed_lab[:, :, 0] = orig_lab[:, :, 0]
+        mixed_lab[:, :, 1] = (0.8 * tex_lab[:, :, 1]) + (0.2 * orig_lab[:, :, 1])
+        mixed_lab[:, :, 2] = (0.8 * tex_lab[:, :, 2]) + (0.2 * orig_lab[:, :, 2])
+
+    shaded_tex = cv2.cvtColor(np.clip(mixed_lab, 0, 255).astype(np.uint8), cv2.COLOR_LAB2RGB).astype(np.float32)
+    if material == "wood":
+        tex_gray = cv2.cvtColor(tex_u8, cv2.COLOR_RGB2GRAY).astype(np.float32)
+        tex_base = cv2.GaussianBlur(tex_gray, (0, 0), sigmaX=9.0, sigmaY=9.0)
+        tex_detail = np.clip((tex_gray - tex_base) / 255.0, -0.35, 0.35)
+        shaded_tex *= (1.0 + (tex_detail[:, :, None] * 0.28))
+
+    alpha = np.clip(alpha_mask[:, :, None] * float(blend_alpha), 0.0, 1.0)
+    composite = (orig_rgb * (1.0 - alpha)) + (shaded_tex * alpha)
+    return np.clip(composite, 0, 255).astype(np.uint8)
+
+
+def blend_texture_direct(
+    orig_rgb: np.ndarray,
+    tex_rgb: np.ndarray,
+    alpha_mask: np.ndarray,
+    blend_alpha: float,
+) -> np.ndarray:
+    alpha = np.clip(alpha_mask[:, :, None] * float(blend_alpha), 0.0, 1.0)
+    composite = (orig_rgb * (1.0 - alpha)) + (tex_rgb * alpha)
+    return np.clip(composite, 0, 255).astype(np.uint8)
+
+
+def apply_local_texture_sync(payload: ApplyTextureRequest) -> dict[str, Any]:
+    step = "APPLY_TEXTURE"
+    started = log_timing_start(step)
+    try:
+        safe_name = Path(payload.filename).name
+        if not safe_name:
+            raise HTTPException(status_code=400, detail="Invalid filename")
+
+        label_safe_name = Path(payload.original_filename).name if payload.original_filename else safe_name
+
+        image_path = UPLOAD_DIR / safe_name
+        if not image_path.exists() or not image_path.is_file():
+            image_path = OUTPUT_DIR / safe_name
+
+        if (not image_path.exists() or not image_path.is_file()) and payload.original_filename:
+            orig_name = Path(payload.original_filename).name
+            image_path = UPLOAD_DIR / orig_name
+            if not image_path.exists() or not image_path.is_file():
+                image_path = OUTPUT_DIR / orig_name
+
+        if not image_path.exists() or not image_path.is_file():
+            raise HTTPException(
+                status_code=404,
+                detail=f"Image not found: {safe_name} (also tried original: {payload.original_filename or 'n/a'})",
+            )
+
+        masks_dir = UPLOAD_DIR / "masks"
+        masks_dir.mkdir(exist_ok=True)
+        label_owner = Path(image_path).stem
+        label_path = masks_dir / f"{label_owner}_labels.png"
+        if not label_path.exists() and payload.original_filename:
+            alt_owner = Path(payload.original_filename).name
+            alt_label = masks_dir / f"{alt_owner}_labels.png"
+            if alt_label.exists():
+                label_path = alt_label
+
+        if not label_path.exists():
+            raise HTTPException(
+                status_code=404,
+                detail=f"Label map not found for {label_owner}. Upload/segment the image first.",
+            )
+
+        if not payload.mask_indices:
+            raise HTTPException(status_code=400, detail="No mask indices provided")
+
+        texture_path = resolve_texture_path(payload.texture_name)
+        orig_pil = Image.open(str(image_path)).convert("RGB")
+        width, height = orig_pil.size
+
+        label_map = cv2.imread(str(label_path), cv2.IMREAD_GRAYSCALE)
+        if label_map is None:
+            raise HTTPException(status_code=500, detail="Could not read label map")
+
+        binary_mask = np.zeros((label_map.shape[0], label_map.shape[1]), dtype=np.uint8)
+        for idx in payload.mask_indices:
+            binary_mask |= (label_map == idx).astype(np.uint8)
+
+        if binary_mask.max() == 0:
+            raise HTTPException(status_code=400, detail="None of the selected segments were found in the label map.")
+
+        direction_mode = str(payload.direction_mode or "auto").strip().lower()
+        if direction_mode not in {"auto", "manual", "none"}:
+            raise HTTPException(status_code=400, detail="Invalid direction_mode. Use auto, manual, or none.")
+
+        replace_mode = str(getattr(payload, "replace_mode", "realistic") or "realistic").strip().lower()
+        lighting_mode = str(getattr(payload, "lighting_mode", "scene") or "scene").strip().lower()
+
+        material = classify_texture_material(payload.texture_name)
+        surface_type, inferred_angle, blend_alpha, target_w = infer_surface_type_and_direction(
+            binary_mask, width, height, payload.texture_name,
+        )
+        replace_strength, light_angle_degrees, light_intensity = choose_auto_texture_settings(material, surface_type)
+        effective_alpha = float(np.clip(blend_alpha * (0.55 + (0.75 * replace_strength)), 0.0, 0.98))
+        if material == "acm":
+            effective_alpha = float(max(effective_alpha, 0.92))
+
+        applied_angle = 0.0
+        if direction_mode == "auto":
+            applied_angle = inferred_angle
+        elif direction_mode == "manual":
+            applied_angle = float(payload.angle_degrees)
+
+        tex_pil = load_texture_pil_rgb(texture_path)
+
+        # Escalar al tamaño de tile deseado ANTES de rotar
+        tex_w, tex_h = tex_pil.size
+        scale = target_w / max(1, tex_w)
+        if abs(scale - 1.0) > 0.05:
+            tex_pil = tex_pil.resize(
+                (max(1, int(tex_w * scale)), max(1, int(tex_h * scale))),
+                Image.Resampling.LANCZOS,
+            )
+            tex_w, tex_h = tex_pil.size
+
+        tiled: Image.Image | None = None
+
+        # Floor surfaces: perspective tiling solo cuando la perspectiva es fuerte.
+        # Para pisos de dormitorio/habitación (perspectiva suave) el quad aproximado
+        # no cubre bien el mask irregular → produce negro. Se usa tiling regular en esos casos.
+        if surface_type == "floor" and direction_mode in {"auto", "none"}:
+            ys_m, xs_m = np.where(binary_mask > 0)
+            if ys_m.size > 0:
+                min_y_m, max_y_m = int(ys_m.min()), int(ys_m.max())
+                bbox_h_m = max(1, max_y_m - min_y_m + 1)
+                trap_score = _compute_trapezoid_score_from_mask(
+                    binary_mask, ys_m, xs_m, min_y_m, max_y_m, bbox_h_m
+                )
+                if trap_score > 0.35:
+                    quad = _extract_mask_quad(binary_mask)
+                    if quad is not None:
+                        tiled = _tile_texture_perspective(tex_pil, quad, width, height)
+                        if tiled is not None:
+                            logger.info(f"[APPLY_TEXTURE] perspective floor tiling applied (trap={trap_score:.2f})")
+                else:
+                    logger.info(f"[APPLY_TEXTURE] flat floor tiling (trap={trap_score:.2f} < 0.35, skip perspective)")
+
+        # Wall / ceiling surfaces: perspective tiling cuando el quad es significativamente
+        # no-rectangular (pared fotografiada en ángulo). Un ratio > 1.20 entre lado mayor
+        # y lado menor indica distorsión perspectiva visible.
+        if surface_type in {"wall", "ceiling"} and tiled is None and direction_mode in {"auto", "none"}:
+            quad = _extract_mask_quad(binary_mask)
+            if quad is not None:
+                tl, tr, br, bl = quad
+                top_w   = float(np.linalg.norm(tr.astype(float) - tl.astype(float)))
+                bot_w   = float(np.linalg.norm(br.astype(float) - bl.astype(float)))
+                left_h  = float(np.linalg.norm(bl.astype(float) - tl.astype(float)))
+                right_h = float(np.linalg.norm(br.astype(float) - tr.astype(float)))
+                w_ratio = max(top_w, bot_w) / max(1.0, min(top_w, bot_w))
+                h_ratio = max(left_h, right_h) / max(1.0, min(left_h, right_h))
+                if w_ratio > 1.20 or h_ratio > 1.20:
+                    tiled = _tile_texture_perspective(tex_pil, quad, width, height)
+                    if tiled is not None:
+                        logger.info(
+                            f"[APPLY_TEXTURE] perspective wall tiling applied "
+                            f"(w_ratio={w_ratio:.2f}, h_ratio={h_ratio:.2f})"
+                        )
+
+        if tiled is None:
+            if abs(applied_angle) > 0.01:
+                # Tile on a large canvas first, then rotate the full canvas to avoid black corners
+                diag = int(np.ceil(np.sqrt(width ** 2 + height ** 2))) + max(tex_w, tex_h)
+                large_w = width + diag
+                large_h = height + diag
+                large = Image.new("RGB", (large_w, large_h))
+                for y in range(0, large_h, tex_h):
+                    for x in range(0, large_w, tex_w):
+                        large.paste(tex_pil, (x, y))
+                large = large.rotate(-applied_angle, resample=Image.Resampling.BICUBIC, expand=False)
+                cx = (large_w - width) // 2
+                cy = (large_h - height) // 2
+                tiled = large.crop((cx, cy, cx + width, cy + height))
+            else:
+                tiled = Image.new("RGB", (width, height))
+                for y in range(0, height, tex_h):
+                    for x in range(0, width, tex_w):
+                        tiled.paste(tex_pil, (x, y))
+
+        orig_u8 = np.array(orig_pil, dtype=np.uint8)
+
+        try:
+            if bool(getattr(payload, "clear_mask_before_apply", False)):
+                orig_candidate = None
+                if payload.original_filename:
+                    cand = UPLOAD_DIR / Path(payload.original_filename).name
+                    if cand.exists() and cand.is_file():
+                        orig_candidate = cand
+                    else:
+                        cand2 = OUTPUT_DIR / Path(payload.original_filename).name
+                        if cand2.exists() and cand2.is_file():
+                            orig_candidate = cand2
+                if orig_candidate is None:
+                    stem = Path(image_path).stem
+                    if "_edit_" in stem:
+                        base_name = stem.split("_edit_")[0] + ".jpg"
+                        cand = UPLOAD_DIR / base_name
+                        if cand.exists() and cand.is_file():
+                            orig_candidate = cand
+                        else:
+                            cand2 = OUTPUT_DIR / base_name
+                            if cand2.exists() and cand2.is_file():
+                                orig_candidate = cand2
+
+                if orig_candidate is not None:
+                    try:
+                        base_pil = Image.open(str(orig_candidate)).convert("RGB")
+                        if base_pil.size != (width, height):
+                            base_pil = base_pil.resize((width, height), Image.Resampling.LANCZOS)
+                        base_arr = np.array(base_pil, dtype=np.uint8)
+                        mask_bool = (binary_mask > 0)
+                        orig_u8[mask_bool] = base_arr[mask_bool]
+                        logger.info(f"[APPLY_TEXTURE] cleared mask from original source: {orig_candidate}")
+                    except Exception:
+                        logger.exception("Failed to restore original pixels for clear_mask_before_apply")
+        except Exception:
+            logger.exception("Error handling clear_mask_before_apply")
+
+        tiled_arr = np.array(tiled, dtype=np.uint8)
+
+        # Parchar píxeles muy oscuros (suma R+G+B < 20) dentro de la máscara.
+        # Cubren tanto negro exacto (0,0,0) como píxeles casi negros que el warp
+        # de perspectiva puede generar en bordes del quad o zonas sin cobertura.
+        mask_bool = binary_mask > 0
+        dark_in_mask = mask_bool & (tiled_arr.sum(axis=2) < 20)
+        if dark_in_mask.any():
+            th_f, tw_f = tex_pil.size[1], tex_pil.size[0]
+            tex_np = np.array(tex_pil, dtype=np.uint8)
+            ys_b, xs_b = np.where(dark_in_mask)
+            tiled_arr[ys_b, xs_b] = tex_np[ys_b % th_f, xs_b % tw_f]
+
+        lit_tex = apply_surface_lighting(
+            tiled_arr,
+            orig_u8,
+            binary_mask,
+            material,
+            lighting_mode,
+            light_angle_degrees,
+            light_intensity,
+        )
+
+        orig_arr = orig_u8.astype(np.float32)
+        tex_arr = lit_tex.astype(np.float32)
+
+        if replace_mode in {"hard", "absolute", "force", "replace"}:
+            mask_bool = (binary_mask > 0).astype(bool)
+            composite_arr = orig_arr.copy()
+            composite_arr[mask_bool] = tex_arr[mask_bool]
+            composite = np.clip(composite_arr, 0, 255).astype(np.uint8)
+        else:
+            feather_mask = build_feather_mask(binary_mask)
+            # All materials use shading-preservation so scene luminance (shadows/highlights)
+            # from the original photo is transferred onto the texture.
+            composite = blend_texture_preserve_shading(orig_arr, tex_arr, feather_mask, effective_alpha, material)
+
+        input_stem = Path(image_path).stem
+        edit_suffix = uuid.uuid4().hex[:8]
+        out_filename = f"{input_stem}_edit_{edit_suffix}.jpg"
+        out_path = UPLOAD_DIR / out_filename
+        Image.fromarray(composite).save(str(out_path), format="JPEG", quality=UPLOAD_JPEG_QUALITY, optimize=True)
+
+        try:
+            out_label_path = masks_dir / f"{Path(out_filename).stem}_labels.png"
+            if label_path.exists():
+                shutil.copyfile(str(label_path), str(out_label_path))
+        except Exception:
+            logger.exception("Failed to copy label map for output image")
+
+        return {
+            "message": "Texture applied successfully",
+            "original": safe_name,
+            "mask_indices": payload.mask_indices,
+            "texture_name": payload.texture_name,
+            "material": material,
+            "direction_mode": direction_mode,
+            "surface_type": surface_type,
+            "replace_mode": replace_mode,
+            "replace_strength": round(replace_strength, 3),
+            "lighting_mode": lighting_mode,
+            "light_angle_degrees": round(light_angle_degrees, 2),
+            "light_intensity": round(light_intensity, 3),
+            "blend_alpha": round(effective_alpha, 3),
+            "applied_angle_degrees": round(applied_angle, 2),
+            "output_filename": out_filename,
+            "output_url": f"/seg/image/{out_filename}",
+        }
+    finally:
+        log_timing_end(step, started)
diff --git a/backend/templates/classic_dashboard.html b/backend/templates/classic_dashboard.html
index 555eeb45fb289affcdf4cd44c127b18a9898c2d2..e965634bce645622dba2ea93e60fdeca8c1c31bb 100644
--- a/backend/templates/classic_dashboard.html
+++ b/backend/templates/classic_dashboard.html
@@ -1,2347 +1,2347 @@
-<!doctype html>
-<html lang="en">
-  <head>
-    <meta charset="UTF-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>SAM Editor</title>
-    <style>
-      * {
-        box-sizing: border-box;
-        margin: 0;
-        padding: 0;
-      }
-      body {
-        background: #f3f4f6;
-        color: #1f2937;
-        font-family: Arial, sans-serif;
-        display: flex;
-        flex-direction: column;
-        height: 100vh;
-        overflow: hidden;
-      }
-      #toolbar {
-        display: flex;
-        align-items: center;
-        gap: 0.5rem;
-        padding: 0.5rem 1rem;
-        background: #ffffff;
-        border-bottom: 1px solid #d1d5db;
-        flex-shrink: 0;
-      }
-      #brand {
-        font-size: 0.9rem;
-        font-weight: 700;
-        letter-spacing: 0.08em;
-        color: #0f172a;
-        text-transform: uppercase;
-        margin-right: 0.35rem;
-      }
-      #upload-strip {
-        display: flex;
-        align-items: center;
-        gap: 0.75rem;
-        padding: 0.65rem 1rem;
-        background: linear-gradient(90deg, #ffffff 0%, #f8fafc 100%);
-        border-bottom: 1px solid #e5e7eb;
-        flex-shrink: 0;
-        flex-wrap: wrap;
-      }
-      /* Hidden: upload flow now uses the large empty-state drop area */
-      #upload-strip {
-        display: none;
-      }
-      #top-export-actions {
-        display: flex;
-        gap: 0.4rem;
-        align-items: center;
-      }
-      #upload-strip label {
-        font-size: 0.85rem;
-        color: #475569;
-      }
-      #upload-picker {
-        display: flex;
-        align-items: center;
-        gap: 0.55rem;
-        min-width: 340px;
-        flex: 1;
-      }
-      #upload-dropzone {
-        display: flex;
-        align-items: center;
-        gap: 0.55rem;
-        flex-wrap: wrap;
-        border: 1px dashed #94a3b8;
-        border-radius: 8px;
-        background: #ffffff;
-        padding: 0.42rem 0.55rem;
-        cursor: pointer;
-        min-height: 42px;
-        flex: 1;
-        transition:
-          border-color 0.18s,
-          background 0.18s;
-      }
-      #upload-dropzone:hover {
-        border-color: #16a34a;
-        background: #eefaf1;
-      }
-      #upload-dropzone.drop-active {
-        border-color: #f3c21b;
-        background: #fff8dc;
-      }
-      #upload-primary {
-        color: #0f172a;
-        font-size: 0.83rem;
-        font-weight: 600;
-      }
-      #upload-secondary {
-        color: #64748b;
-        font-size: 0.74rem;
-      }
-      #file-pill {
-        margin-left: auto;
-        max-width: 220px;
-        overflow: hidden;
-        text-overflow: ellipsis;
-        white-space: nowrap;
-        background: #eef2f7;
-        border: 1px solid #cbd5e1;
-        border-radius: 999px;
-        color: #334155;
-        font-size: 0.73rem;
-        padding: 0.18rem 0.5rem;
-      }
-      #file-input {
-        display: none;
-      }
-      #upload-btn {
-        padding: 0.35rem 0.9rem;
-        background: #2a6;
-        color: #fff;
-        border: none;
-        border-radius: 4px;
-        cursor: pointer;
-        font-size: 0.85rem;
-        min-height: 42px;
-      }
-      #upload-btn:disabled {
-        background: #94a3b8;
-        cursor: default;
-      }
-      #status {
-        font-size: 0.8rem;
-        color: #475569;
-        margin-left: auto;
-      }
-      #workspace {
-        flex: 1;
-        min-height: 0;
-        display: flex;
-        overflow: hidden;
-      }
-      #canvas-container {
-        flex: 1;
-        display: flex;
-        align-items: center;
-        justify-content: center;
-        overflow: hidden;
-        background: #ececec;
-        padding: 1.2rem;
-      }
-      #main-panel {
-        flex: 1;
-        min-width: 0;
-        display: flex;
-        overflow: hidden;
-      }
-      #canvas {
-        max-width: 100%;
-        max-height: 100%;
-        cursor: crosshair;
-        display: none;
-        border-radius: 8px;
-        box-shadow: 0 10px 24px rgba(0, 0, 0, 0.22);
-      }
-      #empty-state {
-        width: min(1120px, 100%);
-        min-height: min(620px, 100%);
-        border-radius: 12px;
-        background: #f4f4f4;
-        border: 1px solid #d6d6d6;
-        display: flex;
-        gap: 1.1rem;
-        padding: 1.15rem;
-      }
-      #empty-state-left {
-        width: 320px;
-        min-width: 280px;
-        display: flex;
-        flex-direction: column;
-        gap: 0.9rem;
-        color: #1e293b;
-      }
-      #empty-state-title {
-        font-size: 2rem;
-        line-height: 1.05;
-        font-weight: 700;
-        color: #1f2937;
-      }
-      .empty-step {
-        display: flex;
-        align-items: center;
-        gap: 0.55rem;
-        font-size: 1.02rem;
-        color: #1f2937;
-        font-weight: 600;
-      }
-      .empty-step::before {
-        content: "";
-        width: 12px;
-        height: 12px;
-        border-radius: 50%;
-        background: #f3c21b;
-        box-shadow: 0 0 0 3px rgba(243, 194, 27, 0.22);
-      }
-      #empty-upload-btn {
-        margin-top: 0.25rem;
-        min-height: 52px;
-        border: none;
-        border-radius: 10px;
-        background: #f3c21b;
-        color: #111827;
-        font-size: 1.2rem;
-        font-weight: 700;
-        cursor: pointer;
-      }
-      #empty-state-right {
-        flex: 1;
-        min-width: 0;
-        border-radius: 12px;
-        position: relative;
-        overflow: hidden;
-        background: linear-gradient(
-          145deg,
-          #d8d8d8 0%,
-          #cecece 40%,
-          #c2c2c2 100%
-        );
-        cursor: pointer;
-        border: 2px dashed transparent;
-        transition:
-          border-color 0.18s,
-          box-shadow 0.18s,
-          background 0.18s;
-      }
-      #empty-state-right:hover {
-        border-color: #f3c21b;
-        box-shadow: inset 0 0 0 1px rgba(255, 255, 255, 0.4);
-      }
-      #empty-state-right.drop-active {
-        border-color: #16a34a;
-        background: linear-gradient(
-          145deg,
-          #dce8dc 0%,
-          #d6e4d6 40%,
-          #cad8ca 100%
-        );
-      }
-      #empty-preview-image {
-        position: absolute;
-        inset: 0;
-        width: 100%;
-        height: 100%;
-        object-fit: cover;
-        display: none;
-      }
-      #empty-drop-hint {
-        position: absolute;
-        inset: 0;
-        display: flex;
-        align-items: center;
-        justify-content: center;
-        text-align: center;
-        padding: 1rem;
-        color: #334155;
-        font-weight: 700;
-        font-size: 1.05rem;
-        letter-spacing: 0.01em;
-        background: linear-gradient(
-          180deg,
-          rgba(255, 255, 255, 0.12),
-          rgba(255, 255, 255, 0.02)
-        );
-      }
-      #empty-room {
-        position: absolute;
-        inset: 0;
-      }
-      #actions {
-        display: none;
-        width: 300px;
-        min-width: 260px;
-        max-width: 360px;
-        flex-direction: column;
-        align-items: stretch;
-        gap: 0.6rem;
-        padding: 0.65rem;
-        background: #f8fafc;
-        border-right: 1px solid #dbe2ea;
-        flex-shrink: 0;
-        overflow: hidden;
-      }
-      #actions.visible {
-        display: flex;
-      }
-      #actions label {
-        font-size: 0.8rem;
-        color: #475569;
-        white-space: nowrap;
-      }
-      .action-btn {
-        padding: 0.35rem 0.9rem;
-        border: none;
-        border-radius: 4px;
-        cursor: pointer;
-        font-size: 0.85rem;
-        color: #fff;
-        white-space: nowrap;
-      }
-      #tex-apply-btn {
-        background: #a62;
-      }
-      .action-btn:disabled {
-        background: #444 !important;
-        cursor: default;
-      }
-      #tex-panel {
-        display: flex;
-        align-items: stretch;
-        flex-direction: column;
-        gap: 0.5rem;
-        flex: 1;
-        min-width: 0;
-        min-height: 0;
-      }
-      #tex-history-actions {
-        display: flex;
-        gap: 0.4rem;
-      }
-      #replace-controls {
-        display: flex;
-        flex-direction: column;
-        gap: 0.32rem;
-        padding: 0.35rem 0.4rem;
-        border: 1px solid #d8e0ea;
-        border-radius: 6px;
-        background: #ffffff;
-      }
-      #replace-controls label {
-        font-size: 0.76rem;
-        color: #64748b;
-      }
-      #replace-mode {
-        background: #202020;
-        border: 1px solid #3d3d3d;
-        color: #ddd;
-        border-radius: 4px;
-        padding: 0.28rem 0.35rem;
-        font-size: 0.8rem;
-      }
-      #replace-strength-wrap {
-        display: flex;
-        align-items: center;
-        gap: 0.45rem;
-      }
-      #replace-strength {
-        width: 100%;
-      }
-      #replace-strength-value {
-        min-width: 2.9rem;
-        text-align: right;
-        font-size: 0.76rem;
-        color: #b7b7b7;
-      }
-      #lighting-controls {
-        display: flex;
-        flex-direction: column;
-        gap: 0.32rem;
-        padding: 0.35rem 0.4rem;
-        border: 1px solid #2f2f2f;
-        border-radius: 6px;
-        background: #141414;
-      }
-      #lighting-controls label {
-        font-size: 0.76rem;
-        color: #9f9f9f;
-      }
-      #lighting-mode {
-        background: #202020;
-        border: 1px solid #3d3d3d;
-        color: #ddd;
-        border-radius: 4px;
-        padding: 0.28rem 0.35rem;
-        font-size: 0.8rem;
-      }
-      #light-angle-wrap,
-      #light-intensity-wrap {
-        display: flex;
-        align-items: center;
-        gap: 0.45rem;
-      }
-      #light-angle,
-      #light-intensity {
-        width: 100%;
-      }
-      #light-angle-value,
-      #light-intensity-value {
-        min-width: 3.4rem;
-        text-align: right;
-        font-size: 0.76rem;
-        color: #b7b7b7;
-      }
-      #exterior-controls {
-        display: none;
-      }
-      #exterior-controls label {
-        font-size: 0.76rem;
-        color: #9f9f9f;
-      }
-      #ext-target,
-      #ext-priority,
-      #ext-top-k,
-      #ext-min-area,
-      #ext-max-area,
-      #ext-keywords {
-        width: 100%;
-        background: #202020;
-        border: 1px solid #3d3d3d;
-        color: #ddd;
-        border-radius: 4px;
-        padding: 0.28rem 0.35rem;
-        font-size: 0.8rem;
-      }
-      #ext-actions {
-        display: flex;
-        gap: 0.4rem;
-      }
-      #ext-analyze-btn {
-        background: #4f5b9d;
-      }
-      #ext-segment-btn {
-        background: #3f7f54;
-      }
-      #tex-reset-btn {
-        background: #555;
-      }
-      #tex-undo-btn {
-        background: #335d85;
-      }
-      #download-btn {
-        background: #2d7c4f;
-      }
-      #share-btn {
-        background: #5f4fb2;
-      }
-      #tex-gallery {
-        display: flex;
-        flex-direction: column;
-        align-items: stretch;
-        gap: 0.6rem;
-        overflow-x: hidden;
-        overflow-y: auto;
-        flex: 1;
-        padding: 0.25rem 0;
-        scrollbar-width: thin;
-      }
-      .tex-section {
-        display: flex;
-        flex-direction: column;
-        gap: 0.35rem;
-      }
-      .tex-section-title {
-        color: #64748b;
-        font-size: 0.76rem;
-        text-transform: uppercase;
-        letter-spacing: 0.06em;
-      }
-      .tex-row {
-        display: flex;
-        gap: 0.4rem;
-        flex-wrap: wrap;
-        padding-bottom: 0;
-      }
-      .tex-empty {
-        color: #64748b;
-        font-size: 0.72rem;
-        font-style: italic;
-        padding: 0.1rem 0.2rem;
-      }
-      .tex-card {
-        width: 104px;
-        flex-shrink: 0;
-        cursor: pointer;
-        border-radius: 8px;
-        border: 1px solid #dbe2ea;
-        background: #ffffff;
-        padding: 0.22rem;
-        display: flex;
-        flex-direction: column;
-        gap: 0.28rem;
-        transition:
-          border-color 0.15s,
-          box-shadow 0.15s,
-          transform 0.15s;
-      }
-      .tex-thumb {
-        width: 100%;
-        height: 64px;
-        border-radius: 6px;
-        border: 2px solid transparent;
-        object-fit: cover;
-        opacity: 0.88;
-        transition:
-          opacity 0.15s,
-          border-color 0.15s;
-      }
-      .tex-card-copy {
-        display: flex;
-        flex-direction: column;
-        gap: 0.14rem;
-      }
-      .tex-card-name {
-        color: #0f172a;
-        font-size: 0.68rem;
-        font-weight: 700;
-        line-height: 1.15;
-      }
-      .tex-card-size {
-        color: #64748b;
-        font-size: 0.62rem;
-        line-height: 1.15;
-      }
-      .tex-card-path {
-        color: #94a3b8;
-        font-size: 0.58rem;
-        line-height: 1.1;
-        word-break: break-word;
-      }
-      .tex-card:hover {
-        transform: translateY(-1px);
-        border-color: #cbd5e1;
-        box-shadow: 0 6px 16px rgba(15, 23, 42, 0.08);
-      }
-      .tex-card:hover .tex-thumb {
-        opacity: 1;
-      }
-      .tex-card.active {
-        border-color: #f3c21b;
-        box-shadow: 0 0 0 2px rgba(243, 194, 27, 0.16);
-      }
-      .tex-card.active .tex-thumb {
-        border-color: #f90;
-        opacity: 1;
-      }
-      #loading-overlay {
-        position: fixed;
-        inset: 0;
-        background: rgba(15, 23, 42, 0.58);
-        backdrop-filter: blur(2px);
-        display: none;
-        align-items: center;
-        justify-content: center;
-        z-index: 9999;
-      }
-      #loading-overlay.visible {
-        display: flex;
-      }
-      #loading-card {
-        min-width: 260px;
-        max-width: min(92vw, 440px);
-        border-radius: 12px;
-        background: #ffffff;
-        border: 1px solid #dbe2ea;
-        box-shadow: 0 20px 48px rgba(2, 8, 23, 0.28);
-        padding: 1.15rem 1.2rem;
-        display: flex;
-        flex-direction: column;
-        gap: 0.55rem;
-      }
-      #loading-row {
-        display: flex;
-        align-items: center;
-        gap: 0.65rem;
-      }
-      #loading-spinner {
-        width: 22px;
-        height: 22px;
-        border-radius: 50%;
-        border: 3px solid #d1d5db;
-        border-top-color: #16a34a;
-        animation: spin 0.85s linear infinite;
-        flex-shrink: 0;
-      }
-      #loading-title {
-        font-size: 0.95rem;
-        font-weight: 700;
-        color: #0f172a;
-      }
-      #loading-text {
-        font-size: 0.82rem;
-        color: #475569;
-        line-height: 1.35;
-      }
-      @keyframes spin {
-        to {
-          transform: rotate(360deg);
-        }
-      }
-      @media (max-width: 900px) {
-        #workspace {
-          flex-direction: column;
-        }
-        #actions {
-          width: 100%;
-          max-width: none;
-          min-width: 0;
-          border-right: none;
-          border-bottom: 1px solid #333;
-          max-height: 45vh;
-        }
-        #empty-state {
-          flex-direction: column;
-          min-height: 70vh;
-        }
-        #empty-state-left {
-          width: 100%;
-          min-width: 0;
-        }
-      }
-    </style>
-  </head>
-  <body>
-    <div id="toolbar">
-      <span id="brand">HyperReality</span>
-      <span id="status">No image loaded</span>
-    </div>
-    <div id="upload-strip">
-      <div id="top-export-actions">
-        <button id="download-btn" class="action-btn">Download</button>
-        <button id="share-btn" class="action-btn">Share</button>
-      </div>
-      <div id="upload-picker">
-        <label id="upload-dropzone" for="file-input">
-          <span id="upload-primary">Selecciona o arrastra tu imagen</span>
-          <span id="upload-secondary">JPG, PNG o WEBP</span>
-          <span id="file-pill">Ningún archivo</span>
-        </label>
-        <input id="file-input" type="file" accept="image/*" />
-        <button id="upload-btn" disabled>Procesar</button>
-      </div>
-    </div>
-    <div id="workspace">
-      <div id="actions">
-        <div id="tex-panel">
-          <label>Textura por categoria</label>
-          <div id="exterior-controls">
-            <label for="ext-target">Exterior target</label>
-            <select id="ext-target">
-              <option value="wall" selected>Wall / Facade</option>
-              <option value="roof">Roof</option>
-              <option value="window">Window</option>
-            </select>
-            <label for="ext-priority">Priority</label>
-            <select id="ext-priority">
-              <option value="speed">Speed</option>
-              <option value="balanced" selected>Balanced</option>
-              <option value="quality">Quality</option>
-            </select>
-            <label for="ext-top-k">Top-K masks</label>
-            <input
-              id="ext-top-k"
-              type="number"
-              min="1"
-              max="20"
-              step="1"
-              value="8"
-            />
-            <label for="ext-min-area">Min area ratio</label>
-            <input
-              id="ext-min-area"
-              type="number"
-              min="0"
-              max="1"
-              step="0.001"
-              value="0.01"
-            />
-            <label for="ext-max-area">Max area ratio</label>
-            <input
-              id="ext-max-area"
-              type="number"
-              min="0"
-              max="1"
-              step="0.001"
-              value="0.85"
-            />
-            <label for="ext-keywords"
-              >Semantic keywords (comma-separated)</label
-            >
-            <input
-              id="ext-keywords"
-              type="text"
-              value="building,wall,facade,house,roof,window,door"
-            />
-            <div id="ext-actions">
-              <button id="ext-analyze-btn" class="action-btn">
-                Analyze Exterior
-              </button>
-              <button id="ext-segment-btn" class="action-btn">
-                Segment Exterior
-              </button>
-            </div>
-          </div>
-          <div id="tex-gallery"></div>
-
-          <div id="mask-debug" style="margin-top: 0.6rem">
-            <label style="color: #475569; font-size: 0.82rem"
-              >Debug máscaras</label
-            >
-            <div
-              id="mask-debug-controls"
-              style="display: flex; gap: 0.4rem; margin-top: 0.25rem"
-            >
-              <button
-                id="mask-debug-refresh"
-                class="action-btn"
-                style="background: #444"
-              >
-                Refrescar Máscaras
-              </button>
-              <button
-                id="mask-debug-load-local"
-                class="action-btn"
-                style="background: #2a6"
-              >
-                Cargar Guardadas
-              </button>
-              <button
-                id="mask-debug-clear-local"
-                class="action-btn"
-                style="background: #a33"
-              >
-                Borrar Guardadas
-              </button>
-            </div>
-            <div
-              id="mask-debug-list"
-              style="
-                display: flex;
-                flex-direction: column;
-                gap: 0.4rem;
-                margin-top: 0.4rem;
-                max-height: 220px;
-                overflow: auto;
-              "
-            ></div>
-            <div
-              id="mask-debug-local-list"
-              style="
-                display: flex;
-                flex-direction: column;
-                gap: 0.4rem;
-                margin-top: 0.6rem;
-                max-height: 220px;
-                overflow: auto;
-                border-top: 1px solid #dbe2ea;
-                padding-top: 0.4rem;
-              "
-            ></div>
-          </div>
-          <div id="replace-controls" style="margin-top: 0.35rem">
-            <label
-              style="
-                font-size: 0.85rem;
-                color: #334155;
-                display: flex;
-                align-items: center;
-                gap: 0.4rem;
-              "
-            >
-              <input
-                id="clear-mask-checkbox"
-                type="checkbox"
-                checked
-                style="transform: scale(0.95)"
-              />
-              Limpiar máscara antes de aplicar
-            </label>
-          </div>
-          <div
-            id="applied-textures"
-            style="
-              margin-top: 0.45rem;
-              border: 1px solid #d8e0ea;
-              border-radius: 6px;
-              background: #ffffff;
-              padding: 0.35rem 0.4rem;
-            "
-          >
-            <label style="font-size: 0.78rem; color: #64748b"
-              >Texturas aplicadas</label
-            >
-            <div
-              id="applied-texture-list"
-              style="
-                margin-top: 0.3rem;
-                max-height: 160px;
-                overflow: auto;
-                display: flex;
-                flex-direction: column;
-                gap: 0.28rem;
-              "
-            ></div>
-          </div>
-          <div id="tex-history-actions">
-            <button id="tex-reset-btn" class="action-btn">Reset All</button>
-            <button id="tex-undo-btn" class="action-btn">Undo Last</button>
-            <button id="tex-apply-btn" class="action-btn">
-              Aplicar Textura
-            </button>
-          </div>
-        </div>
-      </div>
-      <div id="main-panel">
-        <div id="canvas-container">
-          <div id="empty-state">
-            <div id="empty-state-left">
-              <div id="empty-state-title">Ver los productos en su cuarto</div>
-              <div class="empty-step">Sube una foto de tu habitación</div>
-              <div class="empty-step">Prueba nuestras texturas</div>
-              <button id="empty-upload-btn" type="button">Sube tu foto</button>
-            </div>
-            <div id="empty-state-right">
-              <img id="empty-preview-image" alt="Vista previa de imagen" />
-              <div id="empty-drop-hint">
-                Arrastra tu imagen aqui<br />o haz clic para seleccionar
-              </div>
-              <div id="empty-room"></div>
-            </div>
-          </div>
-          <canvas id="canvas"></canvas>
-        </div>
-      </div>
-    </div>
-    <div id="loading-overlay" aria-live="polite" aria-busy="true">
-      <div id="loading-card">
-        <div id="loading-row">
-          <div id="loading-spinner"></div>
-          <div id="loading-title">Procesando imagen...</div>
-        </div>
-        <div id="loading-text">Estamos subiendo y segmentando tu foto.</div>
-      </div>
-    </div>
-    <script>
-      const FRONTEND_DEBUG_MODE = __FRONTEND_DEBUG_ENABLED__;
-
-      const fileInput = document.getElementById("file-input");
-      const uploadBtn = document.getElementById("upload-btn");
-      const statusEl = document.getElementById("status");
-      const canvas = document.getElementById("canvas");
-      const ctx = canvas.getContext("2d");
-      const emptyStateEl = document.getElementById("empty-state");
-      const emptyUploadBtn = document.getElementById("empty-upload-btn");
-      const emptyStateRightEl = document.getElementById("empty-state-right");
-      const emptyDropHintEl = document.getElementById("empty-drop-hint");
-      const emptyPreviewImageEl = document.getElementById(
-        "empty-preview-image",
-      );
-      const emptyRoomEl = document.getElementById("empty-room");
-      const uploadStripEl = document.getElementById("upload-strip");
-      const uploadDropzone = document.getElementById("upload-dropzone");
-      const filePill = document.getElementById("file-pill");
-      const maskDebugEl = document.getElementById("mask-debug");
-      const loadingOverlayEl = document.getElementById("loading-overlay");
-      const loadingTitleEl = document.getElementById("loading-title");
-      const loadingTextEl = document.getElementById("loading-text");
-
-      const actionsBar = document.getElementById("actions");
-      const texGallery = document.getElementById("tex-gallery");
-      const texResetBtn = document.getElementById("tex-reset-btn");
-      const texUndoBtn = document.getElementById("tex-undo-btn");
-      const downloadBtn = document.getElementById("download-btn");
-      const shareBtn = document.getElementById("share-btn");
-      const texApplyBtn = document.getElementById("tex-apply-btn");
-      const extTargetEl = document.getElementById("ext-target");
-      const extPriorityEl = document.getElementById("ext-priority");
-      const extTopKEl = document.getElementById("ext-top-k");
-      const extMinAreaEl = document.getElementById("ext-min-area");
-      const extMaxAreaEl = document.getElementById("ext-max-area");
-      const extKeywordsEl = document.getElementById("ext-keywords");
-      const extAnalyzeBtn = document.getElementById("ext-analyze-btn");
-      const extSegmentBtn = document.getElementById("ext-segment-btn");
-      const appliedTextureListEl = document.getElementById(
-        "applied-texture-list",
-      );
-
-      let originalImageData = null;
-      let labelData = null;
-      let hoveredMask = 0;
-      const selectedMasks = new Set();
-      let currentFilename = null;
-      let originalFilename = null;
-      let selectedTextureName = null;
-      let allTextureNames = [];
-      let textureHistory = [];
-      let appliedTextureHistory = [];
-      let selectedUploadFile = null;
-      let previewObjectUrl = null;
-      let isUploading = false;
-      let autoUploadTimer = null;
-
-      const ACM_TEXTURE_CATALOG = [
-        {
-          nombre: "Glossy White",
-          textura: "Texture_ACM/ACM_White.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Amarillo",
-          textura: "Texture_ACM/ACM_Amarillo.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Glossy Orange",
-          textura: "Texture_ACM/ACM_Orange.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Glossy Red",
-          textura: "Texture_ACM/ACM_Glossy_Red.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Light Blue",
-          textura: "Texture_ACM/ACM_Light_Blue.png",
-          dimensiones: ["1.22x2.44"],
-        },
-        {
-          nombre: "Azul",
-          textura: "Texture_ACM/ACM_Azul.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Verde HN",
-          textura: "Texture_ACM/ACM_Verde_HN.png",
-          dimensiones: ["1.22x2.44"],
-        },
-        {
-          nombre: "Verde Lima",
-          textura: "Texture_ACM/ACM_Verde_Lima.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Verde",
-          textura: "Texture_ACM/ACM_Verde.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Madera Clara",
-          textura: "Texture_ACM/ACM_Madera_Clara.png",
-          dimensiones: ["1.22x2.44"],
-        },
-        {
-          nombre: "Roble (Oak)",
-          textura: "Texture_ACM/ACM_ROBLE(OAK).png",
-          dimensiones: ["1.22x2.44"],
-        },
-        {
-          nombre: "Grafito",
-          textura: "Texture_ACM/ACM_Grafito.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Silver Metallic",
-          textura: "Texture_ACM/ACM_Metalic.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Mouse Grey",
-          textura: "Texture_ACM/ACM_MouseGrey.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Matte Black",
-          textura: "Texture_ACM/ACM_Matteblack.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-        {
-          nombre: "Glossy Black",
-          textura: "Texture_ACM/ACM_Glossy_Black.png",
-          dimensiones: ["1.22x2.44", "1.50x4.98"],
-        },
-      ];
-
-      const ACM_TEXTURE_META = ACM_TEXTURE_CATALOG.reduce(
-        (acc, item, index) => {
-          acc[item.textura.toLowerCase()] = {
-            ...item,
-            orden: index,
-          };
-          return acc;
-        },
-        {},
-      );
-
-      function segLog(level, message, payload) {
-        const tag = "[SEGMENTACION_UI]";
-        const ts = new Date().toISOString();
-        const method = typeof console[level] === "function" ? level : "log";
-        if (typeof payload === "undefined") {
-          console[method](`${tag} ${ts} ${message}`);
-          return;
-        }
-        console[method](`${tag} ${ts} ${message}`, payload);
-      }
-
-      function setLoadingOverlay(visible, title, text) {
-        if (!loadingOverlayEl) return;
-        if (title && loadingTitleEl) {
-          loadingTitleEl.textContent = title;
-        }
-        if (text && loadingTextEl) {
-          loadingTextEl.textContent = text;
-        }
-        if (visible) {
-          loadingOverlayEl.classList.add("visible");
-        } else {
-          loadingOverlayEl.classList.remove("visible");
-        }
-      }
-
-      function applyFrontendDebugMode() {
-        if (!maskDebugEl) return;
-        maskDebugEl.style.display = FRONTEND_DEBUG_MODE ? "block" : "none";
-      }
-
-      function hideLegacyUploadStrip() {
-        if (!uploadStripEl) return;
-        uploadStripEl.style.setProperty("display", "none", "important");
-        uploadStripEl.setAttribute("hidden", "hidden");
-      }
-
-      function setEditorHasImage(hasImage) {
-        if (hasImage) {
-          emptyStateEl.style.display = "none";
-          canvas.style.display = "block";
-        } else {
-          emptyStateEl.style.display = "flex";
-          canvas.style.display = "none";
-        }
-      }
-
-      function updateUploadSelection(file) {
-        selectedUploadFile = file || null;
-        if (!file) {
-          filePill.textContent = "Ningún archivo";
-          uploadBtn.disabled = true;
-          if (previewObjectUrl) {
-            try {
-              URL.revokeObjectURL(previewObjectUrl);
-            } catch (err) {}
-            previewObjectUrl = null;
-          }
-          emptyPreviewImageEl.style.display = "none";
-          emptyPreviewImageEl.removeAttribute("src");
-          emptyRoomEl.style.display = "block";
-          if (emptyDropHintEl) emptyDropHintEl.style.display = "flex";
-          return;
-        }
-        filePill.textContent = file.name;
-        uploadBtn.disabled = false;
-        statusEl.textContent = `Archivo listo: ${file.name}`;
-        if (previewObjectUrl) {
-          try {
-            URL.revokeObjectURL(previewObjectUrl);
-          } catch (err) {}
-        }
-        previewObjectUrl = URL.createObjectURL(file);
-        emptyPreviewImageEl.src = previewObjectUrl;
-        emptyPreviewImageEl.style.display = "block";
-        emptyRoomEl.style.display = "none";
-        if (emptyDropHintEl) emptyDropHintEl.style.display = "none";
-      }
-
-      function renderAppliedTextureHistory() {
-        if (!appliedTextureListEl) return;
-        appliedTextureListEl.innerHTML = "";
-
-        if (!appliedTextureHistory.length) {
-          const empty = document.createElement("div");
-          empty.style = "font-size:0.74rem;color:#64748b;";
-          empty.textContent = "Aún no se aplicaron texturas.";
-          appliedTextureListEl.appendChild(empty);
-          return;
-        }
-
-        appliedTextureHistory.forEach((item, idx) => {
-          const row = document.createElement("div");
-          row.style =
-            "font-size:0.74rem; color:#0f172a; border:1px solid #dbe2ea; border-radius:4px; padding:0.22rem 0.3rem; background:#f8fafc;";
-          const masksText = Array.isArray(item.mask_indices)
-            ? item.mask_indices.join(", ")
-            : "";
-          row.textContent = `#${idx + 1} ${item.texture_name} | masks: [${masksText}]`;
-          appliedTextureListEl.appendChild(row);
-        });
-      }
-
-      function syncTextureHistoryButtons() {
-        const canEdit = textureHistory.length > 0;
-        const canUndo = textureHistory.length > 1;
-        const canExport = textureHistory.length > 1;
-        texResetBtn.disabled = !canEdit;
-        texUndoBtn.disabled = !canUndo;
-        downloadBtn.disabled = !canExport;
-        shareBtn.disabled = !canExport;
-      }
-
-      async function getCurrentImageBlob() {
-        if (!currentFilename) {
-          throw new Error("No hay imagen para exportar.");
-        }
-        const res = await fetch(
-          `/image/${encodeURIComponent(currentFilename)}?t=${Date.now()}`,
-        );
-        if (!res.ok) {
-          throw new Error("No se pudo cargar la imagen actual.");
-        }
-        return await res.blob();
-      }
-      syncTextureHistoryButtons();
-      renderAppliedTextureHistory();
-
-      function encodeTexturePath(path) {
-        return path
-          .split("/")
-          .map((part) => encodeURIComponent(part))
-          .join("/");
-      }
-
-      function textureFilename(path) {
-        return (
-          String(path || "")
-            .split("/")
-            .filter(Boolean)
-            .pop() || ""
-        );
-      }
-
-      function humanizeTextureName(name) {
-        return textureFilename(name)
-          .replace(/\.[^.]+$/, "")
-          .replace(/[_-]+/g, " ")
-          .trim();
-      }
-
-      function getTextureMeta(name) {
-        const normalized = String(name || "")
-          .replace(/\\/g, "/")
-          .toLowerCase();
-        const fromCatalog = ACM_TEXTURE_META[normalized];
-        if (fromCatalog) {
-          return fromCatalog;
-        }
-        return {
-          nombre: humanizeTextureName(name),
-          textura: name,
-          dimensiones: [],
-          orden: Number.MAX_SAFE_INTEGER,
-        };
-      }
-
-      function categoryFromTextureName(name) {
-        const n = name.toLowerCase();
-        const acmHints = ["acm"];
-        const deckHints = ["deck", "wood", "plank", "laminate", "floor"];
-
-        if (acmHints.some((h) => n.includes(h))) return "acm";
-        if (deckHints.some((h) => n.includes(h))) return "deck";
-        return null;
-      }
-
-      function deckPriority(name) {
-        const n = String(name || "").toLowerCase();
-        if (n.includes("wood_planks") || n.includes("plank_flooring")) return 0;
-        if (n.includes("wood_floor") || n.includes("laminate_floor")) return 1;
-        if (n.includes("deck_")) return 2;
-        return 3;
-      }
-
-      function acmPriority(name) {
-        return getTextureMeta(name).orden;
-      }
-
-      function categoryTitle(category) {
-        if (category === "acm") return "ACM";
-        if (category === "deck") return "Deck";
-        return category;
-      }
-
-      function textureDisplayName(name) {
-        return getTextureMeta(name).nombre || humanizeTextureName(name);
-      }
-
-      function textureDimensionsLabel(name) {
-        const dimensions = getTextureMeta(name).dimensiones || [];
-        return dimensions.join(" | ");
-      }
-
-      function renderTextureGallery() {
-        texGallery.innerHTML = "";
-        selectedTextureName = null;
-
-        const categoryOrder = ["acm", "deck"];
-        const grouped = { acm: [], deck: [] };
-        allTextureNames.forEach((name) => {
-          const category = categoryFromTextureName(name);
-          if (category) {
-            grouped[category].push(name);
-          }
-        });
-
-        grouped.deck.sort((left, right) => {
-          const diff = deckPriority(left) - deckPriority(right);
-          return diff !== 0 ? diff : left.localeCompare(right);
-        });
-
-        grouped.acm.sort((left, right) => {
-          const diff = acmPriority(left) - acmPriority(right);
-          return diff !== 0 ? diff : left.localeCompare(right);
-        });
-
-        categoryOrder.forEach((category) => {
-          const names = grouped[category];
-
-          const section = document.createElement("div");
-          section.className = "tex-section";
-
-          const title = document.createElement("div");
-          title.className = "tex-section-title";
-          title.textContent = categoryTitle(category);
-          section.appendChild(title);
-
-          const row = document.createElement("div");
-          row.className = "tex-row";
-
-          if (!names.length) {
-            const empty = document.createElement("div");
-            empty.className = "tex-empty";
-            empty.textContent = "Sin texturas en esta categoria";
-            row.appendChild(empty);
-          } else {
-            names.forEach((name) => {
-              const meta = getTextureMeta(name);
-              const card = document.createElement("div");
-              card.className = "tex-card";
-
-              const img = document.createElement("img");
-              img.src = `/texture-preview/${encodeTexturePath(name)}`;
-              img.alt = meta.nombre;
-              img.title = meta.nombre;
-              img.className = "tex-thumb";
-
-              const copy = document.createElement("div");
-              copy.className = "tex-card-copy";
-
-              const nameEl = document.createElement("div");
-              nameEl.className = "tex-card-name";
-              nameEl.textContent = meta.nombre;
-
-              const sizeEl = document.createElement("div");
-              sizeEl.className = "tex-card-size";
-              sizeEl.textContent =
-                textureDimensionsLabel(name) || "Medidas no indicadas";
-
-              const pathEl = document.createElement("div");
-              pathEl.className = "tex-card-path";
-              pathEl.textContent = textureFilename(name);
-
-              card.addEventListener("click", () => {
-                document
-                  .querySelectorAll(".tex-card")
-                  .forEach((c) => c.classList.remove("active"));
-                card.classList.add("active");
-                selectedTextureName = name;
-                statusEl.textContent = `Textura seleccionada: ${meta.nombre}`;
-              });
-
-              card.appendChild(img);
-              copy.appendChild(nameEl);
-              copy.appendChild(sizeEl);
-              copy.appendChild(pathEl);
-              card.appendChild(copy);
-              row.appendChild(card);
-            });
-          }
-
-          section.appendChild(row);
-          texGallery.appendChild(section);
-        });
-      }
-
-      async function buildTextureGallery() {
-        texGallery.innerHTML = "";
-        selectedTextureName = null;
-        try {
-          const res = await fetch("/textures");
-          const data = await res.json();
-          if (!res.ok)
-            throw new Error(data.detail || "No se pudieron cargar texturas");
-
-          allTextureNames = Array.isArray(data.textures) ? data.textures : [];
-          renderTextureGallery();
-        } catch (err) {
-          statusEl.textContent = `Error texturas: ${err.message}`;
-        }
-      }
-
-      async function reloadCanvas(filename, url) {
-        currentFilename = filename;
-        const img = new Image();
-        img.src = url + "?t=" + Date.now();
-        await new Promise((res, rej) => {
-          img.onload = res;
-          img.onerror = rej;
-        });
-        canvas.width = img.naturalWidth;
-        canvas.height = img.naturalHeight;
-        ctx.drawImage(img, 0, 0);
-        originalImageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
-        selectedMasks.clear();
-        hoveredMask = 0;
-        setEditorHasImage(true);
-        redraw();
-      }
-
-      async function loadLabelMapForOwner(ownerFilename) {
-        const labelImg = new Image();
-        labelImg.src = `/masks/${encodeURIComponent(ownerFilename)}?t=${Date.now()}`;
-        await new Promise((resolve) => {
-          labelImg.onload = resolve;
-          labelImg.onerror = resolve;
-        });
-        if (!labelImg.naturalWidth) return false;
-
-        const off = document.createElement("canvas");
-        off.width = canvas.width;
-        off.height = canvas.height;
-        const offCtx = off.getContext("2d");
-        offCtx.drawImage(labelImg, 0, 0, off.width, off.height);
-        labelData = offCtx.getImageData(0, 0, off.width, off.height);
-        try {
-          buildMaskDebugList(ownerFilename);
-          loadSavedMasks(ownerFilename);
-        } catch (e) {
-          /* ignore */
-        }
-        return true;
-      }
-
-      async function runAutoAdaptiveSegmentation(baseFilename) {
-        const targetFilename = String(baseFilename || currentFilename || "");
-        if (!targetFilename) return;
-
-        segLog("log", "Iniciando segmentacion auto-adaptiva", {
-          targetFilename,
-        });
-
-        statusEl.textContent =
-          "Auto-analizando escena y ajustando segmentacion...";
-        const payload = {
-          filename: targetFilename,
-          priority: "balanced",
-          scene_hint: "auto",
-          exterior_target: "wall",
-          semantic_keywords: [
-            "building",
-            "wall",
-            "facade",
-            "house",
-            "roof",
-            "window",
-            "door",
-          ],
-        };
-
-        const res = await fetch("/segment_adaptive", {
-          method: "POST",
-          headers: { "Content-Type": "application/json" },
-          body: JSON.stringify(payload),
-        });
-        const data = await res.json();
-        if (!res.ok) {
-          segLog("error", "Fallo segmentacion auto-adaptiva", data);
-          throw new Error(
-            data.detail || data.message || "Auto adaptive segmentation failed",
-          );
-        }
-
-        segLog("log", "Segmentacion auto-adaptiva completada", {
-          scene_type: data.scene_type,
-          filename: data.filename,
-          recommended_mask_index: data.recommended_mask_index,
-        });
-
-        if (data.filename && data.filename !== currentFilename) {
-          await reloadCanvas(
-            data.filename,
-            `/image/${encodeURIComponent(data.filename)}`,
-          );
-        }
-
-        const owner =
-          data.original_filename_for_apply || data.filename || targetFilename;
-        if (owner) {
-          await loadLabelMapForOwner(owner);
-          originalFilename = owner;
-        }
-
-        selectedMasks.clear();
-        let suggested = null;
-        if (
-          Array.isArray(data.exterior_mask_suggestions) &&
-          data.exterior_mask_suggestions.length
-        ) {
-          suggested = Number(data.exterior_mask_suggestions[0].mask_index || 0);
-        } else if (
-          Array.isArray(data.interior_mask_suggestions) &&
-          data.interior_mask_suggestions.length
-        ) {
-          suggested = Number(data.interior_mask_suggestions[0].mask_index || 0);
-        } else if (Number.isFinite(data.recommended_mask_index)) {
-          suggested = Number(data.recommended_mask_index);
-        }
-
-        if (suggested && suggested > 0) {
-          selectedMasks.add(suggested);
-        }
-
-        redraw();
-        actionsBar.classList.add("visible");
-        await buildTextureGallery();
-        const sceneType = String(data.scene_type || "desconocida");
-        statusEl.textContent = suggested
-          ? `Auto ${sceneType}: mascara ${suggested} preseleccionada.`
-          : `Auto ${sceneType}: segmentacion lista, selecciona una mascara.`;
-      }
-
-      function exteriorKeywordsArray() {
-        return String(extKeywordsEl.value || "")
-          .split(",")
-          .map((s) => s.trim())
-          .filter(Boolean);
-      }
-
-      async function runExteriorWorkflow(mode) {
-        if (!currentFilename) {
-          statusEl.textContent = "Sube y segmenta una imagen primero.";
-          return;
-        }
-
-        const endpoint =
-          mode === "segment" ? "/segment_adaptive" : "/analyze_scene";
-        const payload = {
-          filename: currentFilename,
-          priority: String(extPriorityEl.value || "balanced"),
-          scene_hint: "exterior",
-          top_k: Number(extTopKEl.value || 8),
-          exterior_target: String(extTargetEl.value || "wall"),
-          semantic_keywords: exteriorKeywordsArray(),
-          min_area_ratio: Number(extMinAreaEl.value || 0.01),
-          max_area_ratio: Number(extMaxAreaEl.value || 0.85),
-        };
-
-        extAnalyzeBtn.disabled = true;
-        extSegmentBtn.disabled = true;
-        statusEl.textContent =
-          mode === "segment"
-            ? "Segmentando exterior..."
-            : "Analizando exterior...";
-        try {
-          const res = await fetch(endpoint, {
-            method: "POST",
-            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify(payload),
-          });
-          const data = await res.json();
-          if (!res.ok)
-            throw new Error(
-              data.detail || data.message || "Exterior workflow failed",
-            );
-
-          const owner =
-            data.original_filename_for_apply ||
-            data.filename ||
-            originalFilename ||
-            currentFilename;
-          if (data.filename && data.filename !== currentFilename) {
-            await reloadCanvas(
-              data.filename,
-              `/image/${encodeURIComponent(data.filename)}`,
-            );
-          }
-          if (owner) {
-            await loadLabelMapForOwner(owner);
-            originalFilename = owner;
-          }
-
-          selectedMasks.clear();
-          let suggested = null;
-          if (
-            Array.isArray(data.exterior_mask_suggestions) &&
-            data.exterior_mask_suggestions.length
-          ) {
-            suggested = Number(
-              data.exterior_mask_suggestions[0].mask_index || 0,
-            );
-          } else if (Number.isFinite(data.recommended_mask_index)) {
-            suggested = Number(data.recommended_mask_index);
-          }
-          if (suggested && suggested > 0) {
-            selectedMasks.add(suggested);
-          }
-
-          redraw();
-          actionsBar.classList.add("visible");
-          await buildTextureGallery();
-          if (suggested) {
-            statusEl.textContent = `Exterior listo. Mascara sugerida ${suggested}.`;
-          } else {
-            statusEl.textContent =
-              "Exterior listo. Selecciona una mascara para aplicar textura.";
-          }
-        } catch (err) {
-          statusEl.textContent = `Error: ${err.message}`;
-        } finally {
-          extAnalyzeBtn.disabled = false;
-          extSegmentBtn.disabled = false;
-        }
-      }
-
-      function hslToRgb(h, s, l) {
-        const c = (1 - Math.abs(2 * l - 1)) * s;
-        const x = c * (1 - Math.abs(((h / 60) % 2) - 1));
-        const m = l - c / 2;
-        let r, g, b;
-        if (h < 60) [r, g, b] = [c, x, 0];
-        else if (h < 120) [r, g, b] = [x, c, 0];
-        else if (h < 180) [r, g, b] = [0, c, x];
-        else if (h < 240) [r, g, b] = [0, x, c];
-        else if (h < 300) [r, g, b] = [x, 0, c];
-        else [r, g, b] = [c, 0, x];
-        return [
-          Math.round((r + m) * 255),
-          Math.round((g + m) * 255),
-          Math.round((b + m) * 255),
-        ];
-      }
-
-      function maskColor(idx) {
-        return hslToRgb((idx * 137.508) % 360, 0.85, 0.55);
-      }
-
-      function getCanvasPos(e) {
-        const rect = canvas.getBoundingClientRect();
-        return {
-          x: Math.floor(((e.clientX - rect.left) * canvas.width) / rect.width),
-          y: Math.floor(((e.clientY - rect.top) * canvas.height) / rect.height),
-        };
-      }
-
-      function getLabelAt(x, y) {
-        if (
-          !labelData ||
-          x < 0 ||
-          y < 0 ||
-          x >= canvas.width ||
-          y >= canvas.height
-        )
-          return 0;
-        return labelData.data[(y * canvas.width + x) * 4];
-      }
-
-      function redraw() {
-        if (!originalImageData) return;
-        const imgData = new ImageData(
-          new Uint8ClampedArray(originalImageData.data),
-          originalImageData.width,
-          originalImageData.height,
-        );
-        if (labelData && (hoveredMask || selectedMasks.size)) {
-          const d = imgData.data;
-          const ld = labelData.data;
-          for (let i = 0; i < d.length; i += 4) {
-            const mi = ld[i];
-            if (!mi) continue;
-            const sel = selectedMasks.has(mi);
-            const hov = mi === hoveredMask;
-            if (!sel && !hov) continue;
-            let r, g, b, a;
-            if (sel) {
-              [r, g, b] = maskColor(mi);
-              a = 0.5;
-            } else {
-              [r, g, b] = [255, 255, 255];
-              a = 0.2;
-            }
-            d[i] = d[i] * (1 - a) + r * a;
-            d[i + 1] = d[i + 1] * (1 - a) + g * a;
-            d[i + 2] = d[i + 2] * (1 - a) + b * a;
-          }
-        }
-        ctx.putImageData(imgData, 0, 0);
-      }
-
-      canvas.addEventListener("mousemove", (e) => {
-        const { x, y } = getCanvasPos(e);
-        const mi = getLabelAt(x, y);
-        if (mi !== hoveredMask) {
-          hoveredMask = mi;
-          statusEl.textContent = mi
-            ? `Segment ${mi} - click to select (${selectedMasks.size} selected)`
-            : `${selectedMasks.size} selected`;
-          redraw();
-        }
-      });
-
-      canvas.addEventListener("mouseleave", () => {
-        hoveredMask = 0;
-        redraw();
-      });
-
-      canvas.addEventListener("click", (e) => {
-        const { x, y } = getCanvasPos(e);
-        const mi = getLabelAt(x, y);
-        if (!mi) return;
-        if (selectedMasks.has(mi)) selectedMasks.delete(mi);
-        else selectedMasks.add(mi);
-        statusEl.textContent = `${selectedMasks.size} segment(s) selected`;
-        redraw();
-      });
-
-      texApplyBtn.addEventListener("click", async () => {
-        if (!selectedMasks.size) {
-          statusEl.textContent = "Selecciona un segmento primero.";
-          return;
-        }
-        if (!currentFilename) {
-          statusEl.textContent = "Sube una imagen primero.";
-          return;
-        }
-        if (!selectedTextureName) {
-          statusEl.textContent = "Selecciona una textura local.";
-          return;
-        }
-
-        const appliedMaskIndices = [...selectedMasks];
-
-        texApplyBtn.disabled = true;
-        statusEl.textContent = `Aplicando textura a ${selectedMasks.size} segmento(s)...`;
-        try {
-          const res = await fetch("/apply_texture", {
-            method: "POST",
-            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({
-              filename: currentFilename,
-              mask_indices: appliedMaskIndices,
-              texture_name: selectedTextureName,
-              direction_mode: "auto",
-              angle_degrees: 0,
-              original_filename:
-                originalFilename || textureHistory[0] || currentFilename,
-              clear_mask_before_apply: !!document.getElementById(
-                "clear-mask-checkbox",
-              ).checked,
-            }),
-          });
-          const d = await res.json();
-          if (!res.ok) throw new Error(d.detail || "Apply texture failed");
-          currentFilename = d.output_filename;
-          await reloadCanvas(d.output_filename, d.output_url);
-          textureHistory.push(d.output_filename);
-          appliedTextureHistory.push({
-            texture_name: textureDisplayName(selectedTextureName),
-            mask_indices: appliedMaskIndices,
-            output_filename: d.output_filename,
-          });
-          syncTextureHistoryButtons();
-          renderAppliedTextureHistory();
-          statusEl.textContent = `Textura aplicada (auto): ${d.surface_type || "generic"} | realistic | scene-aware.`;
-        } catch (err) {
-          statusEl.textContent = `Error: ${err.message}`;
-        } finally {
-          texApplyBtn.disabled = false;
-        }
-      });
-
-      extAnalyzeBtn.addEventListener("click", async () => {
-        await runExteriorWorkflow("analyze");
-      });
-
-      extSegmentBtn.addEventListener("click", async () => {
-        await runExteriorWorkflow("segment");
-      });
-
-      texUndoBtn.addEventListener("click", async () => {
-        if (textureHistory.length <= 1) {
-          statusEl.textContent = "No hay una textura previa para deshacer.";
-          return;
-        }
-        texUndoBtn.disabled = true;
-        texResetBtn.disabled = true;
-        try {
-          textureHistory.pop();
-          if (appliedTextureHistory.length) appliedTextureHistory.pop();
-          const previousFilename = textureHistory[textureHistory.length - 1];
-          await reloadCanvas(
-            previousFilename,
-            `/image/${encodeURIComponent(previousFilename)}`,
-          );
-          syncTextureHistoryButtons();
-          renderAppliedTextureHistory();
-          statusEl.textContent = "Ultima textura revertida.";
-        } catch (err) {
-          statusEl.textContent = `Error: ${err.message}`;
-        } finally {
-          syncTextureHistoryButtons();
-        }
-      });
-
-      texResetBtn.addEventListener("click", async () => {
-        if (!textureHistory.length) {
-          statusEl.textContent = "No hay imagen para restaurar.";
-          return;
-        }
-        texUndoBtn.disabled = true;
-        texResetBtn.disabled = true;
-        try {
-          const baseFilename = textureHistory[0];
-          textureHistory = [baseFilename];
-          appliedTextureHistory = [];
-          await reloadCanvas(
-            baseFilename,
-            `/image/${encodeURIComponent(baseFilename)}`,
-          );
-          syncTextureHistoryButtons();
-          renderAppliedTextureHistory();
-          statusEl.textContent = "Texturas reiniciadas al estado original.";
-        } catch (err) {
-          statusEl.textContent = `Error: ${err.message}`;
-        } finally {
-          syncTextureHistoryButtons();
-        }
-      });
-
-      downloadBtn.addEventListener("click", async () => {
-        if (textureHistory.length <= 1) {
-          statusEl.textContent = "Aplica una textura antes de descargar.";
-          return;
-        }
-        downloadBtn.disabled = true;
-        try {
-          const blob = await getCurrentImageBlob();
-          const fileName = currentFilename || `edited_${Date.now()}.jpg`;
-          const blobUrl = URL.createObjectURL(blob);
-          const a = document.createElement("a");
-          a.href = blobUrl;
-          a.download = fileName;
-          document.body.appendChild(a);
-          a.click();
-          a.remove();
-          URL.revokeObjectURL(blobUrl);
-          statusEl.textContent = "Imagen descargada.";
-        } catch (err) {
-          statusEl.textContent = `Error: ${err.message}`;
-        } finally {
-          syncTextureHistoryButtons();
-        }
-      });
-
-      shareBtn.addEventListener("click", async () => {
-        if (textureHistory.length <= 1) {
-          statusEl.textContent = "Aplica una textura antes de compartir.";
-          return;
-        }
-        if (!navigator.share) {
-          statusEl.textContent = "Share no disponible en este navegador.";
-          return;
-        }
-
-        shareBtn.disabled = true;
-        try {
-          const blob = await getCurrentImageBlob();
-          const fileName = currentFilename || `edited_${Date.now()}.jpg`;
-          const file = new File([blob], fileName, {
-            type: blob.type || "image/jpeg",
-          });
-
-          if (navigator.canShare && !navigator.canShare({ files: [file] })) {
-            throw new Error("El dispositivo no soporta compartir archivos.");
-          }
-
-          await navigator.share({
-            files: [file],
-            title: "HyperReality",
-            text: "Edited texture preview",
-          });
-          statusEl.textContent = "Imagen compartida.";
-        } catch (err) {
-          if (err && err.name === "AbortError") {
-            statusEl.textContent = "Compartir cancelado.";
-          } else {
-            statusEl.textContent = `Error: ${err.message}`;
-          }
-        } finally {
-          syncTextureHistoryButtons();
-        }
-      });
-
-      async function loadSegmentedResult(data) {
-        segLog("log", "Cargando resultado segmentado en canvas", {
-          filename: data.filename,
-          mask_count: data.mask_count,
-        });
-        selectedMasks.clear();
-        hoveredMask = 0;
-
-        const img = new Image();
-        img.src = `/image/${encodeURIComponent(data.filename)}`;
-        await new Promise((resolve, reject) => {
-          img.onload = resolve;
-          img.onerror = reject;
-        });
-
-        canvas.width = img.naturalWidth;
-        canvas.height = img.naturalHeight;
-        ctx.drawImage(img, 0, 0);
-        originalImageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
-
-        const labelImg = new Image();
-        labelImg.src = `/masks/${encodeURIComponent(data.filename)}`;
-        await new Promise((resolve) => {
-          labelImg.onload = resolve;
-          labelImg.onerror = resolve;
-        });
-
-        if (labelImg.naturalWidth) {
-          const off = document.createElement("canvas");
-          off.width = canvas.width;
-          off.height = canvas.height;
-          const offCtx = off.getContext("2d");
-          offCtx.drawImage(labelImg, 0, 0);
-          labelData = offCtx.getImageData(0, 0, off.width, off.height);
-          try {
-            buildMaskDebugList(data.filename);
-            loadSavedMasks(data.filename);
-          } catch (e) {}
-        }
-
-        setEditorHasImage(true);
-        currentFilename = data.filename;
-        originalFilename = data.filename;
-        textureHistory = [data.filename];
-        appliedTextureHistory = [];
-        syncTextureHistoryButtons();
-        renderAppliedTextureHistory();
-        actionsBar.classList.add("visible");
-        await buildTextureGallery();
-        statusEl.textContent = `${data.mask_count} segments - hover to explore, click to select`;
-        setLoadingOverlay(false);
-        segLog("log", "Resultado segmentado cargado correctamente", {
-          currentFilename,
-          originalFilename,
-        });
-      }
-
-      // --- Mask debug helpers (localStorage + preview) ---
-      function buildMaskDebugList(owner) {
-        owner = owner || originalFilename || currentFilename;
-        const container = document.getElementById("mask-debug-list");
-        container.innerHTML = "";
-        if (!labelData) {
-          container.textContent = "No hay label map cargado.";
-          return;
-        }
-        const w = labelData.width,
-          h = labelData.height;
-        const ids = new Set();
-        for (let i = 0; i < labelData.data.length; i += 4) {
-          const id = labelData.data[i];
-          if (id) ids.add(id);
-        }
-        const idArr = Array.from(ids)
-          .filter((x) => x > 0)
-          .sort((a, b) => a - b);
-        if (!idArr.length) {
-          container.textContent = "No hay máscaras.";
-          return;
-        }
-
-        const pixelCounts = {};
-        const bboxes = {};
-        idArr.forEach((id) => {
-          pixelCounts[id] = 0;
-          bboxes[id] = { minX: w, minY: h, maxX: 0, maxY: 0 };
-        });
-
-        for (let y = 0; y < h; y++) {
-          for (let x = 0; x < w; x++) {
-            const idx = (y * w + x) * 4;
-            const lid = labelData.data[idx];
-            if (!lid) continue;
-            pixelCounts[lid] = (pixelCounts[lid] || 0) + 1;
-            const bb = bboxes[lid];
-            if (x < bb.minX) bb.minX = x;
-            if (y < bb.minY) bb.minY = y;
-            if (x > bb.maxX) bb.maxX = x;
-            if (y > bb.maxY) bb.maxY = y;
-          }
-        }
-
-        idArr.forEach((id) => {
-          const area = pixelCounts[id] || 0;
-          const bb = bboxes[id];
-          const boxW = Math.max(1, bb.maxX - bb.minX + 1);
-          const boxH = Math.max(1, bb.maxY - bb.minY + 1);
-
-          const card = document.createElement("div");
-          card.style =
-            "display:flex;align-items:center;gap:0.5rem;padding:0.25rem;border:1px solid #222;border-radius:6px;background:#0f0f0f;";
-
-          const preview = document.createElement("canvas");
-          preview.width = 120;
-          preview.height = Math.max(40, Math.round(120 * (boxH / boxW)));
-
-          const off = document.createElement("canvas");
-          off.width = boxW;
-          off.height = boxH;
-          const offCtx = off.getContext("2d");
-          const offImg = offCtx.createImageData(boxW, boxH);
-          for (let yy = 0; yy < boxH; yy++) {
-            for (let xx = 0; xx < boxW; xx++) {
-              const sx = bb.minX + xx;
-              const sy = bb.minY + yy;
-              const sidx = (sy * w + sx) * 4;
-              const lid = labelData.data[sidx];
-              const di = (yy * boxW + xx) * 4;
-              if (lid === id) {
-                offImg.data[di] = 255;
-                offImg.data[di + 1] = 255;
-                offImg.data[di + 2] = 255;
-                offImg.data[di + 3] = 255;
-              } else {
-                offImg.data[di] = 0;
-                offImg.data[di + 1] = 0;
-                offImg.data[di + 2] = 0;
-                offImg.data[di + 3] = 0;
-              }
-            }
-          }
-          offCtx.putImageData(offImg, 0, 0);
-
-          const pctx = preview.getContext("2d");
-          pctx.fillStyle = "#000";
-          pctx.fillRect(0, 0, preview.width, preview.height);
-          pctx.drawImage(
-            off,
-            0,
-            0,
-            boxW,
-            boxH,
-            0,
-            0,
-            preview.width,
-            preview.height,
-          );
-
-          const info = document.createElement("div");
-          info.style = "font-size:0.85rem;color:#ddd;";
-          info.innerHTML = `<div>ID ${id} | area ${area}</div><div style="font-size:0.75rem;color:#999">bbox ${bb.minX},${bb.minY} ${boxW}x${boxH}</div>`;
-
-          const btnSel = document.createElement("button");
-          btnSel.className = "action-btn";
-          btnSel.style.background = "#335d85";
-          btnSel.textContent = "Seleccionar";
-          btnSel.onclick = () => {
-            if (selectedMasks.has(id)) selectedMasks.delete(id);
-            else selectedMasks.add(id);
-            redraw();
-            statusEl.textContent = `${selectedMasks.size} segment(s) selected`;
-          };
-
-          const nameInput = document.createElement("input");
-          nameInput.placeholder = "nombre";
-          nameInput.style =
-            "margin-left:6px;padding:4px;border-radius:4px;background:#111;color:#ddd;border:1px solid #333;";
-          const btnSave = document.createElement("button");
-          btnSave.className = "action-btn";
-          btnSave.style.background = "#2a6";
-          btnSave.textContent = "Guardar";
-          btnSave.onclick = () => {
-            const thumb = preview.toDataURL("image/png");
-            const name = nameInput.value || "";
-            saveMaskToLocal(
-              owner || originalFilename || currentFilename,
-              id,
-              thumb,
-              { minX: bb.minX, minY: bb.minY, maxX: bb.maxX, maxY: bb.maxY },
-              area,
-              name,
-            );
-            statusEl.textContent = `Mascara ${id} guardada localmente.`;
-          };
-
-          const btnDownload = document.createElement("button");
-          btnDownload.className = "action-btn";
-          btnDownload.style.background = "#4f5b9d";
-          btnDownload.textContent = "Descargar";
-          btnDownload.onclick = () => {
-            const a = document.createElement("a");
-            a.href = preview.toDataURL("image/png");
-            a.download = `${owner || originalFilename || currentFilename || "mask"}_${id}.png`;
-            document.body.appendChild(a);
-            a.click();
-            a.remove();
-          };
-
-          card.appendChild(preview);
-          card.appendChild(info);
-          card.appendChild(btnSel);
-          card.appendChild(nameInput);
-          card.appendChild(btnSave);
-          card.appendChild(btnDownload);
-          container.appendChild(card);
-        });
-      }
-
-      function saveMaskToLocal(owner, id, thumb, bbox, area, name) {
-        const key = "hyper_masks_" + (owner || "global");
-        let arr = [];
-        try {
-          arr = JSON.parse(localStorage.getItem(key) || "[]");
-        } catch (e) {
-          arr = [];
-        }
-        arr.push({
-          maskIndex: id,
-          name: name || "",
-          thumb: thumb,
-          bbox: bbox,
-          area: area,
-          owner: owner,
-        });
-        localStorage.setItem(key, JSON.stringify(arr));
-        loadSavedMasks(owner);
-      }
-
-      function loadSavedMasks(owner) {
-        const key = "hyper_masks_" + (owner || "global");
-        const list = document.getElementById("mask-debug-local-list");
-        list.innerHTML = "";
-        let arr = [];
-        try {
-          arr = JSON.parse(localStorage.getItem(key) || "[]");
-        } catch (e) {
-          arr = [];
-        }
-        if (!arr.length) {
-          list.textContent = "No guardadas.";
-          return;
-        }
-        arr.forEach((item, idx) => {
-          const card = document.createElement("div");
-          card.style =
-            "display:flex;align-items:center;gap:0.5rem;padding:0.25rem;border:1px solid #222;border-radius:6px;background:#0f0f0f;";
-          const img = document.createElement("img");
-          img.src = item.thumb;
-          img.width = 120;
-          img.height = 80;
-          img.style = "object-fit:cover;border-radius:4px;";
-          const info = document.createElement("div");
-          info.style = "font-size:0.85rem;color:#ddd;";
-          info.innerHTML = `<div>${item.name || ""} (ID ${item.maskIndex})</div><div style="font-size:0.75rem;color:#999">area:${item.area}</div>`;
-          const btnApply = document.createElement("button");
-          btnApply.className = "action-btn";
-          btnApply.style.background = "#335d85";
-          btnApply.textContent = "Seleccionar";
-          btnApply.onclick = () => {
-            if (labelData) {
-              selectedMasks.add(item.maskIndex);
-              redraw();
-              statusEl.textContent = `Mascara ${item.maskIndex} seleccionada.`;
-            } else {
-              statusEl.textContent = "No hay label map cargado.";
-            }
-          };
-          const btnDel = document.createElement("button");
-          btnDel.className = "action-btn";
-          btnDel.style.background = "#a33";
-          btnDel.textContent = "Borrar";
-          btnDel.onclick = () => {
-            arr.splice(idx, 1);
-            localStorage.setItem(key, JSON.stringify(arr));
-            loadSavedMasks(owner);
-          };
-          card.appendChild(img);
-          card.appendChild(info);
-          card.appendChild(btnApply);
-          card.appendChild(btnDel);
-          list.appendChild(card);
-        });
-      }
-
-      document
-        .getElementById("mask-debug-refresh")
-        .addEventListener("click", () =>
-          buildMaskDebugList(originalFilename || currentFilename),
-        );
-      document
-        .getElementById("mask-debug-load-local")
-        .addEventListener("click", () =>
-          loadSavedMasks(originalFilename || currentFilename),
-        );
-      document
-        .getElementById("mask-debug-clear-local")
-        .addEventListener("click", () => {
-          localStorage.removeItem(
-            "hyper_masks_" + (originalFilename || currentFilename || "global"),
-          );
-          loadSavedMasks(originalFilename || currentFilename);
-          statusEl.textContent = "Local masks cleared";
-        });
-
-      async function pollUploadJob(jobId) {
-        segLog("log", "Inicio de polling del job de segmentacion", { jobId });
-        const MAX_POLLS = 300;
-        for (let i = 0; i < MAX_POLLS; i++) {
-          await new Promise((r) => setTimeout(r, 1000));
-          const res = await fetch(`/jobs/${jobId}`);
-          const data = await res.json();
-
-          if (!res.ok) {
-            segLog("error", "Error consultando estado del job", {
-              jobId,
-              data,
-            });
-            throw new Error(data.detail || "Status polling failed");
-          }
-
-          if (data.status === "done") {
-            segLog("log", "Job de segmentacion completado", {
-              jobId,
-              filename: data.filename,
-              mask_count: data.mask_count,
-            });
-            await loadSegmentedResult(data);
-            setLoadingOverlay(false);
-            segLog(
-              "log",
-              "Flujo de carga finalizado sin post-procesado adicional",
-              {
-                jobId,
-                filename: data.filename,
-              },
-            );
-            return;
-          }
-
-          if (data.status === "failed" || data.status === "timeout") {
-            segLog("error", "Job de segmentacion finalizo con error/timeout", {
-              jobId,
-              status: data.status,
-              message: data.message,
-            });
-            throw new Error(data.message || data.status);
-          }
-
-          const stage = data.stage || "processing";
-          const progress = Number.isFinite(data.progress) ? data.progress : 0;
-          const etaText = Number.isFinite(data.eta_seconds)
-            ? ` | ETA ~${Math.max(0, Math.ceil(data.eta_seconds))}s`
-            : "";
-          setLoadingOverlay(
-            true,
-            "Procesando imagen...",
-            `${stage} - ${progress}%${etaText}`,
-          );
-          statusEl.textContent = `${stage} - ${progress}%${etaText}`;
-          segLog("log", "Progreso de segmentacion", {
-            jobId,
-            poll: i + 1,
-            stage,
-            progress,
-            eta_seconds: data.eta_seconds,
-          });
-        }
-
-        segLog("error", "Timeout de polling alcanzado", { jobId });
-        throw new Error("Segmentation timeout in client polling");
-      }
-
-      async function startUploadProcess(fileFromEvent) {
-        if (isUploading) {
-          segLog(
-            "warn",
-            "Se ignoro inicio de upload porque ya hay uno en curso",
-          );
-          return;
-        }
-
-        const fileToUpload =
-          fileFromEvent ||
-          selectedUploadFile ||
-          (fileInput.files && fileInput.files[0]);
-        if (!fileToUpload) {
-          segLog("warn", "Intento de upload sin archivo seleccionado");
-          statusEl.textContent = "Selecciona una imagen primero.";
-          return;
-        }
-
-        segLog("log", "Iniciando upload para segmentacion", {
-          name: fileToUpload.name,
-          size: fileToUpload.size,
-          type: fileToUpload.type,
-        });
-
-        isUploading = true;
-        uploadBtn.disabled = true;
-        statusEl.textContent = "Uploading & segmenting...";
-        setLoadingOverlay(
-          true,
-          "Procesando imagen...",
-          "Subiendo archivo y preparando segmentacion.",
-        );
-        const formData = new FormData();
-        formData.append("file", fileToUpload);
-        try {
-          const res = await fetch("/upload_async", {
-            method: "POST",
-            body: formData,
-          });
-          const data = await res.json();
-          if (!res.ok || !data.job_id) {
-            segLog("error", "Fallo al crear job de upload_async", data);
-            throw new Error(data.detail || data.message || "Upload failed");
-          }
-          segLog("log", "Job de segmentacion creado", { job_id: data.job_id });
-          await pollUploadJob(data.job_id);
-        } catch (err) {
-          segLog("error", "Error general en startUploadProcess", {
-            error: err && err.message ? err.message : String(err),
-          });
-          statusEl.textContent = `Error: ${err.message}`;
-        } finally {
-          isUploading = false;
-          uploadBtn.disabled = !selectedUploadFile;
-          setLoadingOverlay(false);
-          segLog("log", "Fin del flujo de upload/segmentacion", {
-            hasSelectedUploadFile: !!selectedUploadFile,
-          });
-        }
-      }
-
-      function queueAutoUpload(file) {
-        if (!file) return;
-        if (autoUploadTimer) {
-          clearTimeout(autoUploadTimer);
-          autoUploadTimer = null;
-        }
-        autoUploadTimer = setTimeout(() => {
-          autoUploadTimer = null;
-          startUploadProcess(file);
-        }, 120);
-      }
-
-      uploadBtn.addEventListener("click", async () => {
-        await startUploadProcess();
-      });
-
-      emptyUploadBtn.addEventListener("click", () => {
-        fileInput.click();
-      });
-
-      if (emptyStateRightEl) {
-        emptyStateRightEl.addEventListener("click", () => {
-          fileInput.click();
-        });
-
-        emptyStateRightEl.addEventListener("dragover", (e) => {
-          e.preventDefault();
-          emptyStateRightEl.classList.add("drop-active");
-        });
-
-        emptyStateRightEl.addEventListener("dragleave", () => {
-          emptyStateRightEl.classList.remove("drop-active");
-        });
-
-        emptyStateRightEl.addEventListener("drop", (e) => {
-          e.preventDefault();
-          emptyStateRightEl.classList.remove("drop-active");
-          const file =
-            e.dataTransfer && e.dataTransfer.files && e.dataTransfer.files[0]
-              ? e.dataTransfer.files[0]
-              : null;
-          if (!file) return;
-          updateUploadSelection(file);
-          try {
-            const dt = new DataTransfer();
-            dt.items.add(file);
-            fileInput.files = dt.files;
-          } catch (err) {
-            // Some browsers may block direct FileList assignment.
-          }
-          queueAutoUpload(file);
-        });
-      }
-
-      hideLegacyUploadStrip();
-      applyFrontendDebugMode();
-      setEditorHasImage(false);
-
-      fileInput.addEventListener("change", () => {
-        const file =
-          fileInput.files && fileInput.files[0] ? fileInput.files[0] : null;
-        updateUploadSelection(file);
-        queueAutoUpload(file);
-      });
-
-      uploadDropzone.addEventListener("dragover", (e) => {
-        e.preventDefault();
-        uploadDropzone.classList.add("drop-active");
-      });
-
-      uploadDropzone.addEventListener("dragleave", () => {
-        uploadDropzone.classList.remove("drop-active");
-      });
-
-      uploadDropzone.addEventListener("drop", (e) => {
-        e.preventDefault();
-        uploadDropzone.classList.remove("drop-active");
-        const file =
-          e.dataTransfer && e.dataTransfer.files && e.dataTransfer.files[0]
-            ? e.dataTransfer.files[0]
-            : null;
-        if (!file) return;
-        updateUploadSelection(file);
-        try {
-          const dt = new DataTransfer();
-          dt.items.add(file);
-          fileInput.files = dt.files;
-        } catch (err) {
-          // Some browsers may block direct FileList assignment.
-        }
-        queueAutoUpload(file);
-      });
-    </script>
-  </body>
-</html>
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>SAM Editor</title>
+    <style>
+      * {
+        box-sizing: border-box;
+        margin: 0;
+        padding: 0;
+      }
+      body {
+        background: #f3f4f6;
+        color: #1f2937;
+        font-family: Arial, sans-serif;
+        display: flex;
+        flex-direction: column;
+        height: 100vh;
+        overflow: hidden;
+      }
+      #toolbar {
+        display: flex;
+        align-items: center;
+        gap: 0.5rem;
+        padding: 0.5rem 1rem;
+        background: #ffffff;
+        border-bottom: 1px solid #d1d5db;
+        flex-shrink: 0;
+      }
+      #brand {
+        font-size: 0.9rem;
+        font-weight: 700;
+        letter-spacing: 0.08em;
+        color: #0f172a;
+        text-transform: uppercase;
+        margin-right: 0.35rem;
+      }
+      #upload-strip {
+        display: flex;
+        align-items: center;
+        gap: 0.75rem;
+        padding: 0.65rem 1rem;
+        background: linear-gradient(90deg, #ffffff 0%, #f8fafc 100%);
+        border-bottom: 1px solid #e5e7eb;
+        flex-shrink: 0;
+        flex-wrap: wrap;
+      }
+      /* Hidden: upload flow now uses the large empty-state drop area */
+      #upload-strip {
+        display: none;
+      }
+      #top-export-actions {
+        display: flex;
+        gap: 0.4rem;
+        align-items: center;
+      }
+      #upload-strip label {
+        font-size: 0.85rem;
+        color: #475569;
+      }
+      #upload-picker {
+        display: flex;
+        align-items: center;
+        gap: 0.55rem;
+        min-width: 340px;
+        flex: 1;
+      }
+      #upload-dropzone {
+        display: flex;
+        align-items: center;
+        gap: 0.55rem;
+        flex-wrap: wrap;
+        border: 1px dashed #94a3b8;
+        border-radius: 8px;
+        background: #ffffff;
+        padding: 0.42rem 0.55rem;
+        cursor: pointer;
+        min-height: 42px;
+        flex: 1;
+        transition:
+          border-color 0.18s,
+          background 0.18s;
+      }
+      #upload-dropzone:hover {
+        border-color: #16a34a;
+        background: #eefaf1;
+      }
+      #upload-dropzone.drop-active {
+        border-color: #f3c21b;
+        background: #fff8dc;
+      }
+      #upload-primary {
+        color: #0f172a;
+        font-size: 0.83rem;
+        font-weight: 600;
+      }
+      #upload-secondary {
+        color: #64748b;
+        font-size: 0.74rem;
+      }
+      #file-pill {
+        margin-left: auto;
+        max-width: 220px;
+        overflow: hidden;
+        text-overflow: ellipsis;
+        white-space: nowrap;
+        background: #eef2f7;
+        border: 1px solid #cbd5e1;
+        border-radius: 999px;
+        color: #334155;
+        font-size: 0.73rem;
+        padding: 0.18rem 0.5rem;
+      }
+      #file-input {
+        display: none;
+      }
+      #upload-btn {
+        padding: 0.35rem 0.9rem;
+        background: #2a6;
+        color: #fff;
+        border: none;
+        border-radius: 4px;
+        cursor: pointer;
+        font-size: 0.85rem;
+        min-height: 42px;
+      }
+      #upload-btn:disabled {
+        background: #94a3b8;
+        cursor: default;
+      }
+      #status {
+        font-size: 0.8rem;
+        color: #475569;
+        margin-left: auto;
+      }
+      #workspace {
+        flex: 1;
+        min-height: 0;
+        display: flex;
+        overflow: hidden;
+      }
+      #canvas-container {
+        flex: 1;
+        display: flex;
+        align-items: center;
+        justify-content: center;
+        overflow: hidden;
+        background: #ececec;
+        padding: 1.2rem;
+      }
+      #main-panel {
+        flex: 1;
+        min-width: 0;
+        display: flex;
+        overflow: hidden;
+      }
+      #canvas {
+        max-width: 100%;
+        max-height: 100%;
+        cursor: crosshair;
+        display: none;
+        border-radius: 8px;
+        box-shadow: 0 10px 24px rgba(0, 0, 0, 0.22);
+      }
+      #empty-state {
+        width: min(1120px, 100%);
+        min-height: min(620px, 100%);
+        border-radius: 12px;
+        background: #f4f4f4;
+        border: 1px solid #d6d6d6;
+        display: flex;
+        gap: 1.1rem;
+        padding: 1.15rem;
+      }
+      #empty-state-left {
+        width: 320px;
+        min-width: 280px;
+        display: flex;
+        flex-direction: column;
+        gap: 0.9rem;
+        color: #1e293b;
+      }
+      #empty-state-title {
+        font-size: 2rem;
+        line-height: 1.05;
+        font-weight: 700;
+        color: #1f2937;
+      }
+      .empty-step {
+        display: flex;
+        align-items: center;
+        gap: 0.55rem;
+        font-size: 1.02rem;
+        color: #1f2937;
+        font-weight: 600;
+      }
+      .empty-step::before {
+        content: "";
+        width: 12px;
+        height: 12px;
+        border-radius: 50%;
+        background: #f3c21b;
+        box-shadow: 0 0 0 3px rgba(243, 194, 27, 0.22);
+      }
+      #empty-upload-btn {
+        margin-top: 0.25rem;
+        min-height: 52px;
+        border: none;
+        border-radius: 10px;
+        background: #f3c21b;
+        color: #111827;
+        font-size: 1.2rem;
+        font-weight: 700;
+        cursor: pointer;
+      }
+      #empty-state-right {
+        flex: 1;
+        min-width: 0;
+        border-radius: 12px;
+        position: relative;
+        overflow: hidden;
+        background: linear-gradient(
+          145deg,
+          #d8d8d8 0%,
+          #cecece 40%,
+          #c2c2c2 100%
+        );
+        cursor: pointer;
+        border: 2px dashed transparent;
+        transition:
+          border-color 0.18s,
+          box-shadow 0.18s,
+          background 0.18s;
+      }
+      #empty-state-right:hover {
+        border-color: #f3c21b;
+        box-shadow: inset 0 0 0 1px rgba(255, 255, 255, 0.4);
+      }
+      #empty-state-right.drop-active {
+        border-color: #16a34a;
+        background: linear-gradient(
+          145deg,
+          #dce8dc 0%,
+          #d6e4d6 40%,
+          #cad8ca 100%
+        );
+      }
+      #empty-preview-image {
+        position: absolute;
+        inset: 0;
+        width: 100%;
+        height: 100%;
+        object-fit: cover;
+        display: none;
+      }
+      #empty-drop-hint {
+        position: absolute;
+        inset: 0;
+        display: flex;
+        align-items: center;
+        justify-content: center;
+        text-align: center;
+        padding: 1rem;
+        color: #334155;
+        font-weight: 700;
+        font-size: 1.05rem;
+        letter-spacing: 0.01em;
+        background: linear-gradient(
+          180deg,
+          rgba(255, 255, 255, 0.12),
+          rgba(255, 255, 255, 0.02)
+        );
+      }
+      #empty-room {
+        position: absolute;
+        inset: 0;
+      }
+      #actions {
+        display: none;
+        width: 300px;
+        min-width: 260px;
+        max-width: 360px;
+        flex-direction: column;
+        align-items: stretch;
+        gap: 0.6rem;
+        padding: 0.65rem;
+        background: #f8fafc;
+        border-right: 1px solid #dbe2ea;
+        flex-shrink: 0;
+        overflow: hidden;
+      }
+      #actions.visible {
+        display: flex;
+      }
+      #actions label {
+        font-size: 0.8rem;
+        color: #475569;
+        white-space: nowrap;
+      }
+      .action-btn {
+        padding: 0.35rem 0.9rem;
+        border: none;
+        border-radius: 4px;
+        cursor: pointer;
+        font-size: 0.85rem;
+        color: #fff;
+        white-space: nowrap;
+      }
+      #tex-apply-btn {
+        background: #a62;
+      }
+      .action-btn:disabled {
+        background: #444 !important;
+        cursor: default;
+      }
+      #tex-panel {
+        display: flex;
+        align-items: stretch;
+        flex-direction: column;
+        gap: 0.5rem;
+        flex: 1;
+        min-width: 0;
+        min-height: 0;
+      }
+      #tex-history-actions {
+        display: flex;
+        gap: 0.4rem;
+      }
+      #replace-controls {
+        display: flex;
+        flex-direction: column;
+        gap: 0.32rem;
+        padding: 0.35rem 0.4rem;
+        border: 1px solid #d8e0ea;
+        border-radius: 6px;
+        background: #ffffff;
+      }
+      #replace-controls label {
+        font-size: 0.76rem;
+        color: #64748b;
+      }
+      #replace-mode {
+        background: #202020;
+        border: 1px solid #3d3d3d;
+        color: #ddd;
+        border-radius: 4px;
+        padding: 0.28rem 0.35rem;
+        font-size: 0.8rem;
+      }
+      #replace-strength-wrap {
+        display: flex;
+        align-items: center;
+        gap: 0.45rem;
+      }
+      #replace-strength {
+        width: 100%;
+      }
+      #replace-strength-value {
+        min-width: 2.9rem;
+        text-align: right;
+        font-size: 0.76rem;
+        color: #b7b7b7;
+      }
+      #lighting-controls {
+        display: flex;
+        flex-direction: column;
+        gap: 0.32rem;
+        padding: 0.35rem 0.4rem;
+        border: 1px solid #2f2f2f;
+        border-radius: 6px;
+        background: #141414;
+      }
+      #lighting-controls label {
+        font-size: 0.76rem;
+        color: #9f9f9f;
+      }
+      #lighting-mode {
+        background: #202020;
+        border: 1px solid #3d3d3d;
+        color: #ddd;
+        border-radius: 4px;
+        padding: 0.28rem 0.35rem;
+        font-size: 0.8rem;
+      }
+      #light-angle-wrap,
+      #light-intensity-wrap {
+        display: flex;
+        align-items: center;
+        gap: 0.45rem;
+      }
+      #light-angle,
+      #light-intensity {
+        width: 100%;
+      }
+      #light-angle-value,
+      #light-intensity-value {
+        min-width: 3.4rem;
+        text-align: right;
+        font-size: 0.76rem;
+        color: #b7b7b7;
+      }
+      #exterior-controls {
+        display: none;
+      }
+      #exterior-controls label {
+        font-size: 0.76rem;
+        color: #9f9f9f;
+      }
+      #ext-target,
+      #ext-priority,
+      #ext-top-k,
+      #ext-min-area,
+      #ext-max-area,
+      #ext-keywords {
+        width: 100%;
+        background: #202020;
+        border: 1px solid #3d3d3d;
+        color: #ddd;
+        border-radius: 4px;
+        padding: 0.28rem 0.35rem;
+        font-size: 0.8rem;
+      }
+      #ext-actions {
+        display: flex;
+        gap: 0.4rem;
+      }
+      #ext-analyze-btn {
+        background: #4f5b9d;
+      }
+      #ext-segment-btn {
+        background: #3f7f54;
+      }
+      #tex-reset-btn {
+        background: #555;
+      }
+      #tex-undo-btn {
+        background: #335d85;
+      }
+      #download-btn {
+        background: #2d7c4f;
+      }
+      #share-btn {
+        background: #5f4fb2;
+      }
+      #tex-gallery {
+        display: flex;
+        flex-direction: column;
+        align-items: stretch;
+        gap: 0.6rem;
+        overflow-x: hidden;
+        overflow-y: auto;
+        flex: 1;
+        padding: 0.25rem 0;
+        scrollbar-width: thin;
+      }
+      .tex-section {
+        display: flex;
+        flex-direction: column;
+        gap: 0.35rem;
+      }
+      .tex-section-title {
+        color: #64748b;
+        font-size: 0.76rem;
+        text-transform: uppercase;
+        letter-spacing: 0.06em;
+      }
+      .tex-row {
+        display: flex;
+        gap: 0.4rem;
+        flex-wrap: wrap;
+        padding-bottom: 0;
+      }
+      .tex-empty {
+        color: #64748b;
+        font-size: 0.72rem;
+        font-style: italic;
+        padding: 0.1rem 0.2rem;
+      }
+      .tex-card {
+        width: 104px;
+        flex-shrink: 0;
+        cursor: pointer;
+        border-radius: 8px;
+        border: 1px solid #dbe2ea;
+        background: #ffffff;
+        padding: 0.22rem;
+        display: flex;
+        flex-direction: column;
+        gap: 0.28rem;
+        transition:
+          border-color 0.15s,
+          box-shadow 0.15s,
+          transform 0.15s;
+      }
+      .tex-thumb {
+        width: 100%;
+        height: 64px;
+        border-radius: 6px;
+        border: 2px solid transparent;
+        object-fit: cover;
+        opacity: 0.88;
+        transition:
+          opacity 0.15s,
+          border-color 0.15s;
+      }
+      .tex-card-copy {
+        display: flex;
+        flex-direction: column;
+        gap: 0.14rem;
+      }
+      .tex-card-name {
+        color: #0f172a;
+        font-size: 0.68rem;
+        font-weight: 700;
+        line-height: 1.15;
+      }
+      .tex-card-size {
+        color: #64748b;
+        font-size: 0.62rem;
+        line-height: 1.15;
+      }
+      .tex-card-path {
+        color: #94a3b8;
+        font-size: 0.58rem;
+        line-height: 1.1;
+        word-break: break-word;
+      }
+      .tex-card:hover {
+        transform: translateY(-1px);
+        border-color: #cbd5e1;
+        box-shadow: 0 6px 16px rgba(15, 23, 42, 0.08);
+      }
+      .tex-card:hover .tex-thumb {
+        opacity: 1;
+      }
+      .tex-card.active {
+        border-color: #f3c21b;
+        box-shadow: 0 0 0 2px rgba(243, 194, 27, 0.16);
+      }
+      .tex-card.active .tex-thumb {
+        border-color: #f90;
+        opacity: 1;
+      }
+      #loading-overlay {
+        position: fixed;
+        inset: 0;
+        background: rgba(15, 23, 42, 0.58);
+        backdrop-filter: blur(2px);
+        display: none;
+        align-items: center;
+        justify-content: center;
+        z-index: 9999;
+      }
+      #loading-overlay.visible {
+        display: flex;
+      }
+      #loading-card {
+        min-width: 260px;
+        max-width: min(92vw, 440px);
+        border-radius: 12px;
+        background: #ffffff;
+        border: 1px solid #dbe2ea;
+        box-shadow: 0 20px 48px rgba(2, 8, 23, 0.28);
+        padding: 1.15rem 1.2rem;
+        display: flex;
+        flex-direction: column;
+        gap: 0.55rem;
+      }
+      #loading-row {
+        display: flex;
+        align-items: center;
+        gap: 0.65rem;
+      }
+      #loading-spinner {
+        width: 22px;
+        height: 22px;
+        border-radius: 50%;
+        border: 3px solid #d1d5db;
+        border-top-color: #16a34a;
+        animation: spin 0.85s linear infinite;
+        flex-shrink: 0;
+      }
+      #loading-title {
+        font-size: 0.95rem;
+        font-weight: 700;
+        color: #0f172a;
+      }
+      #loading-text {
+        font-size: 0.82rem;
+        color: #475569;
+        line-height: 1.35;
+      }
+      @keyframes spin {
+        to {
+          transform: rotate(360deg);
+        }
+      }
+      @media (max-width: 900px) {
+        #workspace {
+          flex-direction: column;
+        }
+        #actions {
+          width: 100%;
+          max-width: none;
+          min-width: 0;
+          border-right: none;
+          border-bottom: 1px solid #333;
+          max-height: 45vh;
+        }
+        #empty-state {
+          flex-direction: column;
+          min-height: 70vh;
+        }
+        #empty-state-left {
+          width: 100%;
+          min-width: 0;
+        }
+      }
+    </style>
+  </head>
+  <body>
+    <div id="toolbar">
+      <span id="brand">HyperReality</span>
+      <span id="status">No image loaded</span>
+    </div>
+    <div id="upload-strip">
+      <div id="top-export-actions">
+        <button id="download-btn" class="action-btn">Download</button>
+        <button id="share-btn" class="action-btn">Share</button>
+      </div>
+      <div id="upload-picker">
+        <label id="upload-dropzone" for="file-input">
+          <span id="upload-primary">Selecciona o arrastra tu imagen</span>
+          <span id="upload-secondary">JPG, PNG o WEBP</span>
+          <span id="file-pill">Ningún archivo</span>
+        </label>
+        <input id="file-input" type="file" accept="image/*" />
+        <button id="upload-btn" disabled>Procesar</button>
+      </div>
+    </div>
+    <div id="workspace">
+      <div id="actions">
+        <div id="tex-panel">
+          <label>Textura por categoria</label>
+          <div id="exterior-controls">
+            <label for="ext-target">Exterior target</label>
+            <select id="ext-target">
+              <option value="wall" selected>Wall / Facade</option>
+              <option value="roof">Roof</option>
+              <option value="window">Window</option>
+            </select>
+            <label for="ext-priority">Priority</label>
+            <select id="ext-priority">
+              <option value="speed">Speed</option>
+              <option value="balanced" selected>Balanced</option>
+              <option value="quality">Quality</option>
+            </select>
+            <label for="ext-top-k">Top-K masks</label>
+            <input
+              id="ext-top-k"
+              type="number"
+              min="1"
+              max="20"
+              step="1"
+              value="8"
+            />
+            <label for="ext-min-area">Min area ratio</label>
+            <input
+              id="ext-min-area"
+              type="number"
+              min="0"
+              max="1"
+              step="0.001"
+              value="0.01"
+            />
+            <label for="ext-max-area">Max area ratio</label>
+            <input
+              id="ext-max-area"
+              type="number"
+              min="0"
+              max="1"
+              step="0.001"
+              value="0.85"
+            />
+            <label for="ext-keywords"
+              >Semantic keywords (comma-separated)</label
+            >
+            <input
+              id="ext-keywords"
+              type="text"
+              value="building,wall,facade,house,roof,window,door"
+            />
+            <div id="ext-actions">
+              <button id="ext-analyze-btn" class="action-btn">
+                Analyze Exterior
+              </button>
+              <button id="ext-segment-btn" class="action-btn">
+                Segment Exterior
+              </button>
+            </div>
+          </div>
+          <div id="tex-gallery"></div>
+
+          <div id="mask-debug" style="margin-top: 0.6rem">
+            <label style="color: #475569; font-size: 0.82rem"
+              >Debug máscaras</label
+            >
+            <div
+              id="mask-debug-controls"
+              style="display: flex; gap: 0.4rem; margin-top: 0.25rem"
+            >
+              <button
+                id="mask-debug-refresh"
+                class="action-btn"
+                style="background: #444"
+              >
+                Refrescar Máscaras
+              </button>
+              <button
+                id="mask-debug-load-local"
+                class="action-btn"
+                style="background: #2a6"
+              >
+                Cargar Guardadas
+              </button>
+              <button
+                id="mask-debug-clear-local"
+                class="action-btn"
+                style="background: #a33"
+              >
+                Borrar Guardadas
+              </button>
+            </div>
+            <div
+              id="mask-debug-list"
+              style="
+                display: flex;
+                flex-direction: column;
+                gap: 0.4rem;
+                margin-top: 0.4rem;
+                max-height: 220px;
+                overflow: auto;
+              "
+            ></div>
+            <div
+              id="mask-debug-local-list"
+              style="
+                display: flex;
+                flex-direction: column;
+                gap: 0.4rem;
+                margin-top: 0.6rem;
+                max-height: 220px;
+                overflow: auto;
+                border-top: 1px solid #dbe2ea;
+                padding-top: 0.4rem;
+              "
+            ></div>
+          </div>
+          <div id="replace-controls" style="margin-top: 0.35rem">
+            <label
+              style="
+                font-size: 0.85rem;
+                color: #334155;
+                display: flex;
+                align-items: center;
+                gap: 0.4rem;
+              "
+            >
+              <input
+                id="clear-mask-checkbox"
+                type="checkbox"
+                checked
+                style="transform: scale(0.95)"
+              />
+              Limpiar máscara antes de aplicar
+            </label>
+          </div>
+          <div
+            id="applied-textures"
+            style="
+              margin-top: 0.45rem;
+              border: 1px solid #d8e0ea;
+              border-radius: 6px;
+              background: #ffffff;
+              padding: 0.35rem 0.4rem;
+            "
+          >
+            <label style="font-size: 0.78rem; color: #64748b"
+              >Texturas aplicadas</label
+            >
+            <div
+              id="applied-texture-list"
+              style="
+                margin-top: 0.3rem;
+                max-height: 160px;
+                overflow: auto;
+                display: flex;
+                flex-direction: column;
+                gap: 0.28rem;
+              "
+            ></div>
+          </div>
+          <div id="tex-history-actions">
+            <button id="tex-reset-btn" class="action-btn">Reset All</button>
+            <button id="tex-undo-btn" class="action-btn">Undo Last</button>
+            <button id="tex-apply-btn" class="action-btn">
+              Aplicar Textura
+            </button>
+          </div>
+        </div>
+      </div>
+      <div id="main-panel">
+        <div id="canvas-container">
+          <div id="empty-state">
+            <div id="empty-state-left">
+              <div id="empty-state-title">Ver los productos en su cuarto</div>
+              <div class="empty-step">Sube una foto de tu habitación</div>
+              <div class="empty-step">Prueba nuestras texturas</div>
+              <button id="empty-upload-btn" type="button">Sube tu foto</button>
+            </div>
+            <div id="empty-state-right">
+              <img id="empty-preview-image" alt="Vista previa de imagen" />
+              <div id="empty-drop-hint">
+                Arrastra tu imagen aqui<br />o haz clic para seleccionar
+              </div>
+              <div id="empty-room"></div>
+            </div>
+          </div>
+          <canvas id="canvas"></canvas>
+        </div>
+      </div>
+    </div>
+    <div id="loading-overlay" aria-live="polite" aria-busy="true">
+      <div id="loading-card">
+        <div id="loading-row">
+          <div id="loading-spinner"></div>
+          <div id="loading-title">Procesando imagen...</div>
+        </div>
+        <div id="loading-text">Estamos subiendo y segmentando tu foto.</div>
+      </div>
+    </div>
+    <script>
+      const FRONTEND_DEBUG_MODE = __FRONTEND_DEBUG_ENABLED__;
+
+      const fileInput = document.getElementById("file-input");
+      const uploadBtn = document.getElementById("upload-btn");
+      const statusEl = document.getElementById("status");
+      const canvas = document.getElementById("canvas");
+      const ctx = canvas.getContext("2d");
+      const emptyStateEl = document.getElementById("empty-state");
+      const emptyUploadBtn = document.getElementById("empty-upload-btn");
+      const emptyStateRightEl = document.getElementById("empty-state-right");
+      const emptyDropHintEl = document.getElementById("empty-drop-hint");
+      const emptyPreviewImageEl = document.getElementById(
+        "empty-preview-image",
+      );
+      const emptyRoomEl = document.getElementById("empty-room");
+      const uploadStripEl = document.getElementById("upload-strip");
+      const uploadDropzone = document.getElementById("upload-dropzone");
+      const filePill = document.getElementById("file-pill");
+      const maskDebugEl = document.getElementById("mask-debug");
+      const loadingOverlayEl = document.getElementById("loading-overlay");
+      const loadingTitleEl = document.getElementById("loading-title");
+      const loadingTextEl = document.getElementById("loading-text");
+
+      const actionsBar = document.getElementById("actions");
+      const texGallery = document.getElementById("tex-gallery");
+      const texResetBtn = document.getElementById("tex-reset-btn");
+      const texUndoBtn = document.getElementById("tex-undo-btn");
+      const downloadBtn = document.getElementById("download-btn");
+      const shareBtn = document.getElementById("share-btn");
+      const texApplyBtn = document.getElementById("tex-apply-btn");
+      const extTargetEl = document.getElementById("ext-target");
+      const extPriorityEl = document.getElementById("ext-priority");
+      const extTopKEl = document.getElementById("ext-top-k");
+      const extMinAreaEl = document.getElementById("ext-min-area");
+      const extMaxAreaEl = document.getElementById("ext-max-area");
+      const extKeywordsEl = document.getElementById("ext-keywords");
+      const extAnalyzeBtn = document.getElementById("ext-analyze-btn");
+      const extSegmentBtn = document.getElementById("ext-segment-btn");
+      const appliedTextureListEl = document.getElementById(
+        "applied-texture-list",
+      );
+
+      let originalImageData = null;
+      let labelData = null;
+      let hoveredMask = 0;
+      const selectedMasks = new Set();
+      let currentFilename = null;
+      let originalFilename = null;
+      let selectedTextureName = null;
+      let allTextureNames = [];
+      let textureHistory = [];
+      let appliedTextureHistory = [];
+      let selectedUploadFile = null;
+      let previewObjectUrl = null;
+      let isUploading = false;
+      let autoUploadTimer = null;
+
+      const ACM_TEXTURE_CATALOG = [
+        {
+          nombre: "Glossy White",
+          textura: "Texture_ACM/ACM_White.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Amarillo",
+          textura: "Texture_ACM/ACM_Amarillo.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Glossy Orange",
+          textura: "Texture_ACM/ACM_Orange.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Glossy Red",
+          textura: "Texture_ACM/ACM_Glossy_Red.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Light Blue",
+          textura: "Texture_ACM/ACM_Light_Blue.png",
+          dimensiones: ["1.22x2.44"],
+        },
+        {
+          nombre: "Azul",
+          textura: "Texture_ACM/ACM_Azul.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Verde HN",
+          textura: "Texture_ACM/ACM_Verde_HN.png",
+          dimensiones: ["1.22x2.44"],
+        },
+        {
+          nombre: "Verde Lima",
+          textura: "Texture_ACM/ACM_Verde_Lima.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Verde",
+          textura: "Texture_ACM/ACM_Verde.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Madera Clara",
+          textura: "Texture_ACM/ACM_Madera_Clara.png",
+          dimensiones: ["1.22x2.44"],
+        },
+        {
+          nombre: "Roble (Oak)",
+          textura: "Texture_ACM/ACM_ROBLE(OAK).png",
+          dimensiones: ["1.22x2.44"],
+        },
+        {
+          nombre: "Grafito",
+          textura: "Texture_ACM/ACM_Grafito.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Silver Metallic",
+          textura: "Texture_ACM/ACM_Metalic.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Mouse Grey",
+          textura: "Texture_ACM/ACM_MouseGrey.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Matte Black",
+          textura: "Texture_ACM/ACM_Matteblack.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+        {
+          nombre: "Glossy Black",
+          textura: "Texture_ACM/ACM_Glossy_Black.png",
+          dimensiones: ["1.22x2.44", "1.50x4.98"],
+        },
+      ];
+
+      const ACM_TEXTURE_META = ACM_TEXTURE_CATALOG.reduce(
+        (acc, item, index) => {
+          acc[item.textura.toLowerCase()] = {
+            ...item,
+            orden: index,
+          };
+          return acc;
+        },
+        {},
+      );
+
+      function segLog(level, message, payload) {
+        const tag = "[SEGMENTACION_UI]";
+        const ts = new Date().toISOString();
+        const method = typeof console[level] === "function" ? level : "log";
+        if (typeof payload === "undefined") {
+          console[method](`${tag} ${ts} ${message}`);
+          return;
+        }
+        console[method](`${tag} ${ts} ${message}`, payload);
+      }
+
+      function setLoadingOverlay(visible, title, text) {
+        if (!loadingOverlayEl) return;
+        if (title && loadingTitleEl) {
+          loadingTitleEl.textContent = title;
+        }
+        if (text && loadingTextEl) {
+          loadingTextEl.textContent = text;
+        }
+        if (visible) {
+          loadingOverlayEl.classList.add("visible");
+        } else {
+          loadingOverlayEl.classList.remove("visible");
+        }
+      }
+
+      function applyFrontendDebugMode() {
+        if (!maskDebugEl) return;
+        maskDebugEl.style.display = FRONTEND_DEBUG_MODE ? "block" : "none";
+      }
+
+      function hideLegacyUploadStrip() {
+        if (!uploadStripEl) return;
+        uploadStripEl.style.setProperty("display", "none", "important");
+        uploadStripEl.setAttribute("hidden", "hidden");
+      }
+
+      function setEditorHasImage(hasImage) {
+        if (hasImage) {
+          emptyStateEl.style.display = "none";
+          canvas.style.display = "block";
+        } else {
+          emptyStateEl.style.display = "flex";
+          canvas.style.display = "none";
+        }
+      }
+
+      function updateUploadSelection(file) {
+        selectedUploadFile = file || null;
+        if (!file) {
+          filePill.textContent = "Ningún archivo";
+          uploadBtn.disabled = true;
+          if (previewObjectUrl) {
+            try {
+              URL.revokeObjectURL(previewObjectUrl);
+            } catch (err) {}
+            previewObjectUrl = null;
+          }
+          emptyPreviewImageEl.style.display = "none";
+          emptyPreviewImageEl.removeAttribute("src");
+          emptyRoomEl.style.display = "block";
+          if (emptyDropHintEl) emptyDropHintEl.style.display = "flex";
+          return;
+        }
+        filePill.textContent = file.name;
+        uploadBtn.disabled = false;
+        statusEl.textContent = `Archivo listo: ${file.name}`;
+        if (previewObjectUrl) {
+          try {
+            URL.revokeObjectURL(previewObjectUrl);
+          } catch (err) {}
+        }
+        previewObjectUrl = URL.createObjectURL(file);
+        emptyPreviewImageEl.src = previewObjectUrl;
+        emptyPreviewImageEl.style.display = "block";
+        emptyRoomEl.style.display = "none";
+        if (emptyDropHintEl) emptyDropHintEl.style.display = "none";
+      }
+
+      function renderAppliedTextureHistory() {
+        if (!appliedTextureListEl) return;
+        appliedTextureListEl.innerHTML = "";
+
+        if (!appliedTextureHistory.length) {
+          const empty = document.createElement("div");
+          empty.style = "font-size:0.74rem;color:#64748b;";
+          empty.textContent = "Aún no se aplicaron texturas.";
+          appliedTextureListEl.appendChild(empty);
+          return;
+        }
+
+        appliedTextureHistory.forEach((item, idx) => {
+          const row = document.createElement("div");
+          row.style =
+            "font-size:0.74rem; color:#0f172a; border:1px solid #dbe2ea; border-radius:4px; padding:0.22rem 0.3rem; background:#f8fafc;";
+          const masksText = Array.isArray(item.mask_indices)
+            ? item.mask_indices.join(", ")
+            : "";
+          row.textContent = `#${idx + 1} ${item.texture_name} | masks: [${masksText}]`;
+          appliedTextureListEl.appendChild(row);
+        });
+      }
+
+      function syncTextureHistoryButtons() {
+        const canEdit = textureHistory.length > 0;
+        const canUndo = textureHistory.length > 1;
+        const canExport = textureHistory.length > 1;
+        texResetBtn.disabled = !canEdit;
+        texUndoBtn.disabled = !canUndo;
+        downloadBtn.disabled = !canExport;
+        shareBtn.disabled = !canExport;
+      }
+
+      async function getCurrentImageBlob() {
+        if (!currentFilename) {
+          throw new Error("No hay imagen para exportar.");
+        }
+        const res = await fetch(
+          `/image/${encodeURIComponent(currentFilename)}?t=${Date.now()}`,
+        );
+        if (!res.ok) {
+          throw new Error("No se pudo cargar la imagen actual.");
+        }
+        return await res.blob();
+      }
+      syncTextureHistoryButtons();
+      renderAppliedTextureHistory();
+
+      function encodeTexturePath(path) {
+        return path
+          .split("/")
+          .map((part) => encodeURIComponent(part))
+          .join("/");
+      }
+
+      function textureFilename(path) {
+        return (
+          String(path || "")
+            .split("/")
+            .filter(Boolean)
+            .pop() || ""
+        );
+      }
+
+      function humanizeTextureName(name) {
+        return textureFilename(name)
+          .replace(/\.[^.]+$/, "")
+          .replace(/[_-]+/g, " ")
+          .trim();
+      }
+
+      function getTextureMeta(name) {
+        const normalized = String(name || "")
+          .replace(/\\/g, "/")
+          .toLowerCase();
+        const fromCatalog = ACM_TEXTURE_META[normalized];
+        if (fromCatalog) {
+          return fromCatalog;
+        }
+        return {
+          nombre: humanizeTextureName(name),
+          textura: name,
+          dimensiones: [],
+          orden: Number.MAX_SAFE_INTEGER,
+        };
+      }
+
+      function categoryFromTextureName(name) {
+        const n = name.toLowerCase();
+        const acmHints = ["acm"];
+        const deckHints = ["deck", "wood", "plank", "laminate", "floor"];
+
+        if (acmHints.some((h) => n.includes(h))) return "acm";
+        if (deckHints.some((h) => n.includes(h))) return "deck";
+        return null;
+      }
+
+      function deckPriority(name) {
+        const n = String(name || "").toLowerCase();
+        if (n.includes("wood_planks") || n.includes("plank_flooring")) return 0;
+        if (n.includes("wood_floor") || n.includes("laminate_floor")) return 1;
+        if (n.includes("deck_")) return 2;
+        return 3;
+      }
+
+      function acmPriority(name) {
+        return getTextureMeta(name).orden;
+      }
+
+      function categoryTitle(category) {
+        if (category === "acm") return "ACM";
+        if (category === "deck") return "Deck";
+        return category;
+      }
+
+      function textureDisplayName(name) {
+        return getTextureMeta(name).nombre || humanizeTextureName(name);
+      }
+
+      function textureDimensionsLabel(name) {
+        const dimensions = getTextureMeta(name).dimensiones || [];
+        return dimensions.join(" | ");
+      }
+
+      function renderTextureGallery() {
+        texGallery.innerHTML = "";
+        selectedTextureName = null;
+
+        const categoryOrder = ["acm", "deck"];
+        const grouped = { acm: [], deck: [] };
+        allTextureNames.forEach((name) => {
+          const category = categoryFromTextureName(name);
+          if (category) {
+            grouped[category].push(name);
+          }
+        });
+
+        grouped.deck.sort((left, right) => {
+          const diff = deckPriority(left) - deckPriority(right);
+          return diff !== 0 ? diff : left.localeCompare(right);
+        });
+
+        grouped.acm.sort((left, right) => {
+          const diff = acmPriority(left) - acmPriority(right);
+          return diff !== 0 ? diff : left.localeCompare(right);
+        });
+
+        categoryOrder.forEach((category) => {
+          const names = grouped[category];
+
+          const section = document.createElement("div");
+          section.className = "tex-section";
+
+          const title = document.createElement("div");
+          title.className = "tex-section-title";
+          title.textContent = categoryTitle(category);
+          section.appendChild(title);
+
+          const row = document.createElement("div");
+          row.className = "tex-row";
+
+          if (!names.length) {
+            const empty = document.createElement("div");
+            empty.className = "tex-empty";
+            empty.textContent = "Sin texturas en esta categoria";
+            row.appendChild(empty);
+          } else {
+            names.forEach((name) => {
+              const meta = getTextureMeta(name);
+              const card = document.createElement("div");
+              card.className = "tex-card";
+
+              const img = document.createElement("img");
+              img.src = `/texture-preview/${encodeTexturePath(name)}`;
+              img.alt = meta.nombre;
+              img.title = meta.nombre;
+              img.className = "tex-thumb";
+
+              const copy = document.createElement("div");
+              copy.className = "tex-card-copy";
+
+              const nameEl = document.createElement("div");
+              nameEl.className = "tex-card-name";
+              nameEl.textContent = meta.nombre;
+
+              const sizeEl = document.createElement("div");
+              sizeEl.className = "tex-card-size";
+              sizeEl.textContent =
+                textureDimensionsLabel(name) || "Medidas no indicadas";
+
+              const pathEl = document.createElement("div");
+              pathEl.className = "tex-card-path";
+              pathEl.textContent = textureFilename(name);
+
+              card.addEventListener("click", () => {
+                document
+                  .querySelectorAll(".tex-card")
+                  .forEach((c) => c.classList.remove("active"));
+                card.classList.add("active");
+                selectedTextureName = name;
+                statusEl.textContent = `Textura seleccionada: ${meta.nombre}`;
+              });
+
+              card.appendChild(img);
+              copy.appendChild(nameEl);
+              copy.appendChild(sizeEl);
+              copy.appendChild(pathEl);
+              card.appendChild(copy);
+              row.appendChild(card);
+            });
+          }
+
+          section.appendChild(row);
+          texGallery.appendChild(section);
+        });
+      }
+
+      async function buildTextureGallery() {
+        texGallery.innerHTML = "";
+        selectedTextureName = null;
+        try {
+          const res = await fetch("/textures");
+          const data = await res.json();
+          if (!res.ok)
+            throw new Error(data.detail || "No se pudieron cargar texturas");
+
+          allTextureNames = Array.isArray(data.textures) ? data.textures : [];
+          renderTextureGallery();
+        } catch (err) {
+          statusEl.textContent = `Error texturas: ${err.message}`;
+        }
+      }
+
+      async function reloadCanvas(filename, url) {
+        currentFilename = filename;
+        const img = new Image();
+        img.src = url + "?t=" + Date.now();
+        await new Promise((res, rej) => {
+          img.onload = res;
+          img.onerror = rej;
+        });
+        canvas.width = img.naturalWidth;
+        canvas.height = img.naturalHeight;
+        ctx.drawImage(img, 0, 0);
+        originalImageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
+        selectedMasks.clear();
+        hoveredMask = 0;
+        setEditorHasImage(true);
+        redraw();
+      }
+
+      async function loadLabelMapForOwner(ownerFilename) {
+        const labelImg = new Image();
+        labelImg.src = `/masks/${encodeURIComponent(ownerFilename)}?t=${Date.now()}`;
+        await new Promise((resolve) => {
+          labelImg.onload = resolve;
+          labelImg.onerror = resolve;
+        });
+        if (!labelImg.naturalWidth) return false;
+
+        const off = document.createElement("canvas");
+        off.width = canvas.width;
+        off.height = canvas.height;
+        const offCtx = off.getContext("2d");
+        offCtx.drawImage(labelImg, 0, 0, off.width, off.height);
+        labelData = offCtx.getImageData(0, 0, off.width, off.height);
+        try {
+          buildMaskDebugList(ownerFilename);
+          loadSavedMasks(ownerFilename);
+        } catch (e) {
+          /* ignore */
+        }
+        return true;
+      }
+
+      async function runAutoAdaptiveSegmentation(baseFilename) {
+        const targetFilename = String(baseFilename || currentFilename || "");
+        if (!targetFilename) return;
+
+        segLog("log", "Iniciando segmentacion auto-adaptiva", {
+          targetFilename,
+        });
+
+        statusEl.textContent =
+          "Auto-analizando escena y ajustando segmentacion...";
+        const payload = {
+          filename: targetFilename,
+          priority: "balanced",
+          scene_hint: "auto",
+          exterior_target: "wall",
+          semantic_keywords: [
+            "building",
+            "wall",
+            "facade",
+            "house",
+            "roof",
+            "window",
+            "door",
+          ],
+        };
+
+        const res = await fetch("/segment_adaptive", {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify(payload),
+        });
+        const data = await res.json();
+        if (!res.ok) {
+          segLog("error", "Fallo segmentacion auto-adaptiva", data);
+          throw new Error(
+            data.detail || data.message || "Auto adaptive segmentation failed",
+          );
+        }
+
+        segLog("log", "Segmentacion auto-adaptiva completada", {
+          scene_type: data.scene_type,
+          filename: data.filename,
+          recommended_mask_index: data.recommended_mask_index,
+        });
+
+        if (data.filename && data.filename !== currentFilename) {
+          await reloadCanvas(
+            data.filename,
+            `/image/${encodeURIComponent(data.filename)}`,
+          );
+        }
+
+        const owner =
+          data.original_filename_for_apply || data.filename || targetFilename;
+        if (owner) {
+          await loadLabelMapForOwner(owner);
+          originalFilename = owner;
+        }
+
+        selectedMasks.clear();
+        let suggested = null;
+        if (
+          Array.isArray(data.exterior_mask_suggestions) &&
+          data.exterior_mask_suggestions.length
+        ) {
+          suggested = Number(data.exterior_mask_suggestions[0].mask_index || 0);
+        } else if (
+          Array.isArray(data.interior_mask_suggestions) &&
+          data.interior_mask_suggestions.length
+        ) {
+          suggested = Number(data.interior_mask_suggestions[0].mask_index || 0);
+        } else if (Number.isFinite(data.recommended_mask_index)) {
+          suggested = Number(data.recommended_mask_index);
+        }
+
+        if (suggested && suggested > 0) {
+          selectedMasks.add(suggested);
+        }
+
+        redraw();
+        actionsBar.classList.add("visible");
+        await buildTextureGallery();
+        const sceneType = String(data.scene_type || "desconocida");
+        statusEl.textContent = suggested
+          ? `Auto ${sceneType}: mascara ${suggested} preseleccionada.`
+          : `Auto ${sceneType}: segmentacion lista, selecciona una mascara.`;
+      }
+
+      function exteriorKeywordsArray() {
+        return String(extKeywordsEl.value || "")
+          .split(",")
+          .map((s) => s.trim())
+          .filter(Boolean);
+      }
+
+      async function runExteriorWorkflow(mode) {
+        if (!currentFilename) {
+          statusEl.textContent = "Sube y segmenta una imagen primero.";
+          return;
+        }
+
+        const endpoint =
+          mode === "segment" ? "/segment_adaptive" : "/analyze_scene";
+        const payload = {
+          filename: currentFilename,
+          priority: String(extPriorityEl.value || "balanced"),
+          scene_hint: "exterior",
+          top_k: Number(extTopKEl.value || 8),
+          exterior_target: String(extTargetEl.value || "wall"),
+          semantic_keywords: exteriorKeywordsArray(),
+          min_area_ratio: Number(extMinAreaEl.value || 0.01),
+          max_area_ratio: Number(extMaxAreaEl.value || 0.85),
+        };
+
+        extAnalyzeBtn.disabled = true;
+        extSegmentBtn.disabled = true;
+        statusEl.textContent =
+          mode === "segment"
+            ? "Segmentando exterior..."
+            : "Analizando exterior...";
+        try {
+          const res = await fetch(endpoint, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify(payload),
+          });
+          const data = await res.json();
+          if (!res.ok)
+            throw new Error(
+              data.detail || data.message || "Exterior workflow failed",
+            );
+
+          const owner =
+            data.original_filename_for_apply ||
+            data.filename ||
+            originalFilename ||
+            currentFilename;
+          if (data.filename && data.filename !== currentFilename) {
+            await reloadCanvas(
+              data.filename,
+              `/image/${encodeURIComponent(data.filename)}`,
+            );
+          }
+          if (owner) {
+            await loadLabelMapForOwner(owner);
+            originalFilename = owner;
+          }
+
+          selectedMasks.clear();
+          let suggested = null;
+          if (
+            Array.isArray(data.exterior_mask_suggestions) &&
+            data.exterior_mask_suggestions.length
+          ) {
+            suggested = Number(
+              data.exterior_mask_suggestions[0].mask_index || 0,
+            );
+          } else if (Number.isFinite(data.recommended_mask_index)) {
+            suggested = Number(data.recommended_mask_index);
+          }
+          if (suggested && suggested > 0) {
+            selectedMasks.add(suggested);
+          }
+
+          redraw();
+          actionsBar.classList.add("visible");
+          await buildTextureGallery();
+          if (suggested) {
+            statusEl.textContent = `Exterior listo. Mascara sugerida ${suggested}.`;
+          } else {
+            statusEl.textContent =
+              "Exterior listo. Selecciona una mascara para aplicar textura.";
+          }
+        } catch (err) {
+          statusEl.textContent = `Error: ${err.message}`;
+        } finally {
+          extAnalyzeBtn.disabled = false;
+          extSegmentBtn.disabled = false;
+        }
+      }
+
+      function hslToRgb(h, s, l) {
+        const c = (1 - Math.abs(2 * l - 1)) * s;
+        const x = c * (1 - Math.abs(((h / 60) % 2) - 1));
+        const m = l - c / 2;
+        let r, g, b;
+        if (h < 60) [r, g, b] = [c, x, 0];
+        else if (h < 120) [r, g, b] = [x, c, 0];
+        else if (h < 180) [r, g, b] = [0, c, x];
+        else if (h < 240) [r, g, b] = [0, x, c];
+        else if (h < 300) [r, g, b] = [x, 0, c];
+        else [r, g, b] = [c, 0, x];
+        return [
+          Math.round((r + m) * 255),
+          Math.round((g + m) * 255),
+          Math.round((b + m) * 255),
+        ];
+      }
+
+      function maskColor(idx) {
+        return hslToRgb((idx * 137.508) % 360, 0.85, 0.55);
+      }
+
+      function getCanvasPos(e) {
+        const rect = canvas.getBoundingClientRect();
+        return {
+          x: Math.floor(((e.clientX - rect.left) * canvas.width) / rect.width),
+          y: Math.floor(((e.clientY - rect.top) * canvas.height) / rect.height),
+        };
+      }
+
+      function getLabelAt(x, y) {
+        if (
+          !labelData ||
+          x < 0 ||
+          y < 0 ||
+          x >= canvas.width ||
+          y >= canvas.height
+        )
+          return 0;
+        return labelData.data[(y * canvas.width + x) * 4];
+      }
+
+      function redraw() {
+        if (!originalImageData) return;
+        const imgData = new ImageData(
+          new Uint8ClampedArray(originalImageData.data),
+          originalImageData.width,
+          originalImageData.height,
+        );
+        if (labelData && (hoveredMask || selectedMasks.size)) {
+          const d = imgData.data;
+          const ld = labelData.data;
+          for (let i = 0; i < d.length; i += 4) {
+            const mi = ld[i];
+            if (!mi) continue;
+            const sel = selectedMasks.has(mi);
+            const hov = mi === hoveredMask;
+            if (!sel && !hov) continue;
+            let r, g, b, a;
+            if (sel) {
+              [r, g, b] = maskColor(mi);
+              a = 0.5;
+            } else {
+              [r, g, b] = [255, 255, 255];
+              a = 0.2;
+            }
+            d[i] = d[i] * (1 - a) + r * a;
+            d[i + 1] = d[i + 1] * (1 - a) + g * a;
+            d[i + 2] = d[i + 2] * (1 - a) + b * a;
+          }
+        }
+        ctx.putImageData(imgData, 0, 0);
+      }
+
+      canvas.addEventListener("mousemove", (e) => {
+        const { x, y } = getCanvasPos(e);
+        const mi = getLabelAt(x, y);
+        if (mi !== hoveredMask) {
+          hoveredMask = mi;
+          statusEl.textContent = mi
+            ? `Segment ${mi} - click to select (${selectedMasks.size} selected)`
+            : `${selectedMasks.size} selected`;
+          redraw();
+        }
+      });
+
+      canvas.addEventListener("mouseleave", () => {
+        hoveredMask = 0;
+        redraw();
+      });
+
+      canvas.addEventListener("click", (e) => {
+        const { x, y } = getCanvasPos(e);
+        const mi = getLabelAt(x, y);
+        if (!mi) return;
+        if (selectedMasks.has(mi)) selectedMasks.delete(mi);
+        else selectedMasks.add(mi);
+        statusEl.textContent = `${selectedMasks.size} segment(s) selected`;
+        redraw();
+      });
+
+      texApplyBtn.addEventListener("click", async () => {
+        if (!selectedMasks.size) {
+          statusEl.textContent = "Selecciona un segmento primero.";
+          return;
+        }
+        if (!currentFilename) {
+          statusEl.textContent = "Sube una imagen primero.";
+          return;
+        }
+        if (!selectedTextureName) {
+          statusEl.textContent = "Selecciona una textura local.";
+          return;
+        }
+
+        const appliedMaskIndices = [...selectedMasks];
+
+        texApplyBtn.disabled = true;
+        statusEl.textContent = `Aplicando textura a ${selectedMasks.size} segmento(s)...`;
+        try {
+          const res = await fetch("/apply_texture", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({
+              filename: currentFilename,
+              mask_indices: appliedMaskIndices,
+              texture_name: selectedTextureName,
+              direction_mode: "auto",
+              angle_degrees: 0,
+              original_filename:
+                originalFilename || textureHistory[0] || currentFilename,
+              clear_mask_before_apply: !!document.getElementById(
+                "clear-mask-checkbox",
+              ).checked,
+            }),
+          });
+          const d = await res.json();
+          if (!res.ok) throw new Error(d.detail || "Apply texture failed");
+          currentFilename = d.output_filename;
+          await reloadCanvas(d.output_filename, d.output_url);
+          textureHistory.push(d.output_filename);
+          appliedTextureHistory.push({
+            texture_name: textureDisplayName(selectedTextureName),
+            mask_indices: appliedMaskIndices,
+            output_filename: d.output_filename,
+          });
+          syncTextureHistoryButtons();
+          renderAppliedTextureHistory();
+          statusEl.textContent = `Textura aplicada (auto): ${d.surface_type || "generic"} | realistic | scene-aware.`;
+        } catch (err) {
+          statusEl.textContent = `Error: ${err.message}`;
+        } finally {
+          texApplyBtn.disabled = false;
+        }
+      });
+
+      extAnalyzeBtn.addEventListener("click", async () => {
+        await runExteriorWorkflow("analyze");
+      });
+
+      extSegmentBtn.addEventListener("click", async () => {
+        await runExteriorWorkflow("segment");
+      });
+
+      texUndoBtn.addEventListener("click", async () => {
+        if (textureHistory.length <= 1) {
+          statusEl.textContent = "No hay una textura previa para deshacer.";
+          return;
+        }
+        texUndoBtn.disabled = true;
+        texResetBtn.disabled = true;
+        try {
+          textureHistory.pop();
+          if (appliedTextureHistory.length) appliedTextureHistory.pop();
+          const previousFilename = textureHistory[textureHistory.length - 1];
+          await reloadCanvas(
+            previousFilename,
+            `/image/${encodeURIComponent(previousFilename)}`,
+          );
+          syncTextureHistoryButtons();
+          renderAppliedTextureHistory();
+          statusEl.textContent = "Ultima textura revertida.";
+        } catch (err) {
+          statusEl.textContent = `Error: ${err.message}`;
+        } finally {
+          syncTextureHistoryButtons();
+        }
+      });
+
+      texResetBtn.addEventListener("click", async () => {
+        if (!textureHistory.length) {
+          statusEl.textContent = "No hay imagen para restaurar.";
+          return;
+        }
+        texUndoBtn.disabled = true;
+        texResetBtn.disabled = true;
+        try {
+          const baseFilename = textureHistory[0];
+          textureHistory = [baseFilename];
+          appliedTextureHistory = [];
+          await reloadCanvas(
+            baseFilename,
+            `/image/${encodeURIComponent(baseFilename)}`,
+          );
+          syncTextureHistoryButtons();
+          renderAppliedTextureHistory();
+          statusEl.textContent = "Texturas reiniciadas al estado original.";
+        } catch (err) {
+          statusEl.textContent = `Error: ${err.message}`;
+        } finally {
+          syncTextureHistoryButtons();
+        }
+      });
+
+      downloadBtn.addEventListener("click", async () => {
+        if (textureHistory.length <= 1) {
+          statusEl.textContent = "Aplica una textura antes de descargar.";
+          return;
+        }
+        downloadBtn.disabled = true;
+        try {
+          const blob = await getCurrentImageBlob();
+          const fileName = currentFilename || `edited_${Date.now()}.jpg`;
+          const blobUrl = URL.createObjectURL(blob);
+          const a = document.createElement("a");
+          a.href = blobUrl;
+          a.download = fileName;
+          document.body.appendChild(a);
+          a.click();
+          a.remove();
+          URL.revokeObjectURL(blobUrl);
+          statusEl.textContent = "Imagen descargada.";
+        } catch (err) {
+          statusEl.textContent = `Error: ${err.message}`;
+        } finally {
+          syncTextureHistoryButtons();
+        }
+      });
+
+      shareBtn.addEventListener("click", async () => {
+        if (textureHistory.length <= 1) {
+          statusEl.textContent = "Aplica una textura antes de compartir.";
+          return;
+        }
+        if (!navigator.share) {
+          statusEl.textContent = "Share no disponible en este navegador.";
+          return;
+        }
+
+        shareBtn.disabled = true;
+        try {
+          const blob = await getCurrentImageBlob();
+          const fileName = currentFilename || `edited_${Date.now()}.jpg`;
+          const file = new File([blob], fileName, {
+            type: blob.type || "image/jpeg",
+          });
+
+          if (navigator.canShare && !navigator.canShare({ files: [file] })) {
+            throw new Error("El dispositivo no soporta compartir archivos.");
+          }
+
+          await navigator.share({
+            files: [file],
+            title: "HyperReality",
+            text: "Edited texture preview",
+          });
+          statusEl.textContent = "Imagen compartida.";
+        } catch (err) {
+          if (err && err.name === "AbortError") {
+            statusEl.textContent = "Compartir cancelado.";
+          } else {
+            statusEl.textContent = `Error: ${err.message}`;
+          }
+        } finally {
+          syncTextureHistoryButtons();
+        }
+      });
+
+      async function loadSegmentedResult(data) {
+        segLog("log", "Cargando resultado segmentado en canvas", {
+          filename: data.filename,
+          mask_count: data.mask_count,
+        });
+        selectedMasks.clear();
+        hoveredMask = 0;
+
+        const img = new Image();
+        img.src = `/image/${encodeURIComponent(data.filename)}`;
+        await new Promise((resolve, reject) => {
+          img.onload = resolve;
+          img.onerror = reject;
+        });
+
+        canvas.width = img.naturalWidth;
+        canvas.height = img.naturalHeight;
+        ctx.drawImage(img, 0, 0);
+        originalImageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
+
+        const labelImg = new Image();
+        labelImg.src = `/masks/${encodeURIComponent(data.filename)}`;
+        await new Promise((resolve) => {
+          labelImg.onload = resolve;
+          labelImg.onerror = resolve;
+        });
+
+        if (labelImg.naturalWidth) {
+          const off = document.createElement("canvas");
+          off.width = canvas.width;
+          off.height = canvas.height;
+          const offCtx = off.getContext("2d");
+          offCtx.drawImage(labelImg, 0, 0);
+          labelData = offCtx.getImageData(0, 0, off.width, off.height);
+          try {
+            buildMaskDebugList(data.filename);
+            loadSavedMasks(data.filename);
+          } catch (e) {}
+        }
+
+        setEditorHasImage(true);
+        currentFilename = data.filename;
+        originalFilename = data.filename;
+        textureHistory = [data.filename];
+        appliedTextureHistory = [];
+        syncTextureHistoryButtons();
+        renderAppliedTextureHistory();
+        actionsBar.classList.add("visible");
+        await buildTextureGallery();
+        statusEl.textContent = `${data.mask_count} segments - hover to explore, click to select`;
+        setLoadingOverlay(false);
+        segLog("log", "Resultado segmentado cargado correctamente", {
+          currentFilename,
+          originalFilename,
+        });
+      }
+
+      // --- Mask debug helpers (localStorage + preview) ---
+      function buildMaskDebugList(owner) {
+        owner = owner || originalFilename || currentFilename;
+        const container = document.getElementById("mask-debug-list");
+        container.innerHTML = "";
+        if (!labelData) {
+          container.textContent = "No hay label map cargado.";
+          return;
+        }
+        const w = labelData.width,
+          h = labelData.height;
+        const ids = new Set();
+        for (let i = 0; i < labelData.data.length; i += 4) {
+          const id = labelData.data[i];
+          if (id) ids.add(id);
+        }
+        const idArr = Array.from(ids)
+          .filter((x) => x > 0)
+          .sort((a, b) => a - b);
+        if (!idArr.length) {
+          container.textContent = "No hay máscaras.";
+          return;
+        }
+
+        const pixelCounts = {};
+        const bboxes = {};
+        idArr.forEach((id) => {
+          pixelCounts[id] = 0;
+          bboxes[id] = { minX: w, minY: h, maxX: 0, maxY: 0 };
+        });
+
+        for (let y = 0; y < h; y++) {
+          for (let x = 0; x < w; x++) {
+            const idx = (y * w + x) * 4;
+            const lid = labelData.data[idx];
+            if (!lid) continue;
+            pixelCounts[lid] = (pixelCounts[lid] || 0) + 1;
+            const bb = bboxes[lid];
+            if (x < bb.minX) bb.minX = x;
+            if (y < bb.minY) bb.minY = y;
+            if (x > bb.maxX) bb.maxX = x;
+            if (y > bb.maxY) bb.maxY = y;
+          }
+        }
+
+        idArr.forEach((id) => {
+          const area = pixelCounts[id] || 0;
+          const bb = bboxes[id];
+          const boxW = Math.max(1, bb.maxX - bb.minX + 1);
+          const boxH = Math.max(1, bb.maxY - bb.minY + 1);
+
+          const card = document.createElement("div");
+          card.style =
+            "display:flex;align-items:center;gap:0.5rem;padding:0.25rem;border:1px solid #222;border-radius:6px;background:#0f0f0f;";
+
+          const preview = document.createElement("canvas");
+          preview.width = 120;
+          preview.height = Math.max(40, Math.round(120 * (boxH / boxW)));
+
+          const off = document.createElement("canvas");
+          off.width = boxW;
+          off.height = boxH;
+          const offCtx = off.getContext("2d");
+          const offImg = offCtx.createImageData(boxW, boxH);
+          for (let yy = 0; yy < boxH; yy++) {
+            for (let xx = 0; xx < boxW; xx++) {
+              const sx = bb.minX + xx;
+              const sy = bb.minY + yy;
+              const sidx = (sy * w + sx) * 4;
+              const lid = labelData.data[sidx];
+              const di = (yy * boxW + xx) * 4;
+              if (lid === id) {
+                offImg.data[di] = 255;
+                offImg.data[di + 1] = 255;
+                offImg.data[di + 2] = 255;
+                offImg.data[di + 3] = 255;
+              } else {
+                offImg.data[di] = 0;
+                offImg.data[di + 1] = 0;
+                offImg.data[di + 2] = 0;
+                offImg.data[di + 3] = 0;
+              }
+            }
+          }
+          offCtx.putImageData(offImg, 0, 0);
+
+          const pctx = preview.getContext("2d");
+          pctx.fillStyle = "#000";
+          pctx.fillRect(0, 0, preview.width, preview.height);
+          pctx.drawImage(
+            off,
+            0,
+            0,
+            boxW,
+            boxH,
+            0,
+            0,
+            preview.width,
+            preview.height,
+          );
+
+          const info = document.createElement("div");
+          info.style = "font-size:0.85rem;color:#ddd;";
+          info.innerHTML = `<div>ID ${id} | area ${area}</div><div style="font-size:0.75rem;color:#999">bbox ${bb.minX},${bb.minY} ${boxW}x${boxH}</div>`;
+
+          const btnSel = document.createElement("button");
+          btnSel.className = "action-btn";
+          btnSel.style.background = "#335d85";
+          btnSel.textContent = "Seleccionar";
+          btnSel.onclick = () => {
+            if (selectedMasks.has(id)) selectedMasks.delete(id);
+            else selectedMasks.add(id);
+            redraw();
+            statusEl.textContent = `${selectedMasks.size} segment(s) selected`;
+          };
+
+          const nameInput = document.createElement("input");
+          nameInput.placeholder = "nombre";
+          nameInput.style =
+            "margin-left:6px;padding:4px;border-radius:4px;background:#111;color:#ddd;border:1px solid #333;";
+          const btnSave = document.createElement("button");
+          btnSave.className = "action-btn";
+          btnSave.style.background = "#2a6";
+          btnSave.textContent = "Guardar";
+          btnSave.onclick = () => {
+            const thumb = preview.toDataURL("image/png");
+            const name = nameInput.value || "";
+            saveMaskToLocal(
+              owner || originalFilename || currentFilename,
+              id,
+              thumb,
+              { minX: bb.minX, minY: bb.minY, maxX: bb.maxX, maxY: bb.maxY },
+              area,
+              name,
+            );
+            statusEl.textContent = `Mascara ${id} guardada localmente.`;
+          };
+
+          const btnDownload = document.createElement("button");
+          btnDownload.className = "action-btn";
+          btnDownload.style.background = "#4f5b9d";
+          btnDownload.textContent = "Descargar";
+          btnDownload.onclick = () => {
+            const a = document.createElement("a");
+            a.href = preview.toDataURL("image/png");
+            a.download = `${owner || originalFilename || currentFilename || "mask"}_${id}.png`;
+            document.body.appendChild(a);
+            a.click();
+            a.remove();
+          };
+
+          card.appendChild(preview);
+          card.appendChild(info);
+          card.appendChild(btnSel);
+          card.appendChild(nameInput);
+          card.appendChild(btnSave);
+          card.appendChild(btnDownload);
+          container.appendChild(card);
+        });
+      }
+
+      function saveMaskToLocal(owner, id, thumb, bbox, area, name) {
+        const key = "hyper_masks_" + (owner || "global");
+        let arr = [];
+        try {
+          arr = JSON.parse(localStorage.getItem(key) || "[]");
+        } catch (e) {
+          arr = [];
+        }
+        arr.push({
+          maskIndex: id,
+          name: name || "",
+          thumb: thumb,
+          bbox: bbox,
+          area: area,
+          owner: owner,
+        });
+        localStorage.setItem(key, JSON.stringify(arr));
+        loadSavedMasks(owner);
+      }
+
+      function loadSavedMasks(owner) {
+        const key = "hyper_masks_" + (owner || "global");
+        const list = document.getElementById("mask-debug-local-list");
+        list.innerHTML = "";
+        let arr = [];
+        try {
+          arr = JSON.parse(localStorage.getItem(key) || "[]");
+        } catch (e) {
+          arr = [];
+        }
+        if (!arr.length) {
+          list.textContent = "No guardadas.";
+          return;
+        }
+        arr.forEach((item, idx) => {
+          const card = document.createElement("div");
+          card.style =
+            "display:flex;align-items:center;gap:0.5rem;padding:0.25rem;border:1px solid #222;border-radius:6px;background:#0f0f0f;";
+          const img = document.createElement("img");
+          img.src = item.thumb;
+          img.width = 120;
+          img.height = 80;
+          img.style = "object-fit:cover;border-radius:4px;";
+          const info = document.createElement("div");
+          info.style = "font-size:0.85rem;color:#ddd;";
+          info.innerHTML = `<div>${item.name || ""} (ID ${item.maskIndex})</div><div style="font-size:0.75rem;color:#999">area:${item.area}</div>`;
+          const btnApply = document.createElement("button");
+          btnApply.className = "action-btn";
+          btnApply.style.background = "#335d85";
+          btnApply.textContent = "Seleccionar";
+          btnApply.onclick = () => {
+            if (labelData) {
+              selectedMasks.add(item.maskIndex);
+              redraw();
+              statusEl.textContent = `Mascara ${item.maskIndex} seleccionada.`;
+            } else {
+              statusEl.textContent = "No hay label map cargado.";
+            }
+          };
+          const btnDel = document.createElement("button");
+          btnDel.className = "action-btn";
+          btnDel.style.background = "#a33";
+          btnDel.textContent = "Borrar";
+          btnDel.onclick = () => {
+            arr.splice(idx, 1);
+            localStorage.setItem(key, JSON.stringify(arr));
+            loadSavedMasks(owner);
+          };
+          card.appendChild(img);
+          card.appendChild(info);
+          card.appendChild(btnApply);
+          card.appendChild(btnDel);
+          list.appendChild(card);
+        });
+      }
+
+      document
+        .getElementById("mask-debug-refresh")
+        .addEventListener("click", () =>
+          buildMaskDebugList(originalFilename || currentFilename),
+        );
+      document
+        .getElementById("mask-debug-load-local")
+        .addEventListener("click", () =>
+          loadSavedMasks(originalFilename || currentFilename),
+        );
+      document
+        .getElementById("mask-debug-clear-local")
+        .addEventListener("click", () => {
+          localStorage.removeItem(
+            "hyper_masks_" + (originalFilename || currentFilename || "global"),
+          );
+          loadSavedMasks(originalFilename || currentFilename);
+          statusEl.textContent = "Local masks cleared";
+        });
+
+      async function pollUploadJob(jobId) {
+        segLog("log", "Inicio de polling del job de segmentacion", { jobId });
+        const MAX_POLLS = 300;
+        for (let i = 0; i < MAX_POLLS; i++) {
+          await new Promise((r) => setTimeout(r, 1000));
+          const res = await fetch(`/jobs/${jobId}`);
+          const data = await res.json();
+
+          if (!res.ok) {
+            segLog("error", "Error consultando estado del job", {
+              jobId,
+              data,
+            });
+            throw new Error(data.detail || "Status polling failed");
+          }
+
+          if (data.status === "done") {
+            segLog("log", "Job de segmentacion completado", {
+              jobId,
+              filename: data.filename,
+              mask_count: data.mask_count,
+            });
+            await loadSegmentedResult(data);
+            setLoadingOverlay(false);
+            segLog(
+              "log",
+              "Flujo de carga finalizado sin post-procesado adicional",
+              {
+                jobId,
+                filename: data.filename,
+              },
+            );
+            return;
+          }
+
+          if (data.status === "failed" || data.status === "timeout") {
+            segLog("error", "Job de segmentacion finalizo con error/timeout", {
+              jobId,
+              status: data.status,
+              message: data.message,
+            });
+            throw new Error(data.message || data.status);
+          }
+
+          const stage = data.stage || "processing";
+          const progress = Number.isFinite(data.progress) ? data.progress : 0;
+          const etaText = Number.isFinite(data.eta_seconds)
+            ? ` | ETA ~${Math.max(0, Math.ceil(data.eta_seconds))}s`
+            : "";
+          setLoadingOverlay(
+            true,
+            "Procesando imagen...",
+            `${stage} - ${progress}%${etaText}`,
+          );
+          statusEl.textContent = `${stage} - ${progress}%${etaText}`;
+          segLog("log", "Progreso de segmentacion", {
+            jobId,
+            poll: i + 1,
+            stage,
+            progress,
+            eta_seconds: data.eta_seconds,
+          });
+        }
+
+        segLog("error", "Timeout de polling alcanzado", { jobId });
+        throw new Error("Segmentation timeout in client polling");
+      }
+
+      async function startUploadProcess(fileFromEvent) {
+        if (isUploading) {
+          segLog(
+            "warn",
+            "Se ignoro inicio de upload porque ya hay uno en curso",
+          );
+          return;
+        }
+
+        const fileToUpload =
+          fileFromEvent ||
+          selectedUploadFile ||
+          (fileInput.files && fileInput.files[0]);
+        if (!fileToUpload) {
+          segLog("warn", "Intento de upload sin archivo seleccionado");
+          statusEl.textContent = "Selecciona una imagen primero.";
+          return;
+        }
+
+        segLog("log", "Iniciando upload para segmentacion", {
+          name: fileToUpload.name,
+          size: fileToUpload.size,
+          type: fileToUpload.type,
+        });
+
+        isUploading = true;
+        uploadBtn.disabled = true;
+        statusEl.textContent = "Uploading & segmenting...";
+        setLoadingOverlay(
+          true,
+          "Procesando imagen...",
+          "Subiendo archivo y preparando segmentacion.",
+        );
+        const formData = new FormData();
+        formData.append("file", fileToUpload);
+        try {
+          const res = await fetch("/upload_async", {
+            method: "POST",
+            body: formData,
+          });
+          const data = await res.json();
+          if (!res.ok || !data.job_id) {
+            segLog("error", "Fallo al crear job de upload_async", data);
+            throw new Error(data.detail || data.message || "Upload failed");
+          }
+          segLog("log", "Job de segmentacion creado", { job_id: data.job_id });
+          await pollUploadJob(data.job_id);
+        } catch (err) {
+          segLog("error", "Error general en startUploadProcess", {
+            error: err && err.message ? err.message : String(err),
+          });
+          statusEl.textContent = `Error: ${err.message}`;
+        } finally {
+          isUploading = false;
+          uploadBtn.disabled = !selectedUploadFile;
+          setLoadingOverlay(false);
+          segLog("log", "Fin del flujo de upload/segmentacion", {
+            hasSelectedUploadFile: !!selectedUploadFile,
+          });
+        }
+      }
+
+      function queueAutoUpload(file) {
+        if (!file) return;
+        if (autoUploadTimer) {
+          clearTimeout(autoUploadTimer);
+          autoUploadTimer = null;
+        }
+        autoUploadTimer = setTimeout(() => {
+          autoUploadTimer = null;
+          startUploadProcess(file);
+        }, 120);
+      }
+
+      uploadBtn.addEventListener("click", async () => {
+        await startUploadProcess();
+      });
+
+      emptyUploadBtn.addEventListener("click", () => {
+        fileInput.click();
+      });
+
+      if (emptyStateRightEl) {
+        emptyStateRightEl.addEventListener("click", () => {
+          fileInput.click();
+        });
+
+        emptyStateRightEl.addEventListener("dragover", (e) => {
+          e.preventDefault();
+          emptyStateRightEl.classList.add("drop-active");
+        });
+
+        emptyStateRightEl.addEventListener("dragleave", () => {
+          emptyStateRightEl.classList.remove("drop-active");
+        });
+
+        emptyStateRightEl.addEventListener("drop", (e) => {
+          e.preventDefault();
+          emptyStateRightEl.classList.remove("drop-active");
+          const file =
+            e.dataTransfer && e.dataTransfer.files && e.dataTransfer.files[0]
+              ? e.dataTransfer.files[0]
+              : null;
+          if (!file) return;
+          updateUploadSelection(file);
+          try {
+            const dt = new DataTransfer();
+            dt.items.add(file);
+            fileInput.files = dt.files;
+          } catch (err) {
+            // Some browsers may block direct FileList assignment.
+          }
+          queueAutoUpload(file);
+        });
+      }
+
+      hideLegacyUploadStrip();
+      applyFrontendDebugMode();
+      setEditorHasImage(false);
+
+      fileInput.addEventListener("change", () => {
+        const file =
+          fileInput.files && fileInput.files[0] ? fileInput.files[0] : null;
+        updateUploadSelection(file);
+        queueAutoUpload(file);
+      });
+
+      uploadDropzone.addEventListener("dragover", (e) => {
+        e.preventDefault();
+        uploadDropzone.classList.add("drop-active");
+      });
+
+      uploadDropzone.addEventListener("dragleave", () => {
+        uploadDropzone.classList.remove("drop-active");
+      });
+
+      uploadDropzone.addEventListener("drop", (e) => {
+        e.preventDefault();
+        uploadDropzone.classList.remove("drop-active");
+        const file =
+          e.dataTransfer && e.dataTransfer.files && e.dataTransfer.files[0]
+            ? e.dataTransfer.files[0]
+            : null;
+        if (!file) return;
+        updateUploadSelection(file);
+        try {
+          const dt = new DataTransfer();
+          dt.items.add(file);
+          fileInput.files = dt.files;
+        } catch (err) {
+          // Some browsers may block direct FileList assignment.
+        }
+        queueAutoUpload(file);
+      });
+    </script>
+  </body>
+</html>
diff --git a/backend/texturas/Texture_wpc_deck/DECK_gris.png b/backend/texturas/Texture_wpc_deck/DECK_gris.png
new file mode 100644
index 0000000000000000000000000000000000000000..ed4299c88919598daeb0c8f9b28e73bd554b168e
--- /dev/null
+++ b/backend/texturas/Texture_wpc_deck/DECK_gris.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:55daa6f6e902f484bb4e0327609a3aab8ffd8cd45e37a2eb8b0575983ef0b97b
+size 1443643
diff --git a/backend/texturas/Texture_wpc_deck/DECK_madera.png b/backend/texturas/Texture_wpc_deck/DECK_madera.png
new file mode 100644
index 0000000000000000000000000000000000000000..a6b969ba90677ecd7e0702c1626c2200527e821c
--- /dev/null
+++ b/backend/texturas/Texture_wpc_deck/DECK_madera.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:781cd371ee4970775220d90950f3a03d1735b15dc5175eb7c3c338e344607d5b
+size 1954535
diff --git a/backend/texturas/Texture_wpc_deck/DECK_madera_oscuro.png b/backend/texturas/Texture_wpc_deck/DECK_madera_oscuro.png
new file mode 100644
index 0000000000000000000000000000000000000000..605099e14526bd470815f7dd520d7fc02a0c3331
--- /dev/null
+++ b/backend/texturas/Texture_wpc_deck/DECK_madera_oscuro.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aad5dc59e369431186149eaa324c91098037b1a3d4cb258045bcd923897f5843
+size 1876489
diff --git a/backend/visualizador.html b/backend/visualizador.html
index 04397fdc26aee48396941f9ff88c1474733f366f..668b69fdf1bf2d2da49eea2daef7a399f4407444 100644
--- a/backend/visualizador.html
+++ b/backend/visualizador.html
@@ -1,125 +1,125 @@
-<!doctype html>
-<html lang="es">
-  <head>
-    <meta charset="UTF-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Visualizador SaaS fasdfadsf</title>
-    <script
-      src="https://unpkg.com/react@18/umd/react.development.js"
-      crossorigin
-    ></script>
-    <script
-      src="https://unpkg.com/react-dom@18/umd/react-dom.development.js"
-      crossorigin
-    ></script>
-    <script src="https://cdn.tailwindcss.com"></script>
-  </head>
-  <body class="bg-slate-100 text-slate-900">
-    <div
-      id="root"
-      class="min-h-screen flex items-center justify-center p-4"
-    ></div>
-
-    <script>
-      const { useState, useEffect } = React;
-
-      function App() {
-        const [cliente, setCliente] = useState(null);
-        const [error, setError] = useState(null);
-        const [apiKey, setApiKey] = useState(null);
-
-        useEffect(() => {
-          const params = new URLSearchParams(window.location.search);
-          const token = params.get("token");
-
-          if (!token) {
-            setError("No se encontró el parámetro 'token' en la URL.");
-            return;
-          }
-
-          const url = `/config?token=${encodeURIComponent(token)}`;
-
-          fetch(url)
-            .then((res) => {
-              if (!res.ok) {
-                throw new Error("Error al obtener configuración del cliente");
-              }
-              return res.json();
-            })
-            .then((data) => {
-              setApiKey(data.client_id);
-              setCliente(data);
-              return fetch("/session/start", {
-                method: "POST",
-                headers: {
-                  "Content-Type": "application/x-www-form-urlencoded",
-                },
-                body: `token=${encodeURIComponent(token)}`,
-              });
-            })
-            .catch((err) => setError(err.message));
-        }, []);
-
-        const enviarMensaje = () => {
-          if (!cliente) return;
-          window.parent.postMessage(
-            {
-              type: "saas-session-active",
-              nombreCliente: cliente.nombre,
-            },
-            "*",
-          );
-        };
-
-        return React.createElement(
-          "div",
-          {
-            className:
-              "w-full max-w-3xl bg-white rounded-3xl shadow-xl p-8 space-y-6 text-center",
-          },
-          React.createElement(
-            "h1",
-            { className: "text-3xl font-bold text-slate-900" },
-            "Panel de Control:",
-          ),
-          apiKey &&
-            React.createElement(
-              "p",
-              { className: "text-sm text-slate-500" },
-              `API key usada: ${apiKey}`,
-            ),
-          cliente
-            ? React.createElement(
-                "p",
-                { className: "text-xl text-slate-700" },
-                cliente.nombre,
-              )
-            : React.createElement(
-                "p",
-                { className: "text-xl text-slate-500" },
-                error || "Cargando datos...",
-              ),
-          React.createElement(
-            "button",
-            {
-              className:
-                "px-6 py-3 bg-blue-600 text-white rounded-xl shadow hover:bg-blue-700 transition",
-              onClick: enviarMensaje,
-              disabled: !cliente,
-            },
-            "Notificar al sitio padre",
-          ),
-          cliente &&
-            React.createElement(
-              "div",
-              { className: "mt-4 text-sm text-slate-500" },
-              `Color primario: ${cliente.color_primario}`,
-            ),
-        );
-      }
-
-      const root = ReactDOM.createRoot(document.getElementById("root"));
-      root.render(React.createElement(App));
-    </script>
-  </body>
-</html>
+<!doctype html>
+<html lang="es">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>Visualizador SaaS fasdfadsf</title>
+    <script
+      src="https://unpkg.com/react@18/umd/react.development.js"
+      crossorigin
+    ></script>
+    <script
+      src="https://unpkg.com/react-dom@18/umd/react-dom.development.js"
+      crossorigin
+    ></script>
+    <script src="https://cdn.tailwindcss.com"></script>
+  </head>
+  <body class="bg-slate-100 text-slate-900">
+    <div
+      id="root"
+      class="min-h-screen flex items-center justify-center p-4"
+    ></div>
+
+    <script>
+      const { useState, useEffect } = React;
+
+      function App() {
+        const [cliente, setCliente] = useState(null);
+        const [error, setError] = useState(null);
+        const [apiKey, setApiKey] = useState(null);
+
+        useEffect(() => {
+          const params = new URLSearchParams(window.location.search);
+          const token = params.get("token");
+
+          if (!token) {
+            setError("No se encontró el parámetro 'token' en la URL.");
+            return;
+          }
+
+          const url = `/config?token=${encodeURIComponent(token)}`;
+
+          fetch(url)
+            .then((res) => {
+              if (!res.ok) {
+                throw new Error("Error al obtener configuración del cliente");
+              }
+              return res.json();
+            })
+            .then((data) => {
+              setApiKey(data.client_id);
+              setCliente(data);
+              return fetch("/session/start", {
+                method: "POST",
+                headers: {
+                  "Content-Type": "application/x-www-form-urlencoded",
+                },
+                body: `token=${encodeURIComponent(token)}`,
+              });
+            })
+            .catch((err) => setError(err.message));
+        }, []);
+
+        const enviarMensaje = () => {
+          if (!cliente) return;
+          window.parent.postMessage(
+            {
+              type: "saas-session-active",
+              nombreCliente: cliente.nombre,
+            },
+            "*",
+          );
+        };
+
+        return React.createElement(
+          "div",
+          {
+            className:
+              "w-full max-w-3xl bg-white rounded-3xl shadow-xl p-8 space-y-6 text-center",
+          },
+          React.createElement(
+            "h1",
+            { className: "text-3xl font-bold text-slate-900" },
+            "Panel de Control:",
+          ),
+          apiKey &&
+            React.createElement(
+              "p",
+              { className: "text-sm text-slate-500" },
+              `API key usada: ${apiKey}`,
+            ),
+          cliente
+            ? React.createElement(
+                "p",
+                { className: "text-xl text-slate-700" },
+                cliente.nombre,
+              )
+            : React.createElement(
+                "p",
+                { className: "text-xl text-slate-500" },
+                error || "Cargando datos...",
+              ),
+          React.createElement(
+            "button",
+            {
+              className:
+                "px-6 py-3 bg-blue-600 text-white rounded-xl shadow hover:bg-blue-700 transition",
+              onClick: enviarMensaje,
+              disabled: !cliente,
+            },
+            "Notificar al sitio padre",
+          ),
+          cliente &&
+            React.createElement(
+              "div",
+              { className: "mt-4 text-sm text-slate-500" },
+              `Color primario: ${cliente.color_primario}`,
+            ),
+        );
+      }
+
+      const root = ReactDOM.createRoot(document.getElementById("root"));
+      root.render(React.createElement(App));
+    </script>
+  </body>
+</html>
diff --git a/frontend/.gitignore b/frontend/.gitignore
index 4108b33e7b3aae71ade8d7e209a72f99f17c3485..a547bf36d8d11a4f89c59c144f24795749086dd1 100644
--- a/frontend/.gitignore
+++ b/frontend/.gitignore
@@ -1,24 +1,24 @@
-# Logs
-logs
-*.log
-npm-debug.log*
-yarn-debug.log*
-yarn-error.log*
-pnpm-debug.log*
-lerna-debug.log*
-
-node_modules
-dist
-dist-ssr
-*.local
-
-# Editor directories and files
-.vscode/*
-!.vscode/extensions.json
-.idea
-.DS_Store
-*.suo
-*.ntvs*
-*.njsproj
-*.sln
-*.sw?
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
diff --git a/frontend/FRONTEND_DOCUMENTATION.md b/frontend/FRONTEND_DOCUMENTATION.md
index b50f35ce49361c410473644f18c6ff3ad7d0ed5f..100b7ca36d144e890c92178994735a46fe322d42 100644
--- a/frontend/FRONTEND_DOCUMENTATION.md
+++ b/frontend/FRONTEND_DOCUMENTATION.md
@@ -1,250 +1,250 @@
-# Documentación del Frontend
-
-Este documento describe la arquitectura, las rutas, los estados, los hooks y los componentes principales del frontend React + TypeScript ubicado en `frontend/`.
-
----
-
-## 1. Visión general
-
-El frontend está construido con:
-
-- React 19
-- TypeScript
-- Vite
-- React Router DOM
-- Zustand para estado global
-- @tanstack/react-query para consultas asíncronas
-- Tailwind CSS para estilos
-- Arquitectura basada en características (`features`)
-
-La carpeta principal de la aplicación es `frontend/src`.
-
----
-
-## 2. Estructura de carpetas clave
-
-- `src/main.tsx` - punto de entrada, configuración de router y React Query
-- `src/App.tsx` - rutas principales de la aplicación
-- `src/store` - estado global con Zustand
-- `src/api` - cliente y funciones de API centralizadas
-- `src/hooks` - hooks reutilizables del frontend
-- `src/features` - features organizadas por dominio
-- `src/utils` - utilidades compartidas
-- `src/types.ts` - tipos globales de la aplicación
-
----
-
-## 3. Rutas principales
-
-`src/App.tsx` define las rutas:
-
-- `/` → `RoomSetup`
-- `/visualizer` → `RoomVisualizer`
-- `/settings` → `SettingsPage`
-- `*` → redirección a `/`
-
----
-
-## 4. Estado global (Zustand)
-
-`src/store/useAppStore.ts` almacena:
-
-- `previewImage` - URL de la imagen cargada
-- `uploadMessage` - estado de mensaje de subida
-- `openProductId` - producto seleccionado en `RoomVisualizer`
-- `viewMode` - vista actual de productos en el visualizador (`grid` o `list`)
-
-Funciones disponibles:
-
-- `setPreviewImage`
-- `setUploadMessage`
-- `setOpenProductId`
-- `setViewMode`
-- `reset`
-
----
-
-## 5. Cliente API centralizado
-
-`src/api/client.ts` incluye:
-
-- `DEV_API_BASE` y `API_BASE` para la URL del backend
-- `getApiBase` / `buildApiUrl` para construir endpoints
-- `fetchClientConfig` para obtener configuración de cliente
-- `uploadRoomImage` para subir imágenes al servidor
-- `startSession` para iniciar una sesión remota
-
-Esta capa permite mantener la URL del backend en un solo lugar y soportar un token de desarrollo automático.
-
----
-
-## 6. Hooks compartidos
-
-### `src/hooks/useUploadImage.ts`
-
-- Maneja la subida de imágenes al backend
-- Controla `isUploading` y `uploadError`
-- Envuelve `uploadRoomImage` del cliente API
-
----
-
-## 7. Tipos globales
-
-`src/types.ts` declara tipos comunes como:
-
-- `ClientData`
-- `RouteItem`
-- `Product`
-
-El tipo `Product` se usa en el visualizador para productos de catálogo.
-
----
-
-## 8. Feature: Room Setup
-
-### Archivos
-
-- `src/features/roomSetup/RoomSetup.tsx`
-- `src/features/roomSetup/roomSetupHooks.ts`
-- `src/features/roomSetup/RoomSetupComponents.tsx`
-- `src/data/roomSetupData.ts`
-
-### Comportamiento
-
-`RoomSetup` es la página principal donde el usuario puede:
-
-- subir una imagen arrastrando o seleccionando archivo
-- ver una vista previa de la imagen
-- iniciar la navegación hacia el visualizador
-- ver habitaciones de demostración filtrables
-
-### `useRoomSetup`
-
-Este hook abstrae toda la lógica de:
-
-- drag & drop
-- selección de archivos
-- subida de imagen
-- gestión de estados de carga
-- navegación con `useNavigate`
-
-### Componentes auxiliares
-
-- `FilterButton` - botón de filtrado por categoría
-- `RoomCard` - tarjeta de habitación de demostración
-
----
-
-## 9. Feature: Room Visualizer
-
-### Archivos
-
-- `src/features/roomVisualizer/RoomVisualizer.tsx`
-- `src/features/roomVisualizer/roomVisualizerHooks.ts`
-- `src/features/roomVisualizer/roomVisualizerData.ts`
-- `src/features/roomVisualizer/ProductCards.tsx`
-
-### Comportamiento
-
-`RoomVisualizer` muestra:
-
-- la imagen subida por el usuario
-- controles de zoom y arrastre de la imagen
-- lista / grid de productos para aplicar en la habitación
-- selección de producto y detalles asociados
-
-### `useRoomVisualizer`
-
-Extrae la lógica de visualización de productos:
-
-- modo de vista (`grid` / `list`)
-- búsqueda y filtros básicos
-- producto seleccionado
-- manejo de selección de producto
-- agrupación en chunks para renderizar grillas
-
-### Datos de productos
-
-- `roomVisualizerData.ts` contiene el catálogo de productos estáticos usados en la vista.
-
-### Componentes
-
-- `ProductGroupCard` - renderiza un grupo de 3 productos en grid
-- `IndividualProductCard` - renderiza un producto en modo lista
-
----
-
-## 10. Feature: Settings
-
-### Archivo
-
-- `src/features/settings/SettingsPage.tsx`
-
-### Comportamiento
-
-La página de configuración permite al usuario:
-
-- definir la URL base de la API
-- activar / desactivar la lista de rutas en el viewer
-- definir token de desarrollo automático
-
-### Soporte de almacenamiento
-
-`src/utils/settings.ts` gestiona:
-
-- carga de `localStorage`
-- guardado de configuración
-- valores por defecto
-
----
-
-## 11. Componentes comunes
-
-- `src/components/ui/LoadingScreen.tsx` - pantalla de carga reutilizable
-
----
-
-## 12. Flujo principal de la app
-
-1. Usuario entra en `/`
-2. Sube una imagen en `RoomSetup`
-3. Se crea una vista previa y se almacena en Zustand
-4. Se navega a `/visualizer`
-5. `RoomVisualizer` usa la imagen y muestra productos
-6. El usuario filtra, busca y selecciona productos
-7. `SettingsPage` permite ajustar la API y opciones de la app
-
----
-
-## 13. Cómo ejecutar el frontend
-
-Desde `frontend/`:
-
-```bash
-npm install
-npm run dev
-```
-
-Construcción de producción:
-
-```bash
-npm run build
-```
-
----
-
-## 14. Posibles mejoras futuras
-
-- mover `roomVisualizerProducts` a una API real o servicio de datos
-- extraer más componentes presentacionales del visualizador
-- usar React Query para cargar configuración del cliente en lugar de gestión manual
-- añadir tests unitarios para hooks y componentes
-- normalizar rutas y nombres de features
-
----
-
-## 15. Observaciones adicionales
-
-- La base API se controla desde `VITE_API_BASE_URL` o `DEV_API_BASE` en desarrollo.
-- La aplicación usa `queryClient` de React Query, aunque hoy solo se usa para potenciales fetches futuros.
-- El estado global es ligero y se usa principalmente para compartir imagen previa, modo de vista y selección de producto.
+# Documentación del Frontend
+
+Este documento describe la arquitectura, las rutas, los estados, los hooks y los componentes principales del frontend React + TypeScript ubicado en `frontend/`.
+
+---
+
+## 1. Visión general
+
+El frontend está construido con:
+
+- React 19
+- TypeScript
+- Vite
+- React Router DOM
+- Zustand para estado global
+- @tanstack/react-query para consultas asíncronas
+- Tailwind CSS para estilos
+- Arquitectura basada en características (`features`)
+
+La carpeta principal de la aplicación es `frontend/src`.
+
+---
+
+## 2. Estructura de carpetas clave
+
+- `src/main.tsx` - punto de entrada, configuración de router y React Query
+- `src/App.tsx` - rutas principales de la aplicación
+- `src/store` - estado global con Zustand
+- `src/api` - cliente y funciones de API centralizadas
+- `src/hooks` - hooks reutilizables del frontend
+- `src/features` - features organizadas por dominio
+- `src/utils` - utilidades compartidas
+- `src/types.ts` - tipos globales de la aplicación
+
+---
+
+## 3. Rutas principales
+
+`src/App.tsx` define las rutas:
+
+- `/` → `RoomSetup`
+- `/visualizer` → `RoomVisualizer`
+- `/settings` → `SettingsPage`
+- `*` → redirección a `/`
+
+---
+
+## 4. Estado global (Zustand)
+
+`src/store/useAppStore.ts` almacena:
+
+- `previewImage` - URL de la imagen cargada
+- `uploadMessage` - estado de mensaje de subida
+- `openProductId` - producto seleccionado en `RoomVisualizer`
+- `viewMode` - vista actual de productos en el visualizador (`grid` o `list`)
+
+Funciones disponibles:
+
+- `setPreviewImage`
+- `setUploadMessage`
+- `setOpenProductId`
+- `setViewMode`
+- `reset`
+
+---
+
+## 5. Cliente API centralizado
+
+`src/api/client.ts` incluye:
+
+- `DEV_API_BASE` y `API_BASE` para la URL del backend
+- `getApiBase` / `buildApiUrl` para construir endpoints
+- `fetchClientConfig` para obtener configuración de cliente
+- `uploadRoomImage` para subir imágenes al servidor
+- `startSession` para iniciar una sesión remota
+
+Esta capa permite mantener la URL del backend en un solo lugar y soportar un token de desarrollo automático.
+
+---
+
+## 6. Hooks compartidos
+
+### `src/hooks/useUploadImage.ts`
+
+- Maneja la subida de imágenes al backend
+- Controla `isUploading` y `uploadError`
+- Envuelve `uploadRoomImage` del cliente API
+
+---
+
+## 7. Tipos globales
+
+`src/types.ts` declara tipos comunes como:
+
+- `ClientData`
+- `RouteItem`
+- `Product`
+
+El tipo `Product` se usa en el visualizador para productos de catálogo.
+
+---
+
+## 8. Feature: Room Setup
+
+### Archivos
+
+- `src/features/roomSetup/RoomSetup.tsx`
+- `src/features/roomSetup/roomSetupHooks.ts`
+- `src/features/roomSetup/RoomSetupComponents.tsx`
+- `src/data/roomSetupData.ts`
+
+### Comportamiento
+
+`RoomSetup` es la página principal donde el usuario puede:
+
+- subir una imagen arrastrando o seleccionando archivo
+- ver una vista previa de la imagen
+- iniciar la navegación hacia el visualizador
+- ver habitaciones de demostración filtrables
+
+### `useRoomSetup`
+
+Este hook abstrae toda la lógica de:
+
+- drag & drop
+- selección de archivos
+- subida de imagen
+- gestión de estados de carga
+- navegación con `useNavigate`
+
+### Componentes auxiliares
+
+- `FilterButton` - botón de filtrado por categoría
+- `RoomCard` - tarjeta de habitación de demostración
+
+---
+
+## 9. Feature: Room Visualizer
+
+### Archivos
+
+- `src/features/roomVisualizer/RoomVisualizer.tsx`
+- `src/features/roomVisualizer/roomVisualizerHooks.ts`
+- `src/features/roomVisualizer/roomVisualizerData.ts`
+- `src/features/roomVisualizer/ProductCards.tsx`
+
+### Comportamiento
+
+`RoomVisualizer` muestra:
+
+- la imagen subida por el usuario
+- controles de zoom y arrastre de la imagen
+- lista / grid de productos para aplicar en la habitación
+- selección de producto y detalles asociados
+
+### `useRoomVisualizer`
+
+Extrae la lógica de visualización de productos:
+
+- modo de vista (`grid` / `list`)
+- búsqueda y filtros básicos
+- producto seleccionado
+- manejo de selección de producto
+- agrupación en chunks para renderizar grillas
+
+### Datos de productos
+
+- `roomVisualizerData.ts` contiene el catálogo de productos estáticos usados en la vista.
+
+### Componentes
+
+- `ProductGroupCard` - renderiza un grupo de 3 productos en grid
+- `IndividualProductCard` - renderiza un producto en modo lista
+
+---
+
+## 10. Feature: Settings
+
+### Archivo
+
+- `src/features/settings/SettingsPage.tsx`
+
+### Comportamiento
+
+La página de configuración permite al usuario:
+
+- definir la URL base de la API
+- activar / desactivar la lista de rutas en el viewer
+- definir token de desarrollo automático
+
+### Soporte de almacenamiento
+
+`src/utils/settings.ts` gestiona:
+
+- carga de `localStorage`
+- guardado de configuración
+- valores por defecto
+
+---
+
+## 11. Componentes comunes
+
+- `src/components/ui/LoadingScreen.tsx` - pantalla de carga reutilizable
+
+---
+
+## 12. Flujo principal de la app
+
+1. Usuario entra en `/`
+2. Sube una imagen en `RoomSetup`
+3. Se crea una vista previa y se almacena en Zustand
+4. Se navega a `/visualizer`
+5. `RoomVisualizer` usa la imagen y muestra productos
+6. El usuario filtra, busca y selecciona productos
+7. `SettingsPage` permite ajustar la API y opciones de la app
+
+---
+
+## 13. Cómo ejecutar el frontend
+
+Desde `frontend/`:
+
+```bash
+npm install
+npm run dev
+```
+
+Construcción de producción:
+
+```bash
+npm run build
+```
+
+---
+
+## 14. Posibles mejoras futuras
+
+- mover `roomVisualizerProducts` a una API real o servicio de datos
+- extraer más componentes presentacionales del visualizador
+- usar React Query para cargar configuración del cliente en lugar de gestión manual
+- añadir tests unitarios para hooks y componentes
+- normalizar rutas y nombres de features
+
+---
+
+## 15. Observaciones adicionales
+
+- La base API se controla desde `VITE_API_BASE_URL` o `DEV_API_BASE` en desarrollo.
+- La aplicación usa `queryClient` de React Query, aunque hoy solo se usa para potenciales fetches futuros.
+- El estado global es ligero y se usa principalmente para compartir imagen previa, modo de vista y selección de producto.
diff --git a/frontend/README.md b/frontend/README.md
index 34232b5b0ec06c40d634003f8dce48f5aeccf25f..7dbf7ebf3b2a3d84ad526bc47810d1d211331b8b 100644
--- a/frontend/README.md
+++ b/frontend/README.md
@@ -1,73 +1,73 @@
-# React + TypeScript + Vite
-
-This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.
-
-Currently, two official plugins are available:
-
-- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Oxc](https://oxc.rs)
-- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/)
-
-## React Compiler
-
-The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see [this documentation](https://react.dev/learn/react-compiler/installation).
-
-## Expanding the ESLint configuration
-
-If you are developing a production application, we recommend updating the configuration to enable type-aware lint rules:
-
-```js
-export default defineConfig([
-  globalIgnores(['dist']),
-  {
-    files: ['**/*.{ts,tsx}'],
-    extends: [
-      // Other configs...
-
-      // Remove tseslint.configs.recommended and replace with this
-      tseslint.configs.recommendedTypeChecked,
-      // Alternatively, use this for stricter rules
-      tseslint.configs.strictTypeChecked,
-      // Optionally, add this for stylistic rules
-      tseslint.configs.stylisticTypeChecked,
-
-      // Other configs...
-    ],
-    languageOptions: {
-      parserOptions: {
-        project: ['./tsconfig.node.json', './tsconfig.app.json'],
-        tsconfigRootDir: import.meta.dirname,
-      },
-      // other options...
-    },
-  },
-])
-```
-
-You can also install [eslint-plugin-react-x](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-x) and [eslint-plugin-react-dom](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-dom) for React-specific lint rules:
-
-```js
-// eslint.config.js
-import reactX from 'eslint-plugin-react-x'
-import reactDom from 'eslint-plugin-react-dom'
-
-export default defineConfig([
-  globalIgnores(['dist']),
-  {
-    files: ['**/*.{ts,tsx}'],
-    extends: [
-      // Other configs...
-      // Enable lint rules for React
-      reactX.configs['recommended-typescript'],
-      // Enable lint rules for React DOM
-      reactDom.configs.recommended,
-    ],
-    languageOptions: {
-      parserOptions: {
-        project: ['./tsconfig.node.json', './tsconfig.app.json'],
-        tsconfigRootDir: import.meta.dirname,
-      },
-      // other options...
-    },
-  },
-])
-```
+# React + TypeScript + Vite
+
+This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.
+
+Currently, two official plugins are available:
+
+- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Oxc](https://oxc.rs)
+- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/)
+
+## React Compiler
+
+The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see [this documentation](https://react.dev/learn/react-compiler/installation).
+
+## Expanding the ESLint configuration
+
+If you are developing a production application, we recommend updating the configuration to enable type-aware lint rules:
+
+```js
+export default defineConfig([
+  globalIgnores(['dist']),
+  {
+    files: ['**/*.{ts,tsx}'],
+    extends: [
+      // Other configs...
+
+      // Remove tseslint.configs.recommended and replace with this
+      tseslint.configs.recommendedTypeChecked,
+      // Alternatively, use this for stricter rules
+      tseslint.configs.strictTypeChecked,
+      // Optionally, add this for stylistic rules
+      tseslint.configs.stylisticTypeChecked,
+
+      // Other configs...
+    ],
+    languageOptions: {
+      parserOptions: {
+        project: ['./tsconfig.node.json', './tsconfig.app.json'],
+        tsconfigRootDir: import.meta.dirname,
+      },
+      // other options...
+    },
+  },
+])
+```
+
+You can also install [eslint-plugin-react-x](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-x) and [eslint-plugin-react-dom](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-dom) for React-specific lint rules:
+
+```js
+// eslint.config.js
+import reactX from 'eslint-plugin-react-x'
+import reactDom from 'eslint-plugin-react-dom'
+
+export default defineConfig([
+  globalIgnores(['dist']),
+  {
+    files: ['**/*.{ts,tsx}'],
+    extends: [
+      // Other configs...
+      // Enable lint rules for React
+      reactX.configs['recommended-typescript'],
+      // Enable lint rules for React DOM
+      reactDom.configs.recommended,
+    ],
+    languageOptions: {
+      parserOptions: {
+        project: ['./tsconfig.node.json', './tsconfig.app.json'],
+        tsconfigRootDir: import.meta.dirname,
+      },
+      // other options...
+    },
+  },
+])
+```
diff --git a/frontend/eslint.config.js b/frontend/eslint.config.js
index d41a94898978b552cc09e2ed0cac1449a31fe30b..5e6b472f583e34a1cca751440d4f241495475723 100644
--- a/frontend/eslint.config.js
+++ b/frontend/eslint.config.js
@@ -1,23 +1,23 @@
-import js from '@eslint/js'
-import globals from 'globals'
-import reactHooks from 'eslint-plugin-react-hooks'
-import reactRefresh from 'eslint-plugin-react-refresh'
-import tseslint from 'typescript-eslint'
-import { defineConfig, globalIgnores } from 'eslint/config'
-
-export default defineConfig([
-  globalIgnores(['dist']),
-  {
-    files: ['**/*.{ts,tsx}'],
-    extends: [
-      js.configs.recommended,
-      tseslint.configs.recommended,
-      reactHooks.configs.flat.recommended,
-      reactRefresh.configs.vite,
-    ],
-    languageOptions: {
-      ecmaVersion: 2020,
-      globals: globals.browser,
-    },
-  },
-])
+import js from '@eslint/js'
+import globals from 'globals'
+import reactHooks from 'eslint-plugin-react-hooks'
+import reactRefresh from 'eslint-plugin-react-refresh'
+import tseslint from 'typescript-eslint'
+import { defineConfig, globalIgnores } from 'eslint/config'
+
+export default defineConfig([
+  globalIgnores(['dist']),
+  {
+    files: ['**/*.{ts,tsx}'],
+    extends: [
+      js.configs.recommended,
+      tseslint.configs.recommended,
+      reactHooks.configs.flat.recommended,
+      reactRefresh.configs.vite,
+    ],
+    languageOptions: {
+      ecmaVersion: 2020,
+      globals: globals.browser,
+    },
+  },
+])
diff --git a/frontend/index.html b/frontend/index.html
index 4e43d7613289d19607b2b206d081005d17bd0ef1..edb4df1ef81e845d34be41842ed0a55a70ea5e86 100644
--- a/frontend/index.html
+++ b/frontend/index.html
@@ -1,35 +1,28 @@
-<!doctype html>
-<html lang="es">
-  <head>
-    <meta charset="UTF-8" />
-
-    <!-- Viewport: viewport-fit=cover extiende hasta los bordes en dispositivos con notch -->
-    <meta
-      name="viewport"
-      content="width=device-width, initial-scale=1.0, viewport-fit=cover"
-    />
-
-    <!-- PWA -->
-    <link rel="manifest" href="/manifest.json" />
-    <meta name="theme-color" content="#0047AB" />
-
-    <!-- iOS PWA: fullscreen al instalarse desde Safari -->
-    <meta name="apple-mobile-web-app-capable" content="yes" />
-    <meta name="mobile-web-app-capable" content="yes" />
-    <meta
-      name="apple-mobile-web-app-status-bar-style"
-      content="black-translucent"
-    />
-    <meta name="apple-mobile-web-app-title" content="Hyper Reality" />
-    <link rel="apple-touch-icon" href="/favicon.svg" />
-
-    <!-- Icono -->
-    <link rel="icon" type="image/svg+xml" href="/favicon.svg" />
-
-    <title>Hyper Reality Visualizer</title>
-  </head>
-  <body>
-    <div id="root"></div>
-    <script type="module" src="/src/main.tsx"></script>
-  </body>
-</html>
+<!doctype html>
+<html lang="es">
+  <head>
+    <meta charset="UTF-8" />
+
+    <!-- Viewport: viewport-fit=cover extiende hasta los bordes en dispositivos con notch -->
+    <meta name="viewport" content="width=device-width, initial-scale=1.0, viewport-fit=cover" />
+
+    <!-- PWA -->
+    <link rel="manifest" href="/manifest.json" />
+    <meta name="theme-color" content="#0047AB" />
+
+    <!-- iOS PWA: fullscreen al instalarse desde Safari -->
+    <meta name="apple-mobile-web-app-capable" content="yes" />
+    <meta name="apple-mobile-web-app-status-bar-style" content="black-translucent" />
+    <meta name="apple-mobile-web-app-title" content="Hyper Reality" />
+    <link rel="apple-touch-icon" href="/favicon.svg" />
+
+    <!-- Icono -->
+    <link rel="icon" type="image/svg+xml" href="/favicon.svg" />
+
+    <title>Hyper Reality Visualizer</title>
+  </head>
+  <body>
+    <div id="root"></div>
+    <script type="module" src="/src/main.tsx"></script>
+  </body>
+</html>
diff --git a/frontend/package.json b/frontend/package.json
index daaf694248843191f2d7c86bdc2e03705bae687c..777bdbc00cd7f2df82da15a4c9569631a099d13c 100644
--- a/frontend/package.json
+++ b/frontend/package.json
@@ -1,47 +1,47 @@
-{
-  "name": "frontend",
-  "private": true,
-  "version": "0.1.0",
-  "type": "module",
-  "scripts": {
-    "dev": "vite",
-    "build": "tsc -b && vite build",
-    "build:app": "npm run build",
-    "lint": "eslint .",
-    "preview": "vite preview",
-    "generate:version": "node ./scripts/generate-version.js",
-    "predev": "npm run generate:version",
-    "prebuild": "npm run generate:version",
-    "version:patch": "npm version patch --no-git-tag-version",
-    "version:minor": "npm version minor --no-git-tag-version",
-    "version:major": "npm version major --no-git-tag-version"
-  },
-  "dependencies": {
-    "@tanstack/react-query": "^5.99.2",
-    "@tanstack/react-query-devtools": "^5.99.2",
-    "lucide-react": "^1.8.0",
-    "react": "^19.2.5",
-    "react-dom": "^19.2.5",
-    "react-router-dom": "^7.14.2",
-    "react-share": "^5.3.0",
-    "sweetalert2": "^11.26.24",
-    "zustand": "^5.0.12"
-  },
-  "devDependencies": {
-    "@eslint/js": "^9.39.4",
-    "@types/node": "^24.12.2",
-    "@types/react": "^19.2.14",
-    "@types/react-dom": "^19.2.3",
-    "@vitejs/plugin-react": "^6.0.1",
-    "autoprefixer": "^10.4.19",
-    "eslint": "^9.39.4",
-    "eslint-plugin-react-hooks": "^7.1.1",
-    "eslint-plugin-react-refresh": "^0.5.2",
-    "globals": "^17.5.0",
-    "postcss": "^8.5.10",
-    "tailwindcss": "^3.4.5",
-    "typescript": "~6.0.2",
-    "typescript-eslint": "^8.58.2",
-    "vite": "^8.0.9"
-  }
-}
+{
+  "name": "frontend",
+  "private": true,
+  "version": "0.1.0",
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "tsc -b && vite build",
+    "build:app": "npm run build",
+    "lint": "eslint .",
+    "preview": "vite preview",
+    "generate:version": "node ./scripts/generate-version.js",
+    "predev": "npm run generate:version",
+    "prebuild": "npm run generate:version",
+    "version:patch": "npm version patch --no-git-tag-version",
+    "version:minor": "npm version minor --no-git-tag-version",
+    "version:major": "npm version major --no-git-tag-version"
+  },
+  "dependencies": {
+    "@tanstack/react-query": "^5.99.2",
+    "@tanstack/react-query-devtools": "^5.99.2",
+    "lucide-react": "^1.8.0",
+    "react": "^19.2.5",
+    "react-dom": "^19.2.5",
+    "react-router-dom": "^7.14.2",
+    "react-share": "^5.3.0",
+    "sweetalert2": "^11.26.24",
+    "zustand": "^5.0.12"
+  },
+  "devDependencies": {
+    "@eslint/js": "^9.39.4",
+    "@types/node": "^24.12.2",
+    "@types/react": "^19.2.14",
+    "@types/react-dom": "^19.2.3",
+    "@vitejs/plugin-react": "^6.0.1",
+    "autoprefixer": "^10.4.19",
+    "eslint": "^9.39.4",
+    "eslint-plugin-react-hooks": "^7.1.1",
+    "eslint-plugin-react-refresh": "^0.5.2",
+    "globals": "^17.5.0",
+    "postcss": "^8.5.10",
+    "tailwindcss": "^3.4.5",
+    "typescript": "~6.0.2",
+    "typescript-eslint": "^8.58.2",
+    "vite": "^8.0.9"
+  }
+}
diff --git a/frontend/postcss.config.js b/frontend/postcss.config.js
index daedffd2bf4950df77bf2c9d6920181331f4c48a..2aa7205d4b402a1bdfbe07110c61df920b370066 100644
--- a/frontend/postcss.config.js
+++ b/frontend/postcss.config.js
@@ -1,6 +1,6 @@
-export default {
-  plugins: {
-    tailwindcss: {},
-    autoprefixer: {},
-  },
-};
+export default {
+  plugins: {
+    tailwindcss: {},
+    autoprefixer: {},
+  },
+};
diff --git a/frontend/public/icons.svg b/frontend/public/icons.svg
index 5615851e102ba0b9d90688db879e9f9db99ab0fa..e9522193d9f796a9748e9ad8c952a5df73c87db9 100644
--- a/frontend/public/icons.svg
+++ b/frontend/public/icons.svg
@@ -1,24 +1,24 @@
-<svg xmlns="http://www.w3.org/2000/svg">
-  <symbol id="bluesky-icon" viewBox="0 0 16 17">
-    <g clip-path="url(#bluesky-clip)"><path fill="#08060d" d="M7.75 7.735c-.693-1.348-2.58-3.86-4.334-5.097-1.68-1.187-2.32-.981-2.74-.79C.188 2.065.1 2.812.1 3.251s.241 3.602.398 4.13c.52 1.744 2.367 2.333 4.07 2.145-2.495.37-4.71 1.278-1.805 4.512 3.196 3.309 4.38-.71 4.987-2.746.608 2.036 1.307 5.91 4.93 2.746 2.72-2.746.747-4.143-1.747-4.512 1.702.189 3.55-.4 4.07-2.145.156-.528.397-3.691.397-4.13s-.088-1.186-.575-1.406c-.42-.19-1.06-.395-2.741.79-1.755 1.24-3.64 3.752-4.334 5.099"/></g>
-    <defs><clipPath id="bluesky-clip"><path fill="#fff" d="M.1.85h15.3v15.3H.1z"/></clipPath></defs>
-  </symbol>
-  <symbol id="discord-icon" viewBox="0 0 20 19">
-    <path fill="#08060d" d="M16.224 3.768a14.5 14.5 0 0 0-3.67-1.153c-.158.286-.343.67-.47.976a13.5 13.5 0 0 0-4.067 0c-.128-.306-.317-.69-.476-.976A14.4 14.4 0 0 0 3.868 3.77C1.546 7.28.916 10.703 1.231 14.077a14.7 14.7 0 0 0 4.5 2.306q.545-.748.965-1.587a9.5 9.5 0 0 1-1.518-.74q.191-.14.372-.293c2.927 1.369 6.107 1.369 8.999 0q.183.152.372.294-.723.437-1.52.74.418.838.963 1.588a14.6 14.6 0 0 0 4.504-2.308c.37-3.911-.63-7.302-2.644-10.309m-9.13 8.234c-.878 0-1.599-.82-1.599-1.82 0-.998.705-1.82 1.6-1.82.894 0 1.614.82 1.599 1.82.001 1-.705 1.82-1.6 1.82m5.91 0c-.878 0-1.599-.82-1.599-1.82 0-.998.705-1.82 1.6-1.82.893 0 1.614.82 1.599 1.82 0 1-.706 1.82-1.6 1.82"/>
-  </symbol>
-  <symbol id="documentation-icon" viewBox="0 0 21 20">
-    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="m15.5 13.333 1.533 1.322c.645.555.967.833.967 1.178s-.322.623-.967 1.179L15.5 18.333m-3.333-5-1.534 1.322c-.644.555-.966.833-.966 1.178s.322.623.966 1.179l1.534 1.321"/>
-    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="M17.167 10.836v-4.32c0-1.41 0-2.117-.224-2.68-.359-.906-1.118-1.621-2.08-1.96-.599-.21-1.349-.21-2.848-.21-2.623 0-3.935 0-4.983.369-1.684.591-3.013 1.842-3.641 3.428C3 6.449 3 7.684 3 10.154v2.122c0 2.558 0 3.838.706 4.726q.306.383.713.671c.76.536 1.79.64 3.581.66"/>
-    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="M3 10a2.78 2.78 0 0 1 2.778-2.778c.555 0 1.209.097 1.748-.047.48-.129.854-.503.982-.982.145-.54.048-1.194.048-1.749a2.78 2.78 0 0 1 2.777-2.777"/>
-  </symbol>
-  <symbol id="github-icon" viewBox="0 0 19 19">
-    <path fill="#08060d" fill-rule="evenodd" d="M9.356 1.85C5.05 1.85 1.57 5.356 1.57 9.694a7.84 7.84 0 0 0 5.324 7.44c.387.079.528-.168.528-.376 0-.182-.013-.805-.013-1.454-2.165.467-2.616-.935-2.616-.935-.349-.91-.864-1.143-.864-1.143-.71-.48.051-.48.051-.48.787.051 1.2.805 1.2.805.695 1.194 1.817.857 2.268.649.064-.507.27-.857.49-1.052-1.728-.182-3.545-.857-3.545-3.87 0-.857.31-1.558.8-2.104-.078-.195-.349-1 .077-2.078 0 0 .657-.208 2.14.805a7.5 7.5 0 0 1 1.946-.26c.657 0 1.328.092 1.946.26 1.483-1.013 2.14-.805 2.14-.805.426 1.078.155 1.883.078 2.078.502.546.799 1.247.799 2.104 0 3.013-1.818 3.675-3.558 3.87.284.247.528.714.528 1.454 0 1.052-.012 1.896-.012 2.156 0 .208.142.455.528.377a7.84 7.84 0 0 0 5.324-7.441c.013-4.338-3.48-7.844-7.773-7.844" clip-rule="evenodd"/>
-  </symbol>
-  <symbol id="social-icon" viewBox="0 0 20 20">
-    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="M12.5 6.667a4.167 4.167 0 1 0-8.334 0 4.167 4.167 0 0 0 8.334 0"/>
-    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="M2.5 16.667a5.833 5.833 0 0 1 8.75-5.053m3.837.474.513 1.035c.07.144.257.282.414.309l.93.155c.596.1.736.536.307.965l-.723.73a.64.64 0 0 0-.152.531l.207.903c.164.715-.213.991-.84.618l-.872-.52a.63.63 0 0 0-.577 0l-.872.52c-.624.373-1.003.094-.84-.618l.207-.903a.64.64 0 0 0-.152-.532l-.723-.729c-.426-.43-.289-.864.306-.964l.93-.156a.64.64 0 0 0 .412-.31l.513-1.034c.28-.562.735-.562 1.012 0"/>
-  </symbol>
-  <symbol id="x-icon" viewBox="0 0 19 19">
-    <path fill="#08060d" fill-rule="evenodd" d="M1.893 1.98c.052.072 1.245 1.769 2.653 3.77l2.892 4.114c.183.261.333.48.333.486s-.068.089-.152.183l-.522.593-.765.867-3.597 4.087c-.375.426-.734.834-.798.905a1 1 0 0 0-.118.148c0 .01.236.017.664.017h.663l.729-.83c.4-.457.796-.906.879-.999a692 692 0 0 0 1.794-2.038c.034-.037.301-.34.594-.675l.551-.624.345-.392a7 7 0 0 1 .34-.374c.006 0 .93 1.306 2.052 2.903l2.084 2.965.045.063h2.275c1.87 0 2.273-.003 2.266-.021-.008-.02-1.098-1.572-3.894-5.547-2.013-2.862-2.28-3.246-2.273-3.266.008-.019.282-.332 2.085-2.38l2-2.274 1.567-1.782c.022-.028-.016-.03-.65-.03h-.674l-.3.342a871 871 0 0 1-1.782 2.025c-.067.075-.405.458-.75.852a100 100 0 0 1-.803.91c-.148.172-.299.344-.99 1.127-.304.343-.32.358-.345.327-.015-.019-.904-1.282-1.976-2.808L6.365 1.85H1.8zm1.782.91 8.078 11.294c.772 1.08 1.413 1.973 1.425 1.984.016.017.241.02 1.05.017l1.03-.004-2.694-3.766L7.796 5.75 5.722 2.852l-1.039-.004-1.039-.004z" clip-rule="evenodd"/>
-  </symbol>
-</svg>
+<svg xmlns="http://www.w3.org/2000/svg">
+  <symbol id="bluesky-icon" viewBox="0 0 16 17">
+    <g clip-path="url(#bluesky-clip)"><path fill="#08060d" d="M7.75 7.735c-.693-1.348-2.58-3.86-4.334-5.097-1.68-1.187-2.32-.981-2.74-.79C.188 2.065.1 2.812.1 3.251s.241 3.602.398 4.13c.52 1.744 2.367 2.333 4.07 2.145-2.495.37-4.71 1.278-1.805 4.512 3.196 3.309 4.38-.71 4.987-2.746.608 2.036 1.307 5.91 4.93 2.746 2.72-2.746.747-4.143-1.747-4.512 1.702.189 3.55-.4 4.07-2.145.156-.528.397-3.691.397-4.13s-.088-1.186-.575-1.406c-.42-.19-1.06-.395-2.741.79-1.755 1.24-3.64 3.752-4.334 5.099"/></g>
+    <defs><clipPath id="bluesky-clip"><path fill="#fff" d="M.1.85h15.3v15.3H.1z"/></clipPath></defs>
+  </symbol>
+  <symbol id="discord-icon" viewBox="0 0 20 19">
+    <path fill="#08060d" d="M16.224 3.768a14.5 14.5 0 0 0-3.67-1.153c-.158.286-.343.67-.47.976a13.5 13.5 0 0 0-4.067 0c-.128-.306-.317-.69-.476-.976A14.4 14.4 0 0 0 3.868 3.77C1.546 7.28.916 10.703 1.231 14.077a14.7 14.7 0 0 0 4.5 2.306q.545-.748.965-1.587a9.5 9.5 0 0 1-1.518-.74q.191-.14.372-.293c2.927 1.369 6.107 1.369 8.999 0q.183.152.372.294-.723.437-1.52.74.418.838.963 1.588a14.6 14.6 0 0 0 4.504-2.308c.37-3.911-.63-7.302-2.644-10.309m-9.13 8.234c-.878 0-1.599-.82-1.599-1.82 0-.998.705-1.82 1.6-1.82.894 0 1.614.82 1.599 1.82.001 1-.705 1.82-1.6 1.82m5.91 0c-.878 0-1.599-.82-1.599-1.82 0-.998.705-1.82 1.6-1.82.893 0 1.614.82 1.599 1.82 0 1-.706 1.82-1.6 1.82"/>
+  </symbol>
+  <symbol id="documentation-icon" viewBox="0 0 21 20">
+    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="m15.5 13.333 1.533 1.322c.645.555.967.833.967 1.178s-.322.623-.967 1.179L15.5 18.333m-3.333-5-1.534 1.322c-.644.555-.966.833-.966 1.178s.322.623.966 1.179l1.534 1.321"/>
+    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="M17.167 10.836v-4.32c0-1.41 0-2.117-.224-2.68-.359-.906-1.118-1.621-2.08-1.96-.599-.21-1.349-.21-2.848-.21-2.623 0-3.935 0-4.983.369-1.684.591-3.013 1.842-3.641 3.428C3 6.449 3 7.684 3 10.154v2.122c0 2.558 0 3.838.706 4.726q.306.383.713.671c.76.536 1.79.64 3.581.66"/>
+    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="M3 10a2.78 2.78 0 0 1 2.778-2.778c.555 0 1.209.097 1.748-.047.48-.129.854-.503.982-.982.145-.54.048-1.194.048-1.749a2.78 2.78 0 0 1 2.777-2.777"/>
+  </symbol>
+  <symbol id="github-icon" viewBox="0 0 19 19">
+    <path fill="#08060d" fill-rule="evenodd" d="M9.356 1.85C5.05 1.85 1.57 5.356 1.57 9.694a7.84 7.84 0 0 0 5.324 7.44c.387.079.528-.168.528-.376 0-.182-.013-.805-.013-1.454-2.165.467-2.616-.935-2.616-.935-.349-.91-.864-1.143-.864-1.143-.71-.48.051-.48.051-.48.787.051 1.2.805 1.2.805.695 1.194 1.817.857 2.268.649.064-.507.27-.857.49-1.052-1.728-.182-3.545-.857-3.545-3.87 0-.857.31-1.558.8-2.104-.078-.195-.349-1 .077-2.078 0 0 .657-.208 2.14.805a7.5 7.5 0 0 1 1.946-.26c.657 0 1.328.092 1.946.26 1.483-1.013 2.14-.805 2.14-.805.426 1.078.155 1.883.078 2.078.502.546.799 1.247.799 2.104 0 3.013-1.818 3.675-3.558 3.87.284.247.528.714.528 1.454 0 1.052-.012 1.896-.012 2.156 0 .208.142.455.528.377a7.84 7.84 0 0 0 5.324-7.441c.013-4.338-3.48-7.844-7.773-7.844" clip-rule="evenodd"/>
+  </symbol>
+  <symbol id="social-icon" viewBox="0 0 20 20">
+    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="M12.5 6.667a4.167 4.167 0 1 0-8.334 0 4.167 4.167 0 0 0 8.334 0"/>
+    <path fill="none" stroke="#aa3bff" stroke-linecap="round" stroke-linejoin="round" stroke-width="1.35" d="M2.5 16.667a5.833 5.833 0 0 1 8.75-5.053m3.837.474.513 1.035c.07.144.257.282.414.309l.93.155c.596.1.736.536.307.965l-.723.73a.64.64 0 0 0-.152.531l.207.903c.164.715-.213.991-.84.618l-.872-.52a.63.63 0 0 0-.577 0l-.872.52c-.624.373-1.003.094-.84-.618l.207-.903a.64.64 0 0 0-.152-.532l-.723-.729c-.426-.43-.289-.864.306-.964l.93-.156a.64.64 0 0 0 .412-.31l.513-1.034c.28-.562.735-.562 1.012 0"/>
+  </symbol>
+  <symbol id="x-icon" viewBox="0 0 19 19">
+    <path fill="#08060d" fill-rule="evenodd" d="M1.893 1.98c.052.072 1.245 1.769 2.653 3.77l2.892 4.114c.183.261.333.48.333.486s-.068.089-.152.183l-.522.593-.765.867-3.597 4.087c-.375.426-.734.834-.798.905a1 1 0 0 0-.118.148c0 .01.236.017.664.017h.663l.729-.83c.4-.457.796-.906.879-.999a692 692 0 0 0 1.794-2.038c.034-.037.301-.34.594-.675l.551-.624.345-.392a7 7 0 0 1 .34-.374c.006 0 .93 1.306 2.052 2.903l2.084 2.965.045.063h2.275c1.87 0 2.273-.003 2.266-.021-.008-.02-1.098-1.572-3.894-5.547-2.013-2.862-2.28-3.246-2.273-3.266.008-.019.282-.332 2.085-2.38l2-2.274 1.567-1.782c.022-.028-.016-.03-.65-.03h-.674l-.3.342a871 871 0 0 1-1.782 2.025c-.067.075-.405.458-.75.852a100 100 0 0 1-.803.91c-.148.172-.299.344-.99 1.127-.304.343-.32.358-.345.327-.015-.019-.904-1.282-1.976-2.808L6.365 1.85H1.8zm1.782.91 8.078 11.294c.772 1.08 1.413 1.973 1.425 1.984.016.017.241.02 1.05.017l1.03-.004-2.694-3.766L7.796 5.75 5.722 2.852l-1.039-.004-1.039-.004z" clip-rule="evenodd"/>
+  </symbol>
+</svg>
diff --git a/frontend/rewrite_css.py b/frontend/rewrite_css.py
index 0ad2dc7ebceabb4cb7b711284365b410b91eca19..185b7d3af6bf0ce2f731248055d21b08c11f60b5 100644
--- a/frontend/rewrite_css.py
+++ b/frontend/rewrite_css.py
@@ -1,509 +1,509 @@
-from pathlib import Path
-
-app_css = '''
-:root {
-  font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif;
-  color: #111827;
-  background: #f8fafc;
-  line-height: 1.5;
-}
-
-*, *::before, *::after {
-  box-sizing: border-box;
-}
-
-html, body, #root {
-  min-height: 100%;
-}
-
-body {
-  margin: 0;
-  background: #f8fafc;
-  color: #111827;
-}
-
-button, input, select, textarea {
-  font: inherit;
-}
-
-button {
-  cursor: pointer;
-}
-
-.app-shell {
-  max-width: 1200px;
-  margin: 0 auto;
-  padding: 24px;
-}
-
-.topbar {
-  display: flex;
-  flex-wrap: wrap;
-  justify-content: space-between;
-  align-items: center;
-  gap: 16px;
-  padding: 22px 24px;
-  background: #ffffff;
-  border: 1px solid #e5e7eb;
-  border-radius: 18px;
-}
-
-.topbar h1 {
-  margin: 0;
-  font-size: clamp(1.9rem, 2.5vw, 2.6rem);
-}
-
-.topbar p {
-  margin: 6px 0 0;
-  color: #475569;
-}
-
-.topbar-nav {
-  display: flex;
-  flex-wrap: wrap;
-  gap: 10px;
-}
-
-.topbar-nav a {
-  display: inline-flex;
-  align-items: center;
-  justify-content: center;
-  padding: 10px 14px;
-  border-radius: 14px;
-  background: #f8fafc;
-  color: #334155;
-  text-decoration: none;
-  border: 1px solid transparent;
-  transition: background 0.2s ease, border-color 0.2s ease;
-}
-
-.topbar-nav a:hover {
-  background: #ffffff;
-  border-color: #d1d5db;
-}
-
-.content-viewer {
-  margin-top: 24px;
-}
-
-.route-index,
-.panel,
-.viewer-panel,
-.bridge-panel,
-.room-setup-dropzone,
-.room-setup-card,
-.room-setup-preview {
-  background: #ffffff;
-  border: 1px solid #e5e7eb;
-  border-radius: 20px;
-}
-
-.route-index,
-.panel,
-.viewer-panel,
-.bridge-panel,
-.room-setup-card {
-  padding: 22px;
-}
-
-.route-index h2,
-.panel h2,
-.viewer-panel h2,
-.room-setup-copy h1,
-.room-setup-bottom h2 {
-  margin: 0 0 16px;
-}
-
-.route-index p,
-.room-setup-features li,
-.room-setup-drop-content p,
-.room-setup-drop-content small,
-.room-setup-card h3,
-.topbar p,
-.error-box,
-.empty-state {
-  color: #475569;
-}
-
-.route-index ul,
-.room-setup-features,
-.room-setup-filters,
-.room-setup-grid {
-  margin: 0;
-  padding: 0;
-  list-style: none;
-}
-
-.route-index ul {
-  display: grid;
-  gap: 12px;
-}
-
-.form-row {
-  display: grid;
-  gap: 14px;
-  margin-bottom: 20px;
-}
-
-label {
-  font-size: 0.95rem;
-  color: #334155;
-}
-
-input,
-select,
-textarea {
-  width: 100%;
-  padding: 14px 16px;
-  border-radius: 14px;
-  border: 1px solid #d1d5db;
-  background: #f8fafc;
-  color: #111827;
-}
-
-input:focus,
-select:focus,
-textarea:focus {
-  outline: 2px solid #cbd5e1;
-  outline-offset: 2px;
-}
-
-.button,
-.button-primary,
-.button-secondary {
-  display: inline-flex;
-  align-items: center;
-  justify-content: center;
-  gap: 10px;
-  border-radius: 16px;
-  padding: 14px 18px;
-  font-weight: 700;
-  border: 1px solid transparent;
-  transition: all 0.2s ease;
-}
-
-.button {
-  background: #111827;
-  color: #ffffff;
-}
-
-.button:hover {
-  opacity: 0.95;
-}
-
-.button.secondary,
-.button-secondary {
-  background: #f3f4f6;
-  color: #111827;
-  border-color: #d1d5db;
-}
-
-.error-box {
-  margin-top: 16px;
-  padding: 16px;
-  border-radius: 16px;
-  background: #fef2f2;
-  color: #991b1b;
-  border: 1px solid #fecaca;
-}
-
-.empty-state {
-  min-height: 220px;
-  display: grid;
-  place-content: center;
-  border: 1px dashed #d1d5db;
-  border-radius: 18px;
-}
-
-.room-setup {
-  background: #f8fafc;
-}
-
-.room-setup-inner {
-  max-width: 1200px;
-  margin: 0 auto;
-  padding: 32px 24px;
-}
-
-.room-setup-header {
-  display: flex;
-  justify-content: flex-end;
-  margin-bottom: 24px;
-}
-
-.room-setup-close {
-  border: none;
-  background: transparent;
-  color: #475569;
-  padding: 10px;
-  border-radius: 999px;
-  cursor: pointer;
-}
-
-.room-setup-close:hover {
-  background: #e5e7eb;
-}
-
-.room-setup-top {
-  display: grid;
-  gap: 24px;
-  grid-template-columns: 1.1fr 0.9fr;
-  margin-bottom: 40px;
-}
-
-.room-setup-copy h1 {
-  margin: 0 0 24px;
-  font-size: clamp(2rem, 2.5vw, 3rem);
-  color: #111827;
-}
-
-.room-setup-features {
-  display: grid;
-  gap: 16px;
-}
-
-.room-setup-features li {
-  display: flex;
-  align-items: center;
-  gap: 12px;
-  color: #475569;
-}
-
-.room-setup-actions {
-  display: grid;
-  gap: 16px;
-}
-
-.button-primary {
-  background: #111827;
-  color: #ffffff;
-}
-
-.button-primary:hover {
-  opacity: 0.95;
-}
-
-.button-secondary {
-  background: #ffffff;
-  color: #334155;
-  border-color: #d1d5db;
-}
-
-.button-secondary:hover {
-  background: #f3f4f6;
-}
-
-.button-icon-border {
-  display: inline-flex;
-  align-items: center;
-  justify-content: center;
-  width: 30px;
-  height: 30px;
-  border-radius: 10px;
-  border: 1px solid #d1d5db;
-}
-
-.room-setup-dropzone {
-  position: relative;
-  min-height: 420px;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  transition: all 0.2s ease;
-  padding: 24px;
-  border: 1px dashed #d1d5db;
-  border-radius: 28px;
-}
-
-.room-setup-dropzone.dragging {
-  background: #f3f4f6;
-}
-
-.room-setup-file-input {
-  position: absolute;
-  inset: 0;
-  width: 100%;
-  height: 100%;
-  opacity: 0;
-  cursor: pointer;
-}
-
-.room-setup-drop-content {
-  text-align: center;
-}
-
-.room-setup-drop-icon {
-  display: inline-flex;
-  align-items: center;
-  justify-content: center;
-  width: 72px;
-  height: 72px;
-  border-radius: 999px;
-  background: #e2e8f0;
-  color: #64748b;
-  margin-bottom: 18px;
-}
-
-.room-setup-drop-icon.active {
-  background: #dbeafe;
-  color: #1e293b;
-}
-
-.room-setup-drop-content h3 {
-  margin: 0 0 8px;
-  font-size: 1.2rem;
-}
-
-.room-setup-drop-content p,
-.room-setup-drop-content small {
-  margin: 0;
-  color: #64748b;
-}
-
-.room-setup-preview {
-  position: relative;
-  width: 100%;
-  height: 100%;
-}
-
-.room-setup-preview img {
-  width: 100%;
-  height: 100%;
-  object-fit: cover;
-}
-
-.room-setup-preview-overlay {
-  position: absolute;
-  inset: 0;
-  background: rgba(255, 255, 255, 0.85);
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  opacity: 0;
-  transition: opacity 0.2s ease;
-}
-
-.room-setup-preview:hover .room-setup-preview-overlay {
-  opacity: 1;
-}
-
-.button-delete {
-  background: #ffffff;
-  color: #111827;
-  padding: 12px 16px;
-  border-radius: 14px;
-  font-weight: 600;
-  border: 1px solid #d1d5db;
-}
-
-.room-setup-bottom h2 {
-  margin: 0 0 24px;
-}
-
-.room-setup-filters {
-  display: flex;
-  flex-wrap: wrap;
-  gap: 10px;
-  margin-bottom: 24px;
-}
-
-.room-setup-filter {
-  border: 1px solid #d1d5db;
-  background: #ffffff;
-  color: #334155;
-  padding: 10px 16px;
-  border-radius: 16px;
-  cursor: pointer;
-  transition: all 0.2s ease;
-}
-
-.room-setup-filter.active {
-  background: #f3f4f6;
-}
-
-.room-setup-grid {
-  display: grid;
-  grid-template-columns: repeat(1, minmax(0, 1fr));
-  gap: 20px;
-}
-
-.room-setup-card {
-  overflow: hidden;
-  border-radius: 24px;
-  background: #ffffff;
-  box-shadow: 0 8px 20px rgba(15, 23, 42, 0.06);
-}
-
-.room-setup-card-image {
-  position: relative;
-  aspect-ratio: 4 / 3;
-  overflow: hidden;
-}
-
-.room-setup-card-image img {
-  width: 100%;
-  height: 100%;
-  object-fit: cover;
-  transition: transform 0.4s ease;
-}
-
-.room-setup-card:hover .room-setup-card-image img {
-  transform: scale(1.04);
-}
-
-.room-setup-card h3 {
-  margin: 16px;
-  font-size: 1rem;
-  color: #334155;
-}
-
-.app-version-badge {
-  position: fixed;
-  right: 0;
-  bottom: 0;
-  padding: 10px 14px;
-  border-radius: 12px 0 0 0;
-  background: rgba(255, 255, 255, 0.95);
-  border: 1px solid #e5e7eb;
-  color: #475569;
-  font-size: 0.8rem;
-  z-index: 1000;
-}
-
-.app-version-badge span {
-  display: block;
-  font-weight: 700;
-  color: #111827;
-}
-
-.app-version-badge small {
-  display: block;
-  margin-top: 2px;
-}
-
-@media (max-width: 960px) {
-  .room-setup-top {
-    grid-template-columns: 1fr;
-  }
-
-  .room-setup-grid {
-    grid-template-columns: repeat(2, minmax(0, 1fr));
-  }
-}
-
-@media (max-width: 640px) {
-  .room-setup-inner {
-    padding: 20px 16px;
-  }
-
-  .room-setup-grid {
-    grid-template-columns: 1fr;
-  }
-}
-
-@media (max-width: 900px) {
-  .content {
-    grid-template-columns: 1fr;
-  }
-}
+from pathlib import Path
+
+app_css = '''
+:root {
+  font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif;
+  color: #111827;
+  background: #f8fafc;
+  line-height: 1.5;
+}
+
+*, *::before, *::after {
+  box-sizing: border-box;
+}
+
+html, body, #root {
+  min-height: 100%;
+}
+
+body {
+  margin: 0;
+  background: #f8fafc;
+  color: #111827;
+}
+
+button, input, select, textarea {
+  font: inherit;
+}
+
+button {
+  cursor: pointer;
+}
+
+.app-shell {
+  max-width: 1200px;
+  margin: 0 auto;
+  padding: 24px;
+}
+
+.topbar {
+  display: flex;
+  flex-wrap: wrap;
+  justify-content: space-between;
+  align-items: center;
+  gap: 16px;
+  padding: 22px 24px;
+  background: #ffffff;
+  border: 1px solid #e5e7eb;
+  border-radius: 18px;
+}
+
+.topbar h1 {
+  margin: 0;
+  font-size: clamp(1.9rem, 2.5vw, 2.6rem);
+}
+
+.topbar p {
+  margin: 6px 0 0;
+  color: #475569;
+}
+
+.topbar-nav {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 10px;
+}
+
+.topbar-nav a {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  padding: 10px 14px;
+  border-radius: 14px;
+  background: #f8fafc;
+  color: #334155;
+  text-decoration: none;
+  border: 1px solid transparent;
+  transition: background 0.2s ease, border-color 0.2s ease;
+}
+
+.topbar-nav a:hover {
+  background: #ffffff;
+  border-color: #d1d5db;
+}
+
+.content-viewer {
+  margin-top: 24px;
+}
+
+.route-index,
+.panel,
+.viewer-panel,
+.bridge-panel,
+.room-setup-dropzone,
+.room-setup-card,
+.room-setup-preview {
+  background: #ffffff;
+  border: 1px solid #e5e7eb;
+  border-radius: 20px;
+}
+
+.route-index,
+.panel,
+.viewer-panel,
+.bridge-panel,
+.room-setup-card {
+  padding: 22px;
+}
+
+.route-index h2,
+.panel h2,
+.viewer-panel h2,
+.room-setup-copy h1,
+.room-setup-bottom h2 {
+  margin: 0 0 16px;
+}
+
+.route-index p,
+.room-setup-features li,
+.room-setup-drop-content p,
+.room-setup-drop-content small,
+.room-setup-card h3,
+.topbar p,
+.error-box,
+.empty-state {
+  color: #475569;
+}
+
+.route-index ul,
+.room-setup-features,
+.room-setup-filters,
+.room-setup-grid {
+  margin: 0;
+  padding: 0;
+  list-style: none;
+}
+
+.route-index ul {
+  display: grid;
+  gap: 12px;
+}
+
+.form-row {
+  display: grid;
+  gap: 14px;
+  margin-bottom: 20px;
+}
+
+label {
+  font-size: 0.95rem;
+  color: #334155;
+}
+
+input,
+select,
+textarea {
+  width: 100%;
+  padding: 14px 16px;
+  border-radius: 14px;
+  border: 1px solid #d1d5db;
+  background: #f8fafc;
+  color: #111827;
+}
+
+input:focus,
+select:focus,
+textarea:focus {
+  outline: 2px solid #cbd5e1;
+  outline-offset: 2px;
+}
+
+.button,
+.button-primary,
+.button-secondary {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  gap: 10px;
+  border-radius: 16px;
+  padding: 14px 18px;
+  font-weight: 700;
+  border: 1px solid transparent;
+  transition: all 0.2s ease;
+}
+
+.button {
+  background: #111827;
+  color: #ffffff;
+}
+
+.button:hover {
+  opacity: 0.95;
+}
+
+.button.secondary,
+.button-secondary {
+  background: #f3f4f6;
+  color: #111827;
+  border-color: #d1d5db;
+}
+
+.error-box {
+  margin-top: 16px;
+  padding: 16px;
+  border-radius: 16px;
+  background: #fef2f2;
+  color: #991b1b;
+  border: 1px solid #fecaca;
+}
+
+.empty-state {
+  min-height: 220px;
+  display: grid;
+  place-content: center;
+  border: 1px dashed #d1d5db;
+  border-radius: 18px;
+}
+
+.room-setup {
+  background: #f8fafc;
+}
+
+.room-setup-inner {
+  max-width: 1200px;
+  margin: 0 auto;
+  padding: 32px 24px;
+}
+
+.room-setup-header {
+  display: flex;
+  justify-content: flex-end;
+  margin-bottom: 24px;
+}
+
+.room-setup-close {
+  border: none;
+  background: transparent;
+  color: #475569;
+  padding: 10px;
+  border-radius: 999px;
+  cursor: pointer;
+}
+
+.room-setup-close:hover {
+  background: #e5e7eb;
+}
+
+.room-setup-top {
+  display: grid;
+  gap: 24px;
+  grid-template-columns: 1.1fr 0.9fr;
+  margin-bottom: 40px;
+}
+
+.room-setup-copy h1 {
+  margin: 0 0 24px;
+  font-size: clamp(2rem, 2.5vw, 3rem);
+  color: #111827;
+}
+
+.room-setup-features {
+  display: grid;
+  gap: 16px;
+}
+
+.room-setup-features li {
+  display: flex;
+  align-items: center;
+  gap: 12px;
+  color: #475569;
+}
+
+.room-setup-actions {
+  display: grid;
+  gap: 16px;
+}
+
+.button-primary {
+  background: #111827;
+  color: #ffffff;
+}
+
+.button-primary:hover {
+  opacity: 0.95;
+}
+
+.button-secondary {
+  background: #ffffff;
+  color: #334155;
+  border-color: #d1d5db;
+}
+
+.button-secondary:hover {
+  background: #f3f4f6;
+}
+
+.button-icon-border {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  width: 30px;
+  height: 30px;
+  border-radius: 10px;
+  border: 1px solid #d1d5db;
+}
+
+.room-setup-dropzone {
+  position: relative;
+  min-height: 420px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  transition: all 0.2s ease;
+  padding: 24px;
+  border: 1px dashed #d1d5db;
+  border-radius: 28px;
+}
+
+.room-setup-dropzone.dragging {
+  background: #f3f4f6;
+}
+
+.room-setup-file-input {
+  position: absolute;
+  inset: 0;
+  width: 100%;
+  height: 100%;
+  opacity: 0;
+  cursor: pointer;
+}
+
+.room-setup-drop-content {
+  text-align: center;
+}
+
+.room-setup-drop-icon {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  width: 72px;
+  height: 72px;
+  border-radius: 999px;
+  background: #e2e8f0;
+  color: #64748b;
+  margin-bottom: 18px;
+}
+
+.room-setup-drop-icon.active {
+  background: #dbeafe;
+  color: #1e293b;
+}
+
+.room-setup-drop-content h3 {
+  margin: 0 0 8px;
+  font-size: 1.2rem;
+}
+
+.room-setup-drop-content p,
+.room-setup-drop-content small {
+  margin: 0;
+  color: #64748b;
+}
+
+.room-setup-preview {
+  position: relative;
+  width: 100%;
+  height: 100%;
+}
+
+.room-setup-preview img {
+  width: 100%;
+  height: 100%;
+  object-fit: cover;
+}
+
+.room-setup-preview-overlay {
+  position: absolute;
+  inset: 0;
+  background: rgba(255, 255, 255, 0.85);
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  opacity: 0;
+  transition: opacity 0.2s ease;
+}
+
+.room-setup-preview:hover .room-setup-preview-overlay {
+  opacity: 1;
+}
+
+.button-delete {
+  background: #ffffff;
+  color: #111827;
+  padding: 12px 16px;
+  border-radius: 14px;
+  font-weight: 600;
+  border: 1px solid #d1d5db;
+}
+
+.room-setup-bottom h2 {
+  margin: 0 0 24px;
+}
+
+.room-setup-filters {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 10px;
+  margin-bottom: 24px;
+}
+
+.room-setup-filter {
+  border: 1px solid #d1d5db;
+  background: #ffffff;
+  color: #334155;
+  padding: 10px 16px;
+  border-radius: 16px;
+  cursor: pointer;
+  transition: all 0.2s ease;
+}
+
+.room-setup-filter.active {
+  background: #f3f4f6;
+}
+
+.room-setup-grid {
+  display: grid;
+  grid-template-columns: repeat(1, minmax(0, 1fr));
+  gap: 20px;
+}
+
+.room-setup-card {
+  overflow: hidden;
+  border-radius: 24px;
+  background: #ffffff;
+  box-shadow: 0 8px 20px rgba(15, 23, 42, 0.06);
+}
+
+.room-setup-card-image {
+  position: relative;
+  aspect-ratio: 4 / 3;
+  overflow: hidden;
+}
+
+.room-setup-card-image img {
+  width: 100%;
+  height: 100%;
+  object-fit: cover;
+  transition: transform 0.4s ease;
+}
+
+.room-setup-card:hover .room-setup-card-image img {
+  transform: scale(1.04);
+}
+
+.room-setup-card h3 {
+  margin: 16px;
+  font-size: 1rem;
+  color: #334155;
+}
+
+.app-version-badge {
+  position: fixed;
+  right: 0;
+  bottom: 0;
+  padding: 10px 14px;
+  border-radius: 12px 0 0 0;
+  background: rgba(255, 255, 255, 0.95);
+  border: 1px solid #e5e7eb;
+  color: #475569;
+  font-size: 0.8rem;
+  z-index: 1000;
+}
+
+.app-version-badge span {
+  display: block;
+  font-weight: 700;
+  color: #111827;
+}
+
+.app-version-badge small {
+  display: block;
+  margin-top: 2px;
+}
+
+@media (max-width: 960px) {
+  .room-setup-top {
+    grid-template-columns: 1fr;
+  }
+
+  .room-setup-grid {
+    grid-template-columns: repeat(2, minmax(0, 1fr));
+  }
+}
+
+@media (max-width: 640px) {
+  .room-setup-inner {
+    padding: 20px 16px;
+  }
+
+  .room-setup-grid {
+    grid-template-columns: 1fr;
+  }
+}
+
+@media (max-width: 900px) {
+  .content {
+    grid-template-columns: 1fr;
+  }
+}
 '@; Set-Content -Path '.\src\App.css' -Value $content"
\ No newline at end of file
diff --git a/frontend/scripts/generate-version.js b/frontend/scripts/generate-version.js
index babb8f01406614bcd3da29b6d3724d63c0abfd2d..7477ab8c75953bc7924132a840f4b7ab7e981828 100644
--- a/frontend/scripts/generate-version.js
+++ b/frontend/scripts/generate-version.js
@@ -1,19 +1,19 @@
-import { readFileSync, writeFileSync } from "node:fs";
-import { dirname, join } from "node:path";
-import { fileURLToPath } from "node:url";
-
-const root = dirname(fileURLToPath(import.meta.url));
-const frontendRoot = join(root, "..");
-const pkg = JSON.parse(
-  readFileSync(join(frontendRoot, "package.json"), "utf8"),
-);
-const version = pkg.version || "0.0.0";
-const timestamp = new Date()
-  .toISOString()
-  .replace(/[-:]/g, "")
-  .replace(/\.\d+Z$/, "");
-const fullVersion = `${version}-dev.${timestamp}`;
-const content = `export const appVersion = ${JSON.stringify(fullVersion)};\n`;
-
-writeFileSync(join(frontendRoot, "src", "version.ts"), content, "utf8");
-console.log(`Generated version: ${fullVersion}`);
+import { readFileSync, writeFileSync } from "node:fs";
+import { dirname, join } from "node:path";
+import { fileURLToPath } from "node:url";
+
+const root = dirname(fileURLToPath(import.meta.url));
+const frontendRoot = join(root, "..");
+const pkg = JSON.parse(
+  readFileSync(join(frontendRoot, "package.json"), "utf8"),
+);
+const version = pkg.version || "0.0.0";
+const timestamp = new Date()
+  .toISOString()
+  .replace(/[-:]/g, "")
+  .replace(/\.\d+Z$/, "");
+const fullVersion = `${version}-dev.${timestamp}`;
+const content = `export const appVersion = ${JSON.stringify(fullVersion)};\n`;
+
+writeFileSync(join(frontendRoot, "src", "version.ts"), content, "utf8");
+console.log(`Generated version: ${fullVersion}`);
diff --git a/frontend/src/App.css b/frontend/src/App.css
index 88bdd297400b7f41962df107956307b4c822a537..118acc923fb1be3f8fcadf52864bbc27d1c87e5c 100644
--- a/frontend/src/App.css
+++ b/frontend/src/App.css
@@ -1,542 +1,542 @@
-:root {
-  font-family:
-    Inter,
-    ui-sans-serif,
-    system-ui,
-    -apple-system,
-    BlinkMacSystemFont,
-    "Segoe UI",
-    sans-serif;
-  color: var(--brand-black);
-  background: var(--brand-light);
-  line-height: 1.5;
-}
-
-* {
-  box-sizing: border-box;
-}
-
-html,
-body,
-#root {
-  min-height: 100%;
-}
-
-body {
-  margin: 0;
-  background: var(--brand-light);
-  color: var(--brand-black);
-}
-
-button,
-input,
-select,
-textarea {
-  font: inherit;
-}
-
-button {
-  cursor: pointer;
-}
-
-.app-shell {
-  max-width: 1200px;
-  margin: 0 auto;
-  padding: 24px;
-}
-
-.topbar {
-  display: flex;
-  flex-wrap: wrap;
-  justify-content: space-between;
-  align-items: center;
-  gap: 16px;
-  padding: 22px 24px;
-  background: var(--brand-surface);
-  border: 1px solid var(--brand-border);
-  border-radius: 18px;
-}
-
-.topbar h1 {
-  margin: 0;
-  font-size: clamp(1.9rem, 2.5vw, 2.6rem);
-}
-
-.topbar p {
-  margin: 6px 0 0;
-  color: var(--brand-gray);
-}
-
-.topbar-nav {
-  display: flex;
-  flex-wrap: wrap;
-  gap: 10px;
-}
-
-.topbar-nav a {
-  display: inline-flex;
-  align-items: center;
-  justify-content: center;
-  padding: 10px 14px;
-  border-radius: 14px;
-  background: var(--brand-surface);
-  color: var(--brand-black);
-  text-decoration: none;
-  border: 1px solid transparent;
-  transition:
-    background 0.2s ease,
-    border-color 0.2s ease;
-}
-
-.topbar-nav a:hover {
-  background: #ffffff;
-  border-color: #d1d5db;
-}
-
-.content {
-  display: grid;
-  gap: 24px;
-  grid-template-columns: 1.2fr 1.8fr;
-  margin-top: 24px;
-}
-
-.route-index,
-.panel,
-.viewer-panel,
-.bridge-panel,
-.room-setup-dropzone,
-.room-setup-card,
-.room-setup-preview {
-  background: var(--brand-surface);
-  border: 1px solid var(--brand-border);
-  border-radius: 20px;
-}
-
-.route-index,
-.panel,
-.viewer-panel,
-.bridge-panel,
-.room-setup-card {
-  padding: 22px;
-}
-
-.route-index h2,
-.panel h2,
-.viewer-panel h2,
-.room-setup-copy h1,
-.room-setup-bottom h2 {
-  margin: 0 0 16px;
-}
-
-.route-index p,
-.room-setup-features li,
-.room-setup-drop-content p,
-.room-setup-drop-content small,
-.room-setup-card h3,
-.topbar p,
-.error-box,
-.empty-state {
-  color: #475569;
-}
-
-.route-index ul,
-.room-setup-features,
-.room-setup-filters,
-.room-setup-grid {
-  margin: 0;
-  padding: 0;
-  list-style: none;
-}
-
-.route-index ul {
-  display: grid;
-  gap: 12px;
-}
-
-.form-row {
-  display: grid;
-  gap: 14px;
-  margin-bottom: 20px;
-}
-
-label {
-  font-size: 0.95rem;
-  color: var(--brand-black);
-}
-
-input,
-select,
-textarea {
-  width: 100%;
-  padding: 14px 16px;
-  border-radius: 14px;
-  border: 1px solid #d1d5db;
-  background: #ffffff;
-  color: #111827;
-}
-
-input:focus,
-select:focus,
-textarea:focus {
-  outline: 2px solid var(--brand-blue);
-  outline-offset: 2px;
-}
-
-.button,
-.button-primary,
-.button-secondary {
-  display: inline-flex;
-  align-items: center;
-  justify-content: center;
-  gap: 10px;
-  border-radius: 16px;
-  padding: 14px 18px;
-  font-weight: 700;
-  border: 1px solid transparent;
-  transition: all 0.2s ease;
-}
-
-.button {
-  background: var(--brand-black);
-  color: var(--brand-surface);
-}
-
-.button:hover {
-  opacity: 0.95;
-}
-
-.button.secondary,
-.button-secondary {
-  background: var(--brand-surface);
-  color: var(--brand-black);
-  border-color: var(--brand-border);
-}
-
-.error-box {
-  margin-top: 16px;
-  padding: 16px;
-  border-radius: 16px;
-  background: #fef2f2;
-  color: #991b1b;
-  border: 1px solid #fecaca;
-}
-
-.empty-state {
-  min-height: 220px;
-  display: grid;
-  place-content: center;
-  border: 1px dashed #d1d5db;
-  border-radius: 18px;
-}
-
-.room-setup {
-  background: var(--brand-light);
-}
-
-.room-setup-inner {
-  max-width: 1200px;
-  margin: 0 auto;
-  padding: 32px 24px;
-}
-
-.room-setup-header {
-  display: flex;
-  justify-content: flex-end;
-  margin-bottom: 24px;
-}
-
-.room-setup-close {
-  border: none;
-  background: transparent;
-  color: var(--brand-black);
-  padding: 10px;
-  border-radius: 999px;
-  cursor: pointer;
-}
-
-.room-setup-close:hover {
-  background: var(--brand-border);
-}
-
-.room-setup-top {
-  display: grid;
-  gap: 24px;
-  grid-template-columns: 1.1fr 0.9fr;
-  margin-bottom: 40px;
-}
-
-.room-setup-copy h1 {
-  margin: 0 0 24px;
-  font-size: clamp(2rem, 2.5vw, 3rem);
-  color: #111827;
-}
-
-.room-setup-features {
-  display: grid;
-  gap: 16px;
-}
-
-.room-setup-features li {
-  display: flex;
-  align-items: center;
-  gap: 12px;
-  color: #475569;
-}
-
-.room-setup-actions {
-  display: grid;
-  gap: 16px;
-}
-
-.button-primary {
-  background: #111827;
-  color: #ffffff;
-}
-
-.button-primary:hover {
-  opacity: 0.95;
-}
-
-.button-secondary {
-  background: #ffffff;
-  color: #334155;
-  border-color: #d1d5db;
-}
-
-.button-secondary:hover {
-  background: #f3f4f6;
-}
-
-.button-icon-border {
-  display: inline-flex;
-  align-items: center;
-  justify-content: center;
-  width: 30px;
-  height: 30px;
-  border-radius: 10px;
-  border: 1px solid #d1d5db;
-}
-
-.room-setup-dropzone {
-  position: relative;
-  min-height: 420px;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  transition: all 0.2s ease;
-  padding: 24px;
-  border: 1px dashed #d1d5db;
-  border-radius: 28px;
-}
-
-.room-setup-dropzone.dragging {
-  background: #f3f4f6;
-}
-
-.room-setup-file-input {
-  position: absolute;
-  inset: 0;
-  width: 100%;
-  height: 100%;
-  opacity: 0;
-  cursor: pointer;
-}
-
-.room-setup-drop-content {
-  text-align: center;
-}
-
-.room-setup-drop-icon {
-  display: inline-flex;
-  align-items: center;
-  justify-content: center;
-  width: 72px;
-  height: 72px;
-  border-radius: 999px;
-  background: #e2e8f0;
-  color: #64748b;
-  margin-bottom: 18px;
-}
-
-.room-setup-drop-icon.active {
-  background: #dbeafe;
-  color: #1e293b;
-}
-
-.room-setup-drop-content h3 {
-  margin: 0 0 8px;
-  font-size: 1.2rem;
-}
-
-.room-setup-drop-content p,
-.room-setup-drop-content small {
-  margin: 0;
-  color: #64748b;
-}
-
-.room-setup-preview {
-  position: relative;
-  width: 100%;
-  height: 100%;
-}
-
-.room-setup-preview img {
-  width: 100%;
-  height: 100%;
-  object-fit: cover;
-}
-
-.room-setup-preview-overlay {
-  position: absolute;
-  inset: 0;
-  background: rgba(255, 255, 255, 0.85);
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  opacity: 0;
-  transition: opacity 0.2s ease;
-}
-
-.room-setup-preview:hover .room-setup-preview-overlay {
-  opacity: 1;
-}
-
-.button-delete {
-  background: #ffffff;
-  color: #111827;
-  padding: 12px 16px;
-  border-radius: 14px;
-  font-weight: 600;
-  border: 1px solid #d1d5db;
-}
-
-.room-setup-bottom h2 {
-  margin: 0 0 24px;
-}
-
-.room-setup-filters {
-  display: flex;
-  flex-wrap: wrap;
-  gap: 10px;
-  margin-bottom: 24px;
-}
-
-.room-setup-filter {
-  border: 1px solid #d1d5db;
-  background: #ffffff;
-  color: #334155;
-  padding: 10px 16px;
-  border-radius: 16px;
-  cursor: pointer;
-  transition: all 0.2s ease;
-}
-
-.room-setup-filter.active {
-  background: #f3f4f6;
-}
-
-.room-setup-grid {
-  display: grid;
-  grid-template-columns: repeat(1, minmax(0, 1fr));
-  gap: 20px;
-}
-
-.room-setup-card {
-  overflow: hidden;
-  border-radius: 24px;
-  background: #ffffff;
-  box-shadow: 0 8px 20px rgba(15, 23, 42, 0.06);
-}
-
-.room-setup-card-image {
-  position: relative;
-  aspect-ratio: 4 / 3;
-  overflow: hidden;
-}
-
-.room-setup-card-image img {
-  width: 100%;
-  height: 100%;
-  object-fit: cover;
-  transition: transform 0.4s ease;
-}
-
-.room-setup-card:hover .room-setup-card-image img {
-  transform: scale(1.04);
-}
-
-.room-setup-card h3 {
-  margin: 16px;
-  font-size: 1rem;
-  color: #334155;
-}
-
-@media (max-width: 960px) {
-  .room-setup-top {
-    grid-template-columns: 1fr;
-  }
-
-  .room-setup-grid {
-    grid-template-columns: repeat(2, minmax(0, 1fr));
-  }
-}
-
-@media (max-width: 640px) {
-  .room-setup-inner {
-    padding: 20px 16px;
-  }
-
-  .room-setup-grid {
-    grid-template-columns: 1fr;
-  }
-}
-
-.app-version-badge {
-  position: fixed;
-  right: 0;
-  bottom: 0;
-  padding: 6px 10px;
-  border-radius: 12px 0 0 0;
-  background: rgba(255, 255, 255, 0.95);
-  border: 1px solid #e5e7eb;
-  color: #475569;
-  font-size: 0.78rem;
-  text-align: right;
-  box-shadow: 0 8px 20px rgba(15, 23, 42, 0.08);
-  z-index: 1000;
-}
-
-.app-version-badge:hover {
-  opacity: 1;
-}
-
-.app-version-badge span {
-  display: block;
-  font-weight: 700;
-  color: #111827;
-}
-
-.app-version-badge small {
-  display: block;
-  margin-top: 1px;
-  color: #6b7280;
-}
-
-@media (max-width: 640px) {
-  .app-version-badge {
-    right: 6px;
-    bottom: 6px;
-    padding: 5px 8px;
-    font-size: 0.72rem;
-  }
-
-  .app-version-badge small {
-    margin-top: 0.5px;
-  }
-}
-
-@media (max-width: 900px) {
-  .content {
-    grid-template-columns: 1fr;
-  }
-}
+:root {
+  font-family:
+    Inter,
+    ui-sans-serif,
+    system-ui,
+    -apple-system,
+    BlinkMacSystemFont,
+    "Segoe UI",
+    sans-serif;
+  color: var(--brand-black);
+  background: var(--brand-light);
+  line-height: 1.5;
+}
+
+* {
+  box-sizing: border-box;
+}
+
+html,
+body,
+#root {
+  min-height: 100%;
+}
+
+body {
+  margin: 0;
+  background: var(--brand-light);
+  color: var(--brand-black);
+}
+
+button,
+input,
+select,
+textarea {
+  font: inherit;
+}
+
+button {
+  cursor: pointer;
+}
+
+.app-shell {
+  max-width: 1200px;
+  margin: 0 auto;
+  padding: 24px;
+}
+
+.topbar {
+  display: flex;
+  flex-wrap: wrap;
+  justify-content: space-between;
+  align-items: center;
+  gap: 16px;
+  padding: 22px 24px;
+  background: var(--brand-surface);
+  border: 1px solid var(--brand-border);
+  border-radius: 18px;
+}
+
+.topbar h1 {
+  margin: 0;
+  font-size: clamp(1.9rem, 2.5vw, 2.6rem);
+}
+
+.topbar p {
+  margin: 6px 0 0;
+  color: var(--brand-gray);
+}
+
+.topbar-nav {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 10px;
+}
+
+.topbar-nav a {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  padding: 10px 14px;
+  border-radius: 14px;
+  background: var(--brand-surface);
+  color: var(--brand-black);
+  text-decoration: none;
+  border: 1px solid transparent;
+  transition:
+    background 0.2s ease,
+    border-color 0.2s ease;
+}
+
+.topbar-nav a:hover {
+  background: #ffffff;
+  border-color: #d1d5db;
+}
+
+.content {
+  display: grid;
+  gap: 24px;
+  grid-template-columns: 1.2fr 1.8fr;
+  margin-top: 24px;
+}
+
+.route-index,
+.panel,
+.viewer-panel,
+.bridge-panel,
+.room-setup-dropzone,
+.room-setup-card,
+.room-setup-preview {
+  background: var(--brand-surface);
+  border: 1px solid var(--brand-border);
+  border-radius: 20px;
+}
+
+.route-index,
+.panel,
+.viewer-panel,
+.bridge-panel,
+.room-setup-card {
+  padding: 22px;
+}
+
+.route-index h2,
+.panel h2,
+.viewer-panel h2,
+.room-setup-copy h1,
+.room-setup-bottom h2 {
+  margin: 0 0 16px;
+}
+
+.route-index p,
+.room-setup-features li,
+.room-setup-drop-content p,
+.room-setup-drop-content small,
+.room-setup-card h3,
+.topbar p,
+.error-box,
+.empty-state {
+  color: #475569;
+}
+
+.route-index ul,
+.room-setup-features,
+.room-setup-filters,
+.room-setup-grid {
+  margin: 0;
+  padding: 0;
+  list-style: none;
+}
+
+.route-index ul {
+  display: grid;
+  gap: 12px;
+}
+
+.form-row {
+  display: grid;
+  gap: 14px;
+  margin-bottom: 20px;
+}
+
+label {
+  font-size: 0.95rem;
+  color: var(--brand-black);
+}
+
+input,
+select,
+textarea {
+  width: 100%;
+  padding: 14px 16px;
+  border-radius: 14px;
+  border: 1px solid #d1d5db;
+  background: #ffffff;
+  color: #111827;
+}
+
+input:focus,
+select:focus,
+textarea:focus {
+  outline: 2px solid var(--brand-blue);
+  outline-offset: 2px;
+}
+
+.button,
+.button-primary,
+.button-secondary {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  gap: 10px;
+  border-radius: 16px;
+  padding: 14px 18px;
+  font-weight: 700;
+  border: 1px solid transparent;
+  transition: all 0.2s ease;
+}
+
+.button {
+  background: var(--brand-black);
+  color: var(--brand-surface);
+}
+
+.button:hover {
+  opacity: 0.95;
+}
+
+.button.secondary,
+.button-secondary {
+  background: var(--brand-surface);
+  color: var(--brand-black);
+  border-color: var(--brand-border);
+}
+
+.error-box {
+  margin-top: 16px;
+  padding: 16px;
+  border-radius: 16px;
+  background: #fef2f2;
+  color: #991b1b;
+  border: 1px solid #fecaca;
+}
+
+.empty-state {
+  min-height: 220px;
+  display: grid;
+  place-content: center;
+  border: 1px dashed #d1d5db;
+  border-radius: 18px;
+}
+
+.room-setup {
+  background: var(--brand-light);
+}
+
+.room-setup-inner {
+  max-width: 1200px;
+  margin: 0 auto;
+  padding: 32px 24px;
+}
+
+.room-setup-header {
+  display: flex;
+  justify-content: flex-end;
+  margin-bottom: 24px;
+}
+
+.room-setup-close {
+  border: none;
+  background: transparent;
+  color: var(--brand-black);
+  padding: 10px;
+  border-radius: 999px;
+  cursor: pointer;
+}
+
+.room-setup-close:hover {
+  background: var(--brand-border);
+}
+
+.room-setup-top {
+  display: grid;
+  gap: 24px;
+  grid-template-columns: 1.1fr 0.9fr;
+  margin-bottom: 40px;
+}
+
+.room-setup-copy h1 {
+  margin: 0 0 24px;
+  font-size: clamp(2rem, 2.5vw, 3rem);
+  color: #111827;
+}
+
+.room-setup-features {
+  display: grid;
+  gap: 16px;
+}
+
+.room-setup-features li {
+  display: flex;
+  align-items: center;
+  gap: 12px;
+  color: #475569;
+}
+
+.room-setup-actions {
+  display: grid;
+  gap: 16px;
+}
+
+.button-primary {
+  background: #111827;
+  color: #ffffff;
+}
+
+.button-primary:hover {
+  opacity: 0.95;
+}
+
+.button-secondary {
+  background: #ffffff;
+  color: #334155;
+  border-color: #d1d5db;
+}
+
+.button-secondary:hover {
+  background: #f3f4f6;
+}
+
+.button-icon-border {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  width: 30px;
+  height: 30px;
+  border-radius: 10px;
+  border: 1px solid #d1d5db;
+}
+
+.room-setup-dropzone {
+  position: relative;
+  min-height: 420px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  transition: all 0.2s ease;
+  padding: 24px;
+  border: 1px dashed #d1d5db;
+  border-radius: 28px;
+}
+
+.room-setup-dropzone.dragging {
+  background: #f3f4f6;
+}
+
+.room-setup-file-input {
+  position: absolute;
+  inset: 0;
+  width: 100%;
+  height: 100%;
+  opacity: 0;
+  cursor: pointer;
+}
+
+.room-setup-drop-content {
+  text-align: center;
+}
+
+.room-setup-drop-icon {
+  display: inline-flex;
+  align-items: center;
+  justify-content: center;
+  width: 72px;
+  height: 72px;
+  border-radius: 999px;
+  background: #e2e8f0;
+  color: #64748b;
+  margin-bottom: 18px;
+}
+
+.room-setup-drop-icon.active {
+  background: #dbeafe;
+  color: #1e293b;
+}
+
+.room-setup-drop-content h3 {
+  margin: 0 0 8px;
+  font-size: 1.2rem;
+}
+
+.room-setup-drop-content p,
+.room-setup-drop-content small {
+  margin: 0;
+  color: #64748b;
+}
+
+.room-setup-preview {
+  position: relative;
+  width: 100%;
+  height: 100%;
+}
+
+.room-setup-preview img {
+  width: 100%;
+  height: 100%;
+  object-fit: cover;
+}
+
+.room-setup-preview-overlay {
+  position: absolute;
+  inset: 0;
+  background: rgba(255, 255, 255, 0.85);
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  opacity: 0;
+  transition: opacity 0.2s ease;
+}
+
+.room-setup-preview:hover .room-setup-preview-overlay {
+  opacity: 1;
+}
+
+.button-delete {
+  background: #ffffff;
+  color: #111827;
+  padding: 12px 16px;
+  border-radius: 14px;
+  font-weight: 600;
+  border: 1px solid #d1d5db;
+}
+
+.room-setup-bottom h2 {
+  margin: 0 0 24px;
+}
+
+.room-setup-filters {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 10px;
+  margin-bottom: 24px;
+}
+
+.room-setup-filter {
+  border: 1px solid #d1d5db;
+  background: #ffffff;
+  color: #334155;
+  padding: 10px 16px;
+  border-radius: 16px;
+  cursor: pointer;
+  transition: all 0.2s ease;
+}
+
+.room-setup-filter.active {
+  background: #f3f4f6;
+}
+
+.room-setup-grid {
+  display: grid;
+  grid-template-columns: repeat(1, minmax(0, 1fr));
+  gap: 20px;
+}
+
+.room-setup-card {
+  overflow: hidden;
+  border-radius: 24px;
+  background: #ffffff;
+  box-shadow: 0 8px 20px rgba(15, 23, 42, 0.06);
+}
+
+.room-setup-card-image {
+  position: relative;
+  aspect-ratio: 4 / 3;
+  overflow: hidden;
+}
+
+.room-setup-card-image img {
+  width: 100%;
+  height: 100%;
+  object-fit: cover;
+  transition: transform 0.4s ease;
+}
+
+.room-setup-card:hover .room-setup-card-image img {
+  transform: scale(1.04);
+}
+
+.room-setup-card h3 {
+  margin: 16px;
+  font-size: 1rem;
+  color: #334155;
+}
+
+@media (max-width: 960px) {
+  .room-setup-top {
+    grid-template-columns: 1fr;
+  }
+
+  .room-setup-grid {
+    grid-template-columns: repeat(2, minmax(0, 1fr));
+  }
+}
+
+@media (max-width: 640px) {
+  .room-setup-inner {
+    padding: 20px 16px;
+  }
+
+  .room-setup-grid {
+    grid-template-columns: 1fr;
+  }
+}
+
+.app-version-badge {
+  position: fixed;
+  right: 0;
+  bottom: 0;
+  padding: 6px 10px;
+  border-radius: 12px 0 0 0;
+  background: rgba(255, 255, 255, 0.95);
+  border: 1px solid #e5e7eb;
+  color: #475569;
+  font-size: 0.78rem;
+  text-align: right;
+  box-shadow: 0 8px 20px rgba(15, 23, 42, 0.08);
+  z-index: 1000;
+}
+
+.app-version-badge:hover {
+  opacity: 1;
+}
+
+.app-version-badge span {
+  display: block;
+  font-weight: 700;
+  color: #111827;
+}
+
+.app-version-badge small {
+  display: block;
+  margin-top: 1px;
+  color: #6b7280;
+}
+
+@media (max-width: 640px) {
+  .app-version-badge {
+    right: 6px;
+    bottom: 6px;
+    padding: 5px 8px;
+    font-size: 0.72rem;
+  }
+
+  .app-version-badge small {
+    margin-top: 0.5px;
+  }
+}
+
+@media (max-width: 900px) {
+  .content {
+    grid-template-columns: 1fr;
+  }
+}
diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx
index 26449f7f4cae32c8bf373c4b486182a3a2b7972a..69a7cf256e83839a057a802a9d2370335c36e40d 100644
--- a/frontend/src/App.tsx
+++ b/frontend/src/App.tsx
@@ -1,20 +1,20 @@
-import { Routes, Route, Navigate } from "react-router-dom";
-import SettingsPage from "./features/settings/SettingsPage";
-import RoomSetup from "./features/roomSetup/RoomSetup";
-import RoomVisualizer from "./features/roomVisualizer/RoomVisualizer";
-import SharedView from "./features/shared/SharedView";
-import "./App.css";
-
-export default function App() {
-  return (
-    <div className="min-h-screen bg-[#f4f8ff] text-[#333333]">
-      <Routes>
-        <Route path="/" element={<RoomSetup />} />
-        <Route path="/visualizer" element={<RoomVisualizer />} />
-        <Route path="/share/:shareId" element={<SharedView />} />
-        <Route path="/settings" element={<SettingsPage />} />
-        <Route path="*" element={<Navigate to="/" replace />} />
-      </Routes>
-    </div>
-  );
-}
+import { Routes, Route, Navigate } from "react-router-dom";
+import SettingsPage from "./features/settings/SettingsPage";
+import RoomSetup from "./features/roomSetup/RoomSetup";
+import RoomVisualizer from "./features/roomVisualizer/RoomVisualizer";
+import SharedView from "./features/shared/SharedView";
+import "./App.css";
+
+export default function App() {
+  return (
+    <div className="min-h-screen bg-[#f4f8ff] text-[#333333]">
+      <Routes>
+        <Route path="/" element={<RoomSetup />} />
+        <Route path="/visualizer" element={<RoomVisualizer />} />
+        <Route path="/share/:shareId" element={<SharedView />} />
+        <Route path="/settings" element={<SettingsPage />} />
+        <Route path="*" element={<Navigate to="/" replace />} />
+      </Routes>
+    </div>
+  );
+}
diff --git a/frontend/src/api/client.ts b/frontend/src/api/client.ts
index a361c51ffe711eb7c838f18a79c07278dbd04d4b..a32d51510f0a7c09c21e5d3baf5be034573ed8ec 100644
--- a/frontend/src/api/client.ts
+++ b/frontend/src/api/client.ts
@@ -1,100 +1,100 @@
-import type { ClientData } from "../types";
-
-export const DEV_API_BASE = "http://localhost:8000";
-export const API_BASE =
-  import.meta.env.VITE_API_BASE_URL ??
-  (import.meta.env.DEV ? DEV_API_BASE : "");
-const DEV_CLIENT_ID = "ID_UNICO_DEL_CLIENTE_001";
-
-export interface ClientConfigResponse {
-  cliente: ClientData;
-  query: string;
-}
-
-export function getApiBase(customApiBase?: string) {
-  return customApiBase?.trim() ? customApiBase : API_BASE;
-}
-
-export function buildApiUrl(path: string, customApiBase?: string) {
-  return `${getApiBase(customApiBase)}${path}`;
-}
-
-export async function fetchClientConfig(
-  token: string,
-  clientId: string,
-  customApiBase?: string,
-  useDevToken = true,
-): Promise<ClientConfigResponse> {
-  let finalToken = token;
-  const finalClientId = clientId;
-
-  if (!finalToken && !finalClientId) {
-    if (!import.meta.env.DEV || !useDevToken) {
-      throw new Error("No se encontró el token o key en la URL.");
-    }
-
-    const tokenRes = await fetch(buildApiUrl("/api/token", customApiBase), {
-      method: "POST",
-      headers: { "Content-Type": "application/x-www-form-urlencoded" },
-      body: `client_id=${encodeURIComponent(DEV_CLIENT_ID)}`,
-    });
-
-    if (!tokenRes.ok) {
-      throw new Error("No se pudo generar el token de prueba en desarrollo.");
-    }
-
-    const tokenData = await tokenRes.json();
-    finalToken = tokenData.token;
-  }
-
-  const query = finalToken
-    ? `token=${encodeURIComponent(finalToken)}`
-    : `client_id=${encodeURIComponent(finalClientId)}`;
-
-  const res = await fetch(buildApiUrl(`/config?${query}`, customApiBase));
-  if (!res.ok) {
-    const text = await res.text();
-    throw new Error(
-      `No se pudo obtener la configuración del cliente. ${res.status} ${text}`,
-    );
-  }
-
-  const cliente = await res.json();
-  return { cliente, query };
-}
-
-export interface UploadImageResponse {
-  filename: string;
-  [key: string]: unknown;
-}
-
-export async function uploadRoomImage(
-  file: File,
-  customApiBase?: string,
-): Promise<UploadImageResponse> {
-  const formData = new FormData();
-  formData.append("file", file);
-
-  const response = await fetch(
-    buildApiUrl("/api/upload-image", customApiBase),
-    {
-      method: "POST",
-      body: formData,
-    },
-  );
-
-  if (!response.ok) {
-    const text = await response.text();
-    throw new Error(text || "Error al subir la imagen");
-  }
-
-  return response.json();
-}
-
-export async function startSession(query: string, customApiBase?: string) {
-  await fetch(buildApiUrl("/session/start", customApiBase), {
-    method: "POST",
-    headers: { "Content-Type": "application/x-www-form-urlencoded" },
-    body: query,
-  });
-}
+import type { ClientData } from "../types";
+
+export const DEV_API_BASE = "http://localhost:8000";
+export const API_BASE =
+  import.meta.env.VITE_API_BASE_URL ??
+  (import.meta.env.DEV ? DEV_API_BASE : "");
+const DEV_CLIENT_ID = "ID_UNICO_DEL_CLIENTE_001";
+
+export interface ClientConfigResponse {
+  cliente: ClientData;
+  query: string;
+}
+
+export function getApiBase(customApiBase?: string) {
+  return customApiBase?.trim() ? customApiBase : API_BASE;
+}
+
+export function buildApiUrl(path: string, customApiBase?: string) {
+  return `${getApiBase(customApiBase)}${path}`;
+}
+
+export async function fetchClientConfig(
+  token: string,
+  clientId: string,
+  customApiBase?: string,
+  useDevToken = true,
+): Promise<ClientConfigResponse> {
+  let finalToken = token;
+  const finalClientId = clientId;
+
+  if (!finalToken && !finalClientId) {
+    if (!import.meta.env.DEV || !useDevToken) {
+      throw new Error("No se encontró el token o key en la URL.");
+    }
+
+    const tokenRes = await fetch(buildApiUrl("/api/token", customApiBase), {
+      method: "POST",
+      headers: { "Content-Type": "application/x-www-form-urlencoded" },
+      body: `client_id=${encodeURIComponent(DEV_CLIENT_ID)}`,
+    });
+
+    if (!tokenRes.ok) {
+      throw new Error("No se pudo generar el token de prueba en desarrollo.");
+    }
+
+    const tokenData = await tokenRes.json();
+    finalToken = tokenData.token;
+  }
+
+  const query = finalToken
+    ? `token=${encodeURIComponent(finalToken)}`
+    : `client_id=${encodeURIComponent(finalClientId)}`;
+
+  const res = await fetch(buildApiUrl(`/config?${query}`, customApiBase));
+  if (!res.ok) {
+    const text = await res.text();
+    throw new Error(
+      `No se pudo obtener la configuración del cliente. ${res.status} ${text}`,
+    );
+  }
+
+  const cliente = await res.json();
+  return { cliente, query };
+}
+
+export interface UploadImageResponse {
+  filename: string;
+  [key: string]: unknown;
+}
+
+export async function uploadRoomImage(
+  file: File,
+  customApiBase?: string,
+): Promise<UploadImageResponse> {
+  const formData = new FormData();
+  formData.append("file", file);
+
+  const response = await fetch(
+    buildApiUrl("/api/upload-image", customApiBase),
+    {
+      method: "POST",
+      body: formData,
+    },
+  );
+
+  if (!response.ok) {
+    const text = await response.text();
+    throw new Error(text || "Error al subir la imagen");
+  }
+
+  return response.json();
+}
+
+export async function startSession(query: string, customApiBase?: string) {
+  await fetch(buildApiUrl("/session/start", customApiBase), {
+    method: "POST",
+    headers: { "Content-Type": "application/x-www-form-urlencoded" },
+    body: query,
+  });
+}
diff --git a/frontend/src/assets/vite.svg b/frontend/src/assets/vite.svg
index 25ee512b1d236712b9dcd251ee1bc7253b5a62de..5101b674df391399da71c767aa5c976426c9dc7a 100644
--- a/frontend/src/assets/vite.svg
+++ b/frontend/src/assets/vite.svg
@@ -1 +1 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="77" height="47" fill="none" aria-labelledby="vite-logo-title" viewBox="0 0 77 47"><title id="vite-logo-title">Vite</title><style>.parenthesis{fill:#000}@media (prefers-color-scheme:dark){.parenthesis{fill:#fff}}</style><path fill="#9135ff" d="M40.151 45.71c-.663.844-2.02.374-2.02-.699V34.708a2.26 2.26 0 0 0-2.262-2.262H24.493c-.92 0-1.457-1.04-.92-1.788l7.479-10.471c1.07-1.498 0-3.578-1.842-3.578H15.443c-.92 0-1.456-1.04-.92-1.788l9.696-13.576c.213-.297.556-.474.92-.474h28.894c.92 0 1.456 1.04.92 1.788l-7.48 10.472c-1.07 1.497 0 3.578 1.842 3.578h11.376c.944 0 1.474 1.087.89 1.83L40.153 45.712z"/><mask id="a" width="48" height="47" x="14" y="0" maskUnits="userSpaceOnUse" style="mask-type:alpha"><path fill="#000" d="M40.047 45.71c-.663.843-2.02.374-2.02-.699V34.708a2.26 2.26 0 0 0-2.262-2.262H24.389c-.92 0-1.457-1.04-.92-1.788l7.479-10.472c1.07-1.497 0-3.578-1.842-3.578H15.34c-.92 0-1.456-1.04-.92-1.788l9.696-13.575c.213-.297.556-.474.92-.474H53.93c.92 0 1.456 1.04.92 1.788L47.37 13.03c-1.07 1.498 0 3.578 1.842 3.578h11.376c.944 0 1.474 1.088.89 1.831L40.049 45.712z"/></mask><g mask="url(#a)"><g filter="url(#b)"><ellipse cx="5.508" cy="14.704" fill="#eee6ff" rx="5.508" ry="14.704" transform="rotate(269.814 20.96 11.29)scale(-1 1)"/></g><g filter="url(#c)"><ellipse cx="10.399" cy="29.851" fill="#eee6ff" rx="10.399" ry="29.851" transform="rotate(89.814 -16.902 -8.275)scale(1 -1)"/></g><g filter="url(#d)"><ellipse cx="5.508" cy="30.487" fill="#8900ff" rx="5.508" ry="30.487" transform="rotate(89.814 -19.197 -7.127)scale(1 -1)"/></g><g filter="url(#e)"><ellipse cx="5.508" cy="30.599" fill="#8900ff" rx="5.508" ry="30.599" transform="rotate(89.814 -25.928 4.177)scale(1 -1)"/></g><g filter="url(#f)"><ellipse cx="5.508" cy="30.599" fill="#8900ff" rx="5.508" ry="30.599" transform="rotate(89.814 -25.738 5.52)scale(1 -1)"/></g><g filter="url(#g)"><ellipse cx="14.072" cy="22.078" fill="#eee6ff" rx="14.072" ry="22.078" transform="rotate(93.35 31.245 55.578)scale(-1 1)"/></g><g filter="url(#h)"><ellipse cx="3.47" cy="21.501" fill="#8900ff" rx="3.47" ry="21.501" transform="rotate(89.009 35.419 55.202)scale(-1 1)"/></g><g filter="url(#i)"><ellipse cx="3.47" cy="21.501" fill="#8900ff" rx="3.47" ry="21.501" transform="rotate(89.009 35.419 55.202)scale(-1 1)"/></g><g filter="url(#j)"><ellipse cx="14.592" cy="9.743" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(39.51 14.592 9.743)"/></g><g filter="url(#k)"><ellipse cx="61.728" cy="-5.321" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(37.892 61.728 -5.32)"/></g><g filter="url(#l)"><ellipse cx="55.618" cy="7.104" fill="#00c2ff" rx="5.971" ry="9.665" transform="rotate(37.892 55.618 7.104)"/></g><g filter="url(#m)"><ellipse cx="12.326" cy="39.103" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(37.892 12.326 39.103)"/></g><g filter="url(#n)"><ellipse cx="12.326" cy="39.103" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(37.892 12.326 39.103)"/></g><g filter="url(#o)"><ellipse cx="49.857" cy="30.678" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(37.892 49.857 30.678)"/></g><g filter="url(#p)"><ellipse cx="52.623" cy="33.171" fill="#00c2ff" rx="5.971" ry="15.297" transform="rotate(37.892 52.623 33.17)"/></g></g><path d="M6.919 0c-9.198 13.166-9.252 33.575 0 46.789h6.215c-9.25-13.214-9.196-33.623 0-46.789zm62.424 0h-6.215c9.198 13.166 9.252 33.575 0 46.789h6.215c9.25-13.214 9.196-33.623 0-46.789" class="parenthesis"/><defs><filter id="b" width="60.045" height="41.654" x="-5.564" y="16.92" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="7.659"/></filter><filter id="c" width="90.34" height="51.437" x="-40.407" y="-6.762" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="7.659"/></filter><filter id="d" width="79.355" height="29.4" x="-35.435" y="2.801" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="e" width="79.579" height="29.4" x="-30.84" y="20.8" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="f" width="79.579" height="29.4" x="-29.307" y="21.949" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="g" width="74.749" height="58.852" x="29.961" y="-17.13" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="7.659"/></filter><filter id="h" width="61.377" height="25.362" x="37.754" y="3.055" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="i" width="61.377" height="25.362" x="37.754" y="3.055" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="j" width="56.045" height="63.649" x="-13.43" y="-22.082" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="k" width="54.814" height="64.646" x="34.321" y="-37.644" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="l" width="33.541" height="35.313" x="38.847" y="-10.552" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="m" width="54.814" height="64.646" x="-15.081" y="6.78" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="n" width="54.814" height="64.646" x="-15.081" y="6.78" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="o" width="54.814" height="64.646" x="22.45" y="-1.645" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="p" width="39.409" height="43.623" x="32.919" y="11.36" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter></defs></svg>
+<svg xmlns="http://www.w3.org/2000/svg" width="77" height="47" fill="none" aria-labelledby="vite-logo-title" viewBox="0 0 77 47"><title id="vite-logo-title">Vite</title><style>.parenthesis{fill:#000}@media (prefers-color-scheme:dark){.parenthesis{fill:#fff}}</style><path fill="#9135ff" d="M40.151 45.71c-.663.844-2.02.374-2.02-.699V34.708a2.26 2.26 0 0 0-2.262-2.262H24.493c-.92 0-1.457-1.04-.92-1.788l7.479-10.471c1.07-1.498 0-3.578-1.842-3.578H15.443c-.92 0-1.456-1.04-.92-1.788l9.696-13.576c.213-.297.556-.474.92-.474h28.894c.92 0 1.456 1.04.92 1.788l-7.48 10.472c-1.07 1.497 0 3.578 1.842 3.578h11.376c.944 0 1.474 1.087.89 1.83L40.153 45.712z"/><mask id="a" width="48" height="47" x="14" y="0" maskUnits="userSpaceOnUse" style="mask-type:alpha"><path fill="#000" d="M40.047 45.71c-.663.843-2.02.374-2.02-.699V34.708a2.26 2.26 0 0 0-2.262-2.262H24.389c-.92 0-1.457-1.04-.92-1.788l7.479-10.472c1.07-1.497 0-3.578-1.842-3.578H15.34c-.92 0-1.456-1.04-.92-1.788l9.696-13.575c.213-.297.556-.474.92-.474H53.93c.92 0 1.456 1.04.92 1.788L47.37 13.03c-1.07 1.498 0 3.578 1.842 3.578h11.376c.944 0 1.474 1.088.89 1.831L40.049 45.712z"/></mask><g mask="url(#a)"><g filter="url(#b)"><ellipse cx="5.508" cy="14.704" fill="#eee6ff" rx="5.508" ry="14.704" transform="rotate(269.814 20.96 11.29)scale(-1 1)"/></g><g filter="url(#c)"><ellipse cx="10.399" cy="29.851" fill="#eee6ff" rx="10.399" ry="29.851" transform="rotate(89.814 -16.902 -8.275)scale(1 -1)"/></g><g filter="url(#d)"><ellipse cx="5.508" cy="30.487" fill="#8900ff" rx="5.508" ry="30.487" transform="rotate(89.814 -19.197 -7.127)scale(1 -1)"/></g><g filter="url(#e)"><ellipse cx="5.508" cy="30.599" fill="#8900ff" rx="5.508" ry="30.599" transform="rotate(89.814 -25.928 4.177)scale(1 -1)"/></g><g filter="url(#f)"><ellipse cx="5.508" cy="30.599" fill="#8900ff" rx="5.508" ry="30.599" transform="rotate(89.814 -25.738 5.52)scale(1 -1)"/></g><g filter="url(#g)"><ellipse cx="14.072" cy="22.078" fill="#eee6ff" rx="14.072" ry="22.078" transform="rotate(93.35 31.245 55.578)scale(-1 1)"/></g><g filter="url(#h)"><ellipse cx="3.47" cy="21.501" fill="#8900ff" rx="3.47" ry="21.501" transform="rotate(89.009 35.419 55.202)scale(-1 1)"/></g><g filter="url(#i)"><ellipse cx="3.47" cy="21.501" fill="#8900ff" rx="3.47" ry="21.501" transform="rotate(89.009 35.419 55.202)scale(-1 1)"/></g><g filter="url(#j)"><ellipse cx="14.592" cy="9.743" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(39.51 14.592 9.743)"/></g><g filter="url(#k)"><ellipse cx="61.728" cy="-5.321" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(37.892 61.728 -5.32)"/></g><g filter="url(#l)"><ellipse cx="55.618" cy="7.104" fill="#00c2ff" rx="5.971" ry="9.665" transform="rotate(37.892 55.618 7.104)"/></g><g filter="url(#m)"><ellipse cx="12.326" cy="39.103" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(37.892 12.326 39.103)"/></g><g filter="url(#n)"><ellipse cx="12.326" cy="39.103" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(37.892 12.326 39.103)"/></g><g filter="url(#o)"><ellipse cx="49.857" cy="30.678" fill="#8900ff" rx="4.407" ry="29.108" transform="rotate(37.892 49.857 30.678)"/></g><g filter="url(#p)"><ellipse cx="52.623" cy="33.171" fill="#00c2ff" rx="5.971" ry="15.297" transform="rotate(37.892 52.623 33.17)"/></g></g><path d="M6.919 0c-9.198 13.166-9.252 33.575 0 46.789h6.215c-9.25-13.214-9.196-33.623 0-46.789zm62.424 0h-6.215c9.198 13.166 9.252 33.575 0 46.789h6.215c9.25-13.214 9.196-33.623 0-46.789" class="parenthesis"/><defs><filter id="b" width="60.045" height="41.654" x="-5.564" y="16.92" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="7.659"/></filter><filter id="c" width="90.34" height="51.437" x="-40.407" y="-6.762" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="7.659"/></filter><filter id="d" width="79.355" height="29.4" x="-35.435" y="2.801" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="e" width="79.579" height="29.4" x="-30.84" y="20.8" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="f" width="79.579" height="29.4" x="-29.307" y="21.949" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="g" width="74.749" height="58.852" x="29.961" y="-17.13" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="7.659"/></filter><filter id="h" width="61.377" height="25.362" x="37.754" y="3.055" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="i" width="61.377" height="25.362" x="37.754" y="3.055" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="j" width="56.045" height="63.649" x="-13.43" y="-22.082" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="k" width="54.814" height="64.646" x="34.321" y="-37.644" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="l" width="33.541" height="35.313" x="38.847" y="-10.552" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="m" width="54.814" height="64.646" x="-15.081" y="6.78" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="n" width="54.814" height="64.646" x="-15.081" y="6.78" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="o" width="54.814" height="64.646" x="22.45" y="-1.645" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter><filter id="p" width="39.409" height="43.623" x="32.919" y="11.36" color-interpolation-filters="sRGB" filterUnits="userSpaceOnUse"><feFlood flood-opacity="0" result="BackgroundImageFix"/><feBlend in="SourceGraphic" in2="BackgroundImageFix" result="shape"/><feGaussianBlur result="effect1_foregroundBlur_2002_17286" stdDeviation="4.596"/></filter></defs></svg>
diff --git a/frontend/src/components/ui/LoadingScreen.tsx b/frontend/src/components/ui/LoadingScreen.tsx
index 86d574c10649e5e93d8f64315ba2447c81ecff6c..4b05c2199af422095acb999da9369a0ff6ee31d4 100644
--- a/frontend/src/components/ui/LoadingScreen.tsx
+++ b/frontend/src/components/ui/LoadingScreen.tsx
@@ -1,33 +1,33 @@
-import { Image } from "lucide-react";
-
-export default function LoadingScreen() {
-  return (
-    <div className="fixed inset-0 flex flex-col items-center justify-center bg-zinc-400 z-50">
-      <div className="relative flex flex-col items-center">
-        <div className="relative mb-8 animate-pulse">
-          <div className="text-white">
-            <Image size={110} strokeWidth={1.2} className="drop-shadow-sm" />
-          </div>
-          <div className="absolute -bottom-1 left-1/2 -translate-x-1/2 w-14 h-1.5 bg-yellow-400 rounded-full shadow-md" />
-        </div>
-
-        <div className="text-center">
-          <p className="text-white text-xl font-light tracking-widest uppercase opacity-90 animate-pulse">
-            Encontrar los mejores productos
-          </p>
-          <div className="mt-8 flex gap-2 justify-center">
-            <div className="w-2 h-2 bg-white rounded-full animate-bounce [animation-delay:-0.3s]" />
-            <div className="w-2 h-2 bg-white rounded-full animate-bounce [animation-delay:-0.15s]" />
-            <div className="w-2 h-2 bg-white rounded-full animate-bounce" />
-          </div>
-        </div>
-      </div>
-
-      <div className="absolute bottom-10 opacity-30">
-        <p className="text-white text-xs tracking-tighter uppercase font-bold">
-          Cargando Catálogo v2.0
-        </p>
-      </div>
-    </div>
-  );
-}
+import { Image } from "lucide-react";
+
+export default function LoadingScreen() {
+  return (
+    <div className="fixed inset-0 flex flex-col items-center justify-center bg-zinc-400 z-50">
+      <div className="relative flex flex-col items-center">
+        <div className="relative mb-8 animate-pulse">
+          <div className="text-white">
+            <Image size={110} strokeWidth={1.2} className="drop-shadow-sm" />
+          </div>
+          <div className="absolute -bottom-1 left-1/2 -translate-x-1/2 w-14 h-1.5 bg-yellow-400 rounded-full shadow-md" />
+        </div>
+
+        <div className="text-center">
+          <p className="text-white text-xl font-light tracking-widest uppercase opacity-90 animate-pulse">
+            Encontrar los mejores productos
+          </p>
+          <div className="mt-8 flex gap-2 justify-center">
+            <div className="w-2 h-2 bg-white rounded-full animate-bounce [animation-delay:-0.3s]" />
+            <div className="w-2 h-2 bg-white rounded-full animate-bounce [animation-delay:-0.15s]" />
+            <div className="w-2 h-2 bg-white rounded-full animate-bounce" />
+          </div>
+        </div>
+      </div>
+
+      <div className="absolute bottom-10 opacity-30">
+        <p className="text-white text-xs tracking-tighter uppercase font-bold">
+          Cargando Catálogo v2.0
+        </p>
+      </div>
+    </div>
+  );
+}
diff --git a/frontend/src/data/roomSetupData.ts b/frontend/src/data/roomSetupData.ts
index c37e9efb908d6411424c0698143dc6a1dc3cff99..b7e9d4da82a657cba86651ba9324df44c69e905d 100644
--- a/frontend/src/data/roomSetupData.ts
+++ b/frontend/src/data/roomSetupData.ts
@@ -1,329 +1,329 @@
-export type RoomCategory = {
-  id: string;
-  label: string;
-  count: number;
-};
-
-export type RoomItem = {
-  id: number;
-  title: string;
-  category: string;
-  img: string;
-};
-
-export const categorias: RoomCategory[] = [
-  { id: "todos", label: "Todos", count: 33 },
-  { id: "bano", label: "Baño", count: 10 },
-  { id: "cocina", label: "Cocina", count: 2 },
-  { id: "comedor", label: "Comedor", count: 3 },
-  { id: "dormitorio", label: "Dormitorio", count: 5 },
-  { id: "espacio_abierto", label: "Espacio abierto", count: 7 },
-  { id: "sala", label: "Sala de estar", count: 1 },
-  { id: "terraza", label: "Terraza", count: 5 },
-];
-
-export const habitaciones: RoomItem[] = [
-  {
-    id: 1,
-    title: "Refugio de Spa Contemporáneo",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom1.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 2,
-    title: "Oasis de Mármol Sereno",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom2.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 3,
-    title: "Baño Zen de Luz Natural",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom3.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 4,
-    title: "Retiro de Spa Blanco",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom4.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 5,
-    title: "Lavabo de Encanto Minimalista",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom5.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 6,
-    title: "Baño Escandinavo Refinado",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom6.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 7,
-    title: "Santuario de Mármol Pálido",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom7.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 8,
-    title: "Oasis Sereno de Blanco y Luz",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom8.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 9,
-    title: "Retiro de Mármol y Madera",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom9.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 10,
-    title: "Baño de Luz Cálida",
-    category: "bano",
-    img: new URL(
-      "../assets/imagens-default-room/bathroom/bathroom10.png",
-      import.meta.url,
-    ).href,
-  },
-
-  {
-    id: 11,
-    title: "Cocina Gourmet de Autor",
-    category: "cocina",
-    img: new URL(
-      "../assets/imagens-default-room/Kitchen/kitchen1.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 12,
-    title: "Cocina Contemporánea Urbana",
-    category: "cocina",
-    img: new URL(
-      "../assets/imagens-default-room/Kitchen/kitchen2.png",
-      import.meta.url,
-    ).href,
-  },
-
-  {
-    id: 13,
-    title: "Comedor de Gala Moderno",
-    category: "comedor",
-    img: new URL(
-      "../assets/imagens-default-room/dining room/diningroom1.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 14,
-    title: "Comedor Clásico de Lujo",
-    category: "comedor",
-    img: new URL(
-      "../assets/imagens-default-room/dining room/diningroom2.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 15,
-    title: "Sala de Banquetes Minimalista",
-    category: "comedor",
-    img: new URL(
-      "../assets/imagens-default-room/dining room/diningroom3.png",
-      import.meta.url,
-    ).href,
-  },
-
-  {
-    id: 16,
-    title: "Suite del Amanecer",
-    category: "dormitorio",
-    img: new URL(
-      "../assets/imagens-default-room/bedroom/bedroom1.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 17,
-    title: "Dormitorio de Seda",
-    category: "dormitorio",
-    img: new URL(
-      "../assets/imagens-default-room/bedroom/bedroom2.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 18,
-    title: "Alcoba Tranquila",
-    category: "dormitorio",
-    img: new URL(
-      "../assets/imagens-default-room/bedroom/bedroom3.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 19,
-    title: "Retiro de Noche Azul",
-    category: "dormitorio",
-    img: new URL(
-      "../assets/imagens-default-room/bedroom/bedroom4.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 20,
-    title: "Quinta Esencia del Descanso",
-    category: "dormitorio",
-    img: new URL(
-      "../assets/imagens-default-room/bedroom/bedroom5.png",
-      import.meta.url,
-    ).href,
-  },
-
-  {
-    id: 21,
-    title: "Salón Contemporáneo Sereno",
-    category: "sala",
-    img: new URL(
-      "../assets/imagens-default-room/living room/livingroom1.png",
-      import.meta.url,
-    ).href,
-  },
-
-  {
-    id: 22,
-    title: "Loft de Claridad",
-    category: "espacio_abierto",
-    img: new URL(
-      "../assets/imagens-default-room/open space/openspace1.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 23,
-    title: "Galería Abierta Suave",
-    category: "espacio_abierto",
-    img: new URL(
-      "../assets/imagens-default-room/open space/openspace2.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 24,
-    title: "Ático de Luz Serena",
-    category: "espacio_abierto",
-    img: new URL(
-      "../assets/imagens-default-room/open space/openspace3.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 25,
-    title: "Salón Multifuncional Luminoso",
-    category: "espacio_abierto",
-    img: new URL(
-      "../assets/imagens-default-room/open space/openspace4.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 26,
-    title: "Atrio de Cielo Blanco",
-    category: "espacio_abierto",
-    img: new URL(
-      "../assets/imagens-default-room/open space/openspace5.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 27,
-    title: "Estudio de Altura",
-    category: "espacio_abierto",
-    img: new URL(
-      "../assets/imagens-default-room/open space/openspace6.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 28,
-    title: "Retiro Etéreo",
-    category: "espacio_abierto",
-    img: new URL(
-      "../assets/imagens-default-room/open space/openspace7.png",
-      import.meta.url,
-    ).href,
-  },
-
-  {
-    id: 29,
-    title: "Terraza Nocturna de Ciudad",
-    category: "terraza",
-    img: new URL(
-      "../assets/imagens-default-room/terrace/terrace1.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 30,
-    title: "Terraza Contemporánea",
-    category: "terraza",
-    img: new URL(
-      "../assets/imagens-default-room/terrace/terrace2.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 31,
-    title: "Terraza de Rooftop Chic",
-    category: "terraza",
-    img: new URL(
-      "../assets/imagens-default-room/terrace/terrace3.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 32,
-    title: "Terraza de Diseño Iluminado",
-    category: "terraza",
-    img: new URL(
-      "../assets/imagens-default-room/terrace/terrace4.png",
-      import.meta.url,
-    ).href,
-  },
-  {
-    id: 33,
-    title: "Terraza de Encanto Nocturno",
-    category: "terraza",
-    img: new URL(
-      "../assets/imagens-default-room/terrace/terrace5.png",
-      import.meta.url,
-    ).href,
-  },
-];
+export type RoomCategory = {
+  id: string;
+  label: string;
+  count: number;
+};
+
+export type RoomItem = {
+  id: number;
+  title: string;
+  category: string;
+  img: string;
+};
+
+export const categorias: RoomCategory[] = [
+  { id: "todos", label: "Todos", count: 33 },
+  { id: "bano", label: "Baño", count: 10 },
+  { id: "cocina", label: "Cocina", count: 2 },
+  { id: "comedor", label: "Comedor", count: 3 },
+  { id: "dormitorio", label: "Dormitorio", count: 5 },
+  { id: "espacio_abierto", label: "Espacio abierto", count: 7 },
+  { id: "sala", label: "Sala de estar", count: 1 },
+  { id: "terraza", label: "Terraza", count: 5 },
+];
+
+export const habitaciones: RoomItem[] = [
+  {
+    id: 1,
+    title: "Refugio de Spa Contemporáneo",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom1.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 2,
+    title: "Oasis de Mármol Sereno",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom2.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 3,
+    title: "Baño Zen de Luz Natural",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom3.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 4,
+    title: "Retiro de Spa Blanco",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom4.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 5,
+    title: "Lavabo de Encanto Minimalista",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom5.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 6,
+    title: "Baño Escandinavo Refinado",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom6.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 7,
+    title: "Santuario de Mármol Pálido",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom7.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 8,
+    title: "Oasis Sereno de Blanco y Luz",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom8.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 9,
+    title: "Retiro de Mármol y Madera",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom9.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 10,
+    title: "Baño de Luz Cálida",
+    category: "bano",
+    img: new URL(
+      "../assets/imagens-default-room/bathroom/bathroom10.png",
+      import.meta.url,
+    ).href,
+  },
+
+  {
+    id: 11,
+    title: "Cocina Gourmet de Autor",
+    category: "cocina",
+    img: new URL(
+      "../assets/imagens-default-room/Kitchen/kitchen1.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 12,
+    title: "Cocina Contemporánea Urbana",
+    category: "cocina",
+    img: new URL(
+      "../assets/imagens-default-room/Kitchen/kitchen2.png",
+      import.meta.url,
+    ).href,
+  },
+
+  {
+    id: 13,
+    title: "Comedor de Gala Moderno",
+    category: "comedor",
+    img: new URL(
+      "../assets/imagens-default-room/dining room/diningroom1.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 14,
+    title: "Comedor Clásico de Lujo",
+    category: "comedor",
+    img: new URL(
+      "../assets/imagens-default-room/dining room/diningroom2.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 15,
+    title: "Sala de Banquetes Minimalista",
+    category: "comedor",
+    img: new URL(
+      "../assets/imagens-default-room/dining room/diningroom3.png",
+      import.meta.url,
+    ).href,
+  },
+
+  {
+    id: 16,
+    title: "Suite del Amanecer",
+    category: "dormitorio",
+    img: new URL(
+      "../assets/imagens-default-room/bedroom/bedroom1.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 17,
+    title: "Dormitorio de Seda",
+    category: "dormitorio",
+    img: new URL(
+      "../assets/imagens-default-room/bedroom/bedroom2.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 18,
+    title: "Alcoba Tranquila",
+    category: "dormitorio",
+    img: new URL(
+      "../assets/imagens-default-room/bedroom/bedroom3.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 19,
+    title: "Retiro de Noche Azul",
+    category: "dormitorio",
+    img: new URL(
+      "../assets/imagens-default-room/bedroom/bedroom4.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 20,
+    title: "Quinta Esencia del Descanso",
+    category: "dormitorio",
+    img: new URL(
+      "../assets/imagens-default-room/bedroom/bedroom5.png",
+      import.meta.url,
+    ).href,
+  },
+
+  {
+    id: 21,
+    title: "Salón Contemporáneo Sereno",
+    category: "sala",
+    img: new URL(
+      "../assets/imagens-default-room/living room/livingroom1.png",
+      import.meta.url,
+    ).href,
+  },
+
+  {
+    id: 22,
+    title: "Loft de Claridad",
+    category: "espacio_abierto",
+    img: new URL(
+      "../assets/imagens-default-room/open space/openspace1.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 23,
+    title: "Galería Abierta Suave",
+    category: "espacio_abierto",
+    img: new URL(
+      "../assets/imagens-default-room/open space/openspace2.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 24,
+    title: "Ático de Luz Serena",
+    category: "espacio_abierto",
+    img: new URL(
+      "../assets/imagens-default-room/open space/openspace3.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 25,
+    title: "Salón Multifuncional Luminoso",
+    category: "espacio_abierto",
+    img: new URL(
+      "../assets/imagens-default-room/open space/openspace4.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 26,
+    title: "Atrio de Cielo Blanco",
+    category: "espacio_abierto",
+    img: new URL(
+      "../assets/imagens-default-room/open space/openspace5.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 27,
+    title: "Estudio de Altura",
+    category: "espacio_abierto",
+    img: new URL(
+      "../assets/imagens-default-room/open space/openspace6.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 28,
+    title: "Retiro Etéreo",
+    category: "espacio_abierto",
+    img: new URL(
+      "../assets/imagens-default-room/open space/openspace7.png",
+      import.meta.url,
+    ).href,
+  },
+
+  {
+    id: 29,
+    title: "Terraza Nocturna de Ciudad",
+    category: "terraza",
+    img: new URL(
+      "../assets/imagens-default-room/terrace/terrace1.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 30,
+    title: "Terraza Contemporánea",
+    category: "terraza",
+    img: new URL(
+      "../assets/imagens-default-room/terrace/terrace2.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 31,
+    title: "Terraza de Rooftop Chic",
+    category: "terraza",
+    img: new URL(
+      "../assets/imagens-default-room/terrace/terrace3.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 32,
+    title: "Terraza de Diseño Iluminado",
+    category: "terraza",
+    img: new URL(
+      "../assets/imagens-default-room/terrace/terrace4.png",
+      import.meta.url,
+    ).href,
+  },
+  {
+    id: 33,
+    title: "Terraza de Encanto Nocturno",
+    category: "terraza",
+    img: new URL(
+      "../assets/imagens-default-room/terrace/terrace5.png",
+      import.meta.url,
+    ).href,
+  },
+];
diff --git a/frontend/src/features/roomSetup/RoomSetup.tsx b/frontend/src/features/roomSetup/RoomSetup.tsx
index 9344ce81d4b27d54658020adcf14ca179c6684f1..f637853360453d9cc2a700daf85a6bb0115e86d8 100644
--- a/frontend/src/features/roomSetup/RoomSetup.tsx
+++ b/frontend/src/features/roomSetup/RoomSetup.tsx
@@ -1,334 +1,318 @@
-import { useState } from "react";
-import {
-  X,
-  Camera,
-  Package,
-  Camera as CameraIcon,
-  UploadCloud,
-  Users,
-  ArrowRight,
-} from "lucide-react";
-import { useNavigate } from "react-router-dom";
-import { categorias, habitaciones } from "../../data/roomSetupData";
-import { FilterButton, RoomCard } from "./RoomSetupComponents";
-import { useRoomSetup } from "./roomSetupHooks";
-import useAppStore from "../../store/useAppStore";
-import { useHistoryStore, type HistoryItem } from "../../store/useAppStore";
-import { useActiveSessions } from "../../hooks/useActiveSessions";
-import { API_BASE } from "../../api/client";
-import {
-  useLoadSessionHistory,
-  deleteSessionFromBackend,
-} from "../../hooks/useSessionSync";
-import { useCallback } from "react";
-
-export default function RoomSetup() {
-  useLoadSessionHistory();
-  const [categoriaActiva, setCategoriaActiva] = useState("todos");
-  const navigate = useNavigate();
-  const segmentProgress = useAppStore((s) => s.segmentProgress);
-  const segmentFilename = useAppStore((s) => s.segmentFilename);
-  const storedPreviewImage = useAppStore((s) => s.previewImage);
-  const sessionHistory = useHistoryStore((s) => s.sessionHistory);
-  const removeFromHistory = useHistoryStore((s) => s.removeFromHistory);
-  const userId = useHistoryStore((s) => s.userId);
-
-  const handleDeleteSession = useCallback(
-    (e: React.MouseEvent, filename: string) => {
-      e.stopPropagation();
-      removeFromHistory(filename);
-      deleteSessionFromBackend(userId, filename);
-    },
-    [removeFromHistory, userId],
-  );
-  const { count: activeSessions } = useActiveSessions();
-  const {
-    isDragging,
-    previewImage,
-    uploadMessage,
-    isUploading,
-    fileInputRef,
-    handleDragOver,
-    handleDragLeave,
-    handleDrop,
-    handleFileChange,
-    handleDemoRoomSelect,
-    triggerFileInput,
-    clearPreviewImage,
-  } = useRoomSetup();
-
-  const habitacionesFiltradas =
-    categoriaActiva === "todos"
-      ? habitaciones
-      : habitaciones.filter((h) => h.category === categoriaActiva);
-
-  return (
-    <div className="min-h-screen bg-[#f4f8ff] font-sans text-[#333333]">
-      <main className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-4 sm:py-8 relative">
-        {isUploading && (
-          <div className="fixed inset-0 bg-white/80 backdrop-blur-sm z-50 flex flex-col items-center justify-center gap-4 px-4">
-            <p className="text-[#0047AB] font-semibold text-lg text-center">
-              Analizando imagen con IA...
-            </p>
-            <div className="w-full max-w-xs sm:w-72 bg-gray-200 rounded-full h-3 overflow-hidden">
-              <div
-                className="bg-[#0047AB] h-3 rounded-full transition-all duration-500"
-                style={{ width: `${segmentProgress}%` }}
-              />
-            </div>
-            <p className="text-sm text-gray-500">{uploadMessage}</p>
-          </div>
-        )}
-
-        {/* Badge de sesiones activas */}
-        {activeSessions > 0 && (
-          <div className="mb-4 flex justify-end">
-            <div className="flex items-center gap-2 bg-white border border-[#dbe7ff] rounded-full px-4 py-1.5 shadow-sm">
-              <span className="w-2 h-2 rounded-full bg-green-500 animate-pulse" />
-              <Users className="w-4 h-4 text-[#0047AB]" />
-              <span className="text-sm font-medium text-[#0047AB]">
-                {activeSessions} usuario{activeSessions !== 1 ? "s" : ""} activo
-                {activeSessions !== 1 ? "s" : ""}
-              </span>
-            </div>
-          </div>
-        )}
-
-        {/* SECCIÓN SUPERIOR: Sube tu foto */}
-        <section className="grid grid-cols-1 lg:grid-cols-2 gap-6 lg:gap-12 mb-10 sm:mb-16 lg:mb-20">
-          {/* Columna Izquierda: Textos y Botones */}
-          <div className="flex flex-col justify-center">
-            <h1 className="text-2xl sm:text-3xl lg:text-4xl font-bold text-[#333333] mb-4 sm:mb-6 lg:mb-8">
-              Ver los productos en su cuarto
-            </h1>
-
-            <ul className="space-y-4 sm:space-y-6 mb-6 sm:mb-8 lg:mb-10">
-              <li className="flex items-center gap-3 text-base sm:text-lg font-medium text-[#333333]">
-                <Camera className="w-5 h-5 sm:w-6 sm:h-6 text-[#0047AB] shrink-0" />
-                Sube una foto de tu habitación
-              </li>
-              <li className="flex items-center gap-3 text-base sm:text-lg font-medium text-[#333333]">
-                <Package className="w-5 h-5 sm:w-6 sm:h-6 text-[#0047AB] shrink-0" />
-                Prueba nuestros productos
-              </li>
-            </ul>
-
-            <div className="w-full flex flex-col gap-3">
-              <button
-                onClick={triggerFileInput}
-                className="w-full bg-[#333333] hover:bg-black text-white font-bold text-base sm:text-lg py-3 sm:py-4 px-6 rounded-xl flex items-center justify-center gap-3 transition-colors shadow-sm"
-              >
-                <CameraIcon
-                  className="w-5 h-5 sm:w-6 sm:h-6"
-                  strokeWidth={2.5}
-                />
-                Sube tu foto
-              </button>
-
-              {segmentFilename && !isUploading && (
-                <button
-                  onClick={() =>
-                    navigate("/visualizer", {
-                      state: {
-                        previewImage:
-                          storedPreviewImage ??
-                          `${API_BASE}/seg/image/${segmentFilename}`,
-                      },
-                    })
-                  }
-                  className="w-full bg-[#0047AB] hover:bg-[#003a94] text-white font-bold text-base sm:text-lg py-3 sm:py-4 px-6 rounded-xl flex items-center justify-center gap-3 transition-colors shadow-sm"
-                >
-                  Continuar al visualizador
-                  <ArrowRight
-                    className="w-5 h-5 sm:w-6 sm:h-6"
-                    strokeWidth={2.5}
-                  />
-                </button>
-              )}
-            </div>
-            {uploadMessage && (
-              <p className="text-sm text-[#707070] mt-3">{uploadMessage}</p>
-            )}
-          </div>
-
-          {/* Columna Derecha: Dropzone de Imagen */}
-          <div
-            className={`relative rounded-2xl overflow-hidden min-h-[220px] sm:aspect-[4/3] sm:min-h-0 flex flex-col items-center justify-center border-2 border-dashed transition-all duration-200 ${
-              isDragging
-                ? "border-[#0047AB] bg-[#eaf1ff]"
-                : "border-[#dbe7ff] bg-[#f4f8ff] hover:bg-[#eef4ff]"
-            }`}
-            onDragOver={handleDragOver}
-            onDragLeave={handleDragLeave}
-            onDrop={handleDrop}
-          >
-            {previewImage ? (
-              <div className="relative w-full h-full group">
-                <img
-                  src={previewImage}
-                  alt="Vista previa"
-                  className="w-full h-full object-cover"
-                />
-                <div className="absolute inset-0 bg-black/40 opacity-0 group-hover:opacity-100 transition-opacity flex items-center justify-center backdrop-blur-sm">
-                  <button
-                    onClick={clearPreviewImage}
-                    className="bg-white text-[#0047AB] font-medium py-2 px-4 rounded-lg flex items-center gap-2 hover:bg-[#eef4ff] transition-colors shadow-lg"
-                  >
-                    <X className="w-4 h-4" /> Eliminar foto
-                  </button>
-                </div>
-              </div>
-            ) : (
-              <>
-                <input
-                  type="file"
-                  accept="image/*"
-                  onChange={handleFileChange}
-                  ref={fileInputRef}
-                  className="absolute inset-0 w-full h-full opacity-0 cursor-pointer"
-                />
-                <div className="flex flex-col items-center pointer-events-none text-center p-6">
-                  <div
-                    className={`w-14 h-14 sm:w-16 sm:h-16 rounded-full flex items-center justify-center mb-3 sm:mb-4 transition-colors ${
-                      isDragging
-                        ? "bg-[#0047AB]/20 text-[#0047AB]"
-                        : "bg-[#eaf1ff] text-[#0047AB]"
-                    }`}
-                  >
-                    <UploadCloud className="w-7 h-7 sm:w-8 sm:h-8" />
-                  </div>
-                  <h3 className="text-lg sm:text-xl font-bold text-[#333333] mb-2">
-                    {isDragging
-                      ? "Suelta la imagen aquí"
-                      : "Arrastra tu foto aquí"}
-                  </h3>
-                  <p className="text-[#707070] text-sm sm:text-base">
-                    o haz clic para explorar en tu dispositivo
-                  </p>
-                  <p className="text-[#707070] text-xs mt-3 sm:mt-4">
-                    Formatos soportados: JPG, PNG
-                  </p>
-                </div>
-              </>
-            )}
-          </div>
-        </section>
-
-        {/* SECCIÓN HISTORIAL DE SESIÓN */}
-        {sessionHistory.length > 0 && (
-          <section className="mb-10 sm:mb-14">
-            <h2 className="text-xl sm:text-2xl font-bold text-[#333333] mb-4 sm:mb-6">
-              Tus espacios recientes
-            </h2>
-            <div
-              className="flex gap-4 overflow-x-auto pb-2"
-              style={{ scrollbarWidth: "thin" }}
-            >
-              {sessionHistory.map((item: HistoryItem) => (
-                <div
-                  key={item.filename}
-                  role="button"
-                  tabIndex={0}
-                  onClick={() =>
-                    navigate("/visualizer", {
-                      state: {
-                        previewImage: item.previewUrl,
-                        filename: item.filename,
-                        maskCount: item.maskCount,
-                      },
-                    })
-                  }
-                  onKeyDown={(e) => {
-                    if (e.key === "Enter" || e.key === " ") {
-                      navigate("/visualizer", {
-                        state: {
-                          previewImage: item.previewUrl,
-                          filename: item.filename,
-                          maskCount: item.maskCount,
-                        },
-                      });
-                    }
-                  }}
-                  className={`flex-shrink-0 group relative rounded-2xl overflow-hidden border-2 transition-all duration-200 ${
-                    segmentFilename === item.filename
-                      ? "border-[#0047AB] shadow-lg shadow-[#0047AB]/20"
-                      : "border-[#dbe7ff] hover:border-[#0047AB]"
-                  }`}
-                  style={{ width: 160, height: 120 }}
-                >
-                  <img
-                    src={item.previewUrl}
-                    alt="Habitación previa"
-                    className="w-full h-full object-cover"
-                  />
-                  {/* Overlay con hora */}
-                  <div className="absolute inset-0 bg-gradient-to-t from-black/60 via-transparent to-transparent flex flex-col justify-end p-2">
-                    <p className="text-white/80 text-[10px]">
-                      {new Date(item.uploadedAt).toLocaleDateString([], {
-                        day: "2-digit",
-                        month: "short",
-                      })}{" "}
-                      {new Date(item.uploadedAt).toLocaleTimeString([], {
-                        hour: "2-digit",
-                        minute: "2-digit",
-                      })}
-                    </p>
-                  </div>
-                  {/* Badge "activa" o botón eliminar */}
-                  {segmentFilename === item.filename ? (
-                    <div className="absolute top-2 right-2 bg-[#0047AB] text-white text-[9px] font-bold px-1.5 py-0.5 rounded-full">
-                      Activa
-                    </div>
-                  ) : (
-                    <button
-                      onClick={(e) => handleDeleteSession(e, item.filename)}
-                      className="absolute top-2 right-2 w-5 h-5 rounded-full bg-black/50 text-white flex items-center justify-center opacity-0 group-hover:opacity-100 transition-opacity hover:bg-red-500"
-                    >
-                      <X className="w-3 h-3" />
-                    </button>
-                  )}
-                  {/* Hover: continuar */}
-                  <div className="absolute inset-0 bg-[#0047AB]/80 opacity-0 group-hover:opacity-100 transition-opacity flex items-center justify-center">
-                    <span className="text-white text-xs font-bold flex items-center gap-1">
-                      Continuar <ArrowRight className="w-3.5 h-3.5" />
-                    </span>
-                  </div>
-                </div>
-              ))}
-            </div>
-          </section>
-        )}
-
-        {/* SECCIÓN INFERIOR: Habitaciones de demostración */}
-        <section>
-          <h2 className="text-xl sm:text-2xl font-bold text-[#0047AB] mb-4 sm:mb-6">
-            ¿No tienes una foto? Prueba nuestras habitaciones de demostración
-          </h2>
-
-          {/* Filtros */}
-          <div className="flex flex-wrap gap-2 mb-6 sm:mb-8">
-            {categorias.map((cat) => (
-              <FilterButton
-                key={cat.id}
-                category={cat}
-                active={categoriaActiva === cat.id}
-                onSelect={setCategoriaActiva}
-              />
-            ))}
-          </div>
-
-          {/* Cuadrícula de Imágenes */}
-          <div className="grid grid-cols-1 sm:grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-4 sm:gap-6">
-            {habitacionesFiltradas.map((hab) => (
-              <RoomCard
-                key={hab.id}
-                room={hab}
-                onSelect={handleDemoRoomSelect}
-              />
-            ))}
-          </div>
-        </section>
-      </main>
-    </div>
-  );
-}
+import { useState } from "react";
+import {
+  X,
+  Camera,
+  Package,
+  Camera as CameraIcon,
+  UploadCloud,
+  Users,
+  ArrowRight,
+} from "lucide-react";
+import { useNavigate } from "react-router-dom";
+import { categorias, habitaciones } from "../../data/roomSetupData";
+import { FilterButton, RoomCard } from "./RoomSetupComponents";
+import { useRoomSetup } from "./roomSetupHooks";
+import useAppStore from "../../store/useAppStore";
+import { useHistoryStore, type HistoryItem } from "../../store/useAppStore";
+import { useActiveSessions } from "../../hooks/useActiveSessions";
+import { API_BASE } from "../../api/client";
+import { useLoadSessionHistory, deleteSessionFromBackend } from "../../hooks/useSessionSync";
+import { useCallback } from "react";
+
+export default function RoomSetup() {
+  useLoadSessionHistory();
+  const [categoriaActiva, setCategoriaActiva] = useState("todos");
+  const navigate = useNavigate();
+  const segmentProgress = useAppStore((s) => s.segmentProgress);
+  const segmentFilename = useAppStore((s) => s.segmentFilename);
+  const storedPreviewImage = useAppStore((s) => s.previewImage);
+  const sessionHistory = useHistoryStore((s) => s.sessionHistory);
+  const removeFromHistory = useHistoryStore((s) => s.removeFromHistory);
+  const userId = useHistoryStore((s) => s.userId);
+
+  const handleDeleteSession = useCallback(
+    (e: React.MouseEvent, filename: string) => {
+      e.stopPropagation();
+      removeFromHistory(filename);
+      deleteSessionFromBackend(userId, filename);
+    },
+    [removeFromHistory, userId],
+  );
+  const { count: activeSessions } = useActiveSessions();
+  const {
+    isDragging,
+    previewImage,
+    uploadMessage,
+    isUploading,
+    fileInputRef,
+    handleDragOver,
+    handleDragLeave,
+    handleDrop,
+    handleFileChange,
+    handleDemoRoomSelect,
+    triggerFileInput,
+    clearPreviewImage,
+  } = useRoomSetup();
+
+  const habitacionesFiltradas =
+    categoriaActiva === "todos"
+      ? habitaciones
+      : habitaciones.filter((h) => h.category === categoriaActiva);
+
+  return (
+    <div className="min-h-screen bg-[#f4f8ff] font-sans text-[#333333]">
+      <main className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-4 sm:py-8 relative">
+        {isUploading && (
+          <div className="fixed inset-0 bg-white/80 backdrop-blur-sm z-50 flex flex-col items-center justify-center gap-4 px-4">
+            <p className="text-[#0047AB] font-semibold text-lg text-center">
+              Analizando imagen con IA...
+            </p>
+            <div className="w-full max-w-xs sm:w-72 bg-gray-200 rounded-full h-3 overflow-hidden">
+              <div
+                className="bg-[#0047AB] h-3 rounded-full transition-all duration-500"
+                style={{ width: `${segmentProgress}%` }}
+              />
+            </div>
+            <p className="text-sm text-gray-500">{uploadMessage}</p>
+          </div>
+        )}
+
+        {/* Badge de sesiones activas */}
+        {activeSessions > 0 && (
+          <div className="mb-4 flex justify-end">
+            <div className="flex items-center gap-2 bg-white border border-[#dbe7ff] rounded-full px-4 py-1.5 shadow-sm">
+              <span className="w-2 h-2 rounded-full bg-green-500 animate-pulse" />
+              <Users className="w-4 h-4 text-[#0047AB]" />
+              <span className="text-sm font-medium text-[#0047AB]">
+                {activeSessions} usuario{activeSessions !== 1 ? "s" : ""} activo
+                {activeSessions !== 1 ? "s" : ""}
+              </span>
+            </div>
+          </div>
+        )}
+
+        {/* SECCIÓN SUPERIOR: Sube tu foto */}
+        <section className="grid grid-cols-1 lg:grid-cols-2 gap-6 lg:gap-12 mb-10 sm:mb-16 lg:mb-20">
+          {/* Columna Izquierda: Textos y Botones */}
+          <div className="flex flex-col justify-center">
+            <h1 className="text-2xl sm:text-3xl lg:text-4xl font-bold text-[#333333] mb-4 sm:mb-6 lg:mb-8">
+              Ver los productos en su cuarto
+            </h1>
+
+            <ul className="space-y-4 sm:space-y-6 mb-6 sm:mb-8 lg:mb-10">
+              <li className="flex items-center gap-3 text-base sm:text-lg font-medium text-[#333333]">
+                <Camera className="w-5 h-5 sm:w-6 sm:h-6 text-[#0047AB] shrink-0" />
+                Sube una foto de tu habitación
+              </li>
+              <li className="flex items-center gap-3 text-base sm:text-lg font-medium text-[#333333]">
+                <Package className="w-5 h-5 sm:w-6 sm:h-6 text-[#0047AB] shrink-0" />
+                Prueba nuestros productos
+              </li>
+            </ul>
+
+            <div className="w-full flex flex-col gap-3">
+              <button
+                onClick={triggerFileInput}
+                className="w-full bg-[#333333] hover:bg-black text-white font-bold text-base sm:text-lg py-3 sm:py-4 px-6 rounded-xl flex items-center justify-center gap-3 transition-colors shadow-sm"
+              >
+                <CameraIcon
+                  className="w-5 h-5 sm:w-6 sm:h-6"
+                  strokeWidth={2.5}
+                />
+                Sube tu foto
+              </button>
+
+              {segmentFilename && !isUploading && (
+                <button
+                  onClick={() =>
+                    navigate("/visualizer", {
+                      state: {
+                        previewImage:
+                          storedPreviewImage ??
+                          `${API_BASE}/seg/image/${segmentFilename}`,
+                      },
+                    })
+                  }
+                  className="w-full bg-[#0047AB] hover:bg-[#003a94] text-white font-bold text-base sm:text-lg py-3 sm:py-4 px-6 rounded-xl flex items-center justify-center gap-3 transition-colors shadow-sm"
+                >
+                  Continuar al visualizador
+                  <ArrowRight
+                    className="w-5 h-5 sm:w-6 sm:h-6"
+                    strokeWidth={2.5}
+                  />
+                </button>
+              )}
+            </div>
+            {uploadMessage && (
+              <p className="text-sm text-[#707070] mt-3">{uploadMessage}</p>
+            )}
+          </div>
+
+          {/* Columna Derecha: Dropzone de Imagen */}
+          <div
+            className={`relative rounded-2xl overflow-hidden min-h-[220px] sm:aspect-[4/3] sm:min-h-0 flex flex-col items-center justify-center border-2 border-dashed transition-all duration-200 ${
+              isDragging
+                ? "border-[#0047AB] bg-[#eaf1ff]"
+                : "border-[#dbe7ff] bg-[#f4f8ff] hover:bg-[#eef4ff]"
+            }`}
+            onDragOver={handleDragOver}
+            onDragLeave={handleDragLeave}
+            onDrop={handleDrop}
+          >
+            {previewImage ? (
+              <div className="relative w-full h-full group">
+                <img
+                  src={previewImage}
+                  alt="Vista previa"
+                  className="w-full h-full object-cover"
+                />
+                <div className="absolute inset-0 bg-black/40 opacity-0 group-hover:opacity-100 transition-opacity flex items-center justify-center backdrop-blur-sm">
+                  <button
+                    onClick={clearPreviewImage}
+                    className="bg-white text-[#0047AB] font-medium py-2 px-4 rounded-lg flex items-center gap-2 hover:bg-[#eef4ff] transition-colors shadow-lg"
+                  >
+                    <X className="w-4 h-4" /> Eliminar foto
+                  </button>
+                </div>
+              </div>
+            ) : (
+              <>
+                <input
+                  type="file"
+                  accept="image/*"
+                  onChange={handleFileChange}
+                  ref={fileInputRef}
+                  className="absolute inset-0 w-full h-full opacity-0 cursor-pointer"
+                />
+                <div className="flex flex-col items-center pointer-events-none text-center p-6">
+                  <div
+                    className={`w-14 h-14 sm:w-16 sm:h-16 rounded-full flex items-center justify-center mb-3 sm:mb-4 transition-colors ${
+                      isDragging
+                        ? "bg-[#0047AB]/20 text-[#0047AB]"
+                        : "bg-[#eaf1ff] text-[#0047AB]"
+                    }`}
+                  >
+                    <UploadCloud className="w-7 h-7 sm:w-8 sm:h-8" />
+                  </div>
+                  <h3 className="text-lg sm:text-xl font-bold text-[#333333] mb-2">
+                    {isDragging
+                      ? "Suelta la imagen aquí"
+                      : "Arrastra tu foto aquí"}
+                  </h3>
+                  <p className="text-[#707070] text-sm sm:text-base">
+                    o haz clic para explorar en tu dispositivo
+                  </p>
+                  <p className="text-[#707070] text-xs mt-3 sm:mt-4">
+                    Formatos soportados: JPG, PNG
+                  </p>
+                </div>
+              </>
+            )}
+          </div>
+        </section>
+
+        {/* SECCIÓN HISTORIAL DE SESIÓN */}
+        {sessionHistory.length > 0 && (
+          <section className="mb-10 sm:mb-14">
+            <h2 className="text-xl sm:text-2xl font-bold text-[#333333] mb-4 sm:mb-6">
+              Tus espacios recientes
+            </h2>
+            <div
+              className="flex gap-4 overflow-x-auto pb-2"
+              style={{ scrollbarWidth: "thin" }}
+            >
+              {sessionHistory.map((item: HistoryItem) => (
+                <button
+                  key={item.filename}
+                  onClick={() =>
+                    navigate("/visualizer", {
+                      state: {
+                        previewImage: item.previewUrl,
+                        filename: item.filename,
+                        maskCount: item.maskCount,
+                      },
+                    })
+                  }
+                  className={`flex-shrink-0 group relative rounded-2xl overflow-hidden border-2 transition-all duration-200 ${
+                    segmentFilename === item.filename
+                      ? "border-[#0047AB] shadow-lg shadow-[#0047AB]/20"
+                      : "border-[#dbe7ff] hover:border-[#0047AB]"
+                  }`}
+                  style={{ width: 160, height: 120 }}
+                >
+                  <img
+                    src={item.previewUrl}
+                    alt="Habitación previa"
+                    className="w-full h-full object-cover"
+                  />
+                  {/* Overlay con hora */}
+                  <div className="absolute inset-0 bg-gradient-to-t from-black/60 via-transparent to-transparent flex flex-col justify-end p-2">
+                    <p className="text-white/80 text-[10px]">
+                      {new Date(item.uploadedAt).toLocaleDateString([], {
+                        day: "2-digit",
+                        month: "short",
+                      })}{" "}
+                      {new Date(item.uploadedAt).toLocaleTimeString([], {
+                        hour: "2-digit",
+                        minute: "2-digit",
+                      })}
+                    </p>
+                  </div>
+                  {/* Badge "activa" o botón eliminar */}
+                  {segmentFilename === item.filename ? (
+                    <div className="absolute top-2 right-2 bg-[#0047AB] text-white text-[9px] font-bold px-1.5 py-0.5 rounded-full">
+                      Activa
+                    </div>
+                  ) : (
+                    <button
+                      onClick={(e) => handleDeleteSession(e, item.filename)}
+                      className="absolute top-2 right-2 w-5 h-5 rounded-full bg-black/50 text-white flex items-center justify-center opacity-0 group-hover:opacity-100 transition-opacity hover:bg-red-500"
+                    >
+                      <X className="w-3 h-3" />
+                    </button>
+                  )}
+                  {/* Hover: continuar */}
+                  <div className="absolute inset-0 bg-[#0047AB]/80 opacity-0 group-hover:opacity-100 transition-opacity flex items-center justify-center">
+                    <span className="text-white text-xs font-bold flex items-center gap-1">
+                      Continuar <ArrowRight className="w-3.5 h-3.5" />
+                    </span>
+                  </div>
+                </button>
+              ))}
+            </div>
+          </section>
+        )}
+
+        {/* SECCIÓN INFERIOR: Habitaciones de demostración */}
+        <section>
+          <h2 className="text-xl sm:text-2xl font-bold text-[#0047AB] mb-4 sm:mb-6">
+            ¿No tienes una foto? Prueba nuestras habitaciones de demostración
+          </h2>
+
+          {/* Filtros */}
+          <div className="flex flex-wrap gap-2 mb-6 sm:mb-8">
+            {categorias.map((cat) => (
+              <FilterButton
+                key={cat.id}
+                category={cat}
+                active={categoriaActiva === cat.id}
+                onSelect={setCategoriaActiva}
+              />
+            ))}
+          </div>
+
+          {/* Cuadrícula de Imágenes */}
+          <div className="grid grid-cols-1 sm:grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-4 sm:gap-6">
+            {habitacionesFiltradas.map((hab) => (
+              <RoomCard
+                key={hab.id}
+                room={hab}
+                onSelect={handleDemoRoomSelect}
+              />
+            ))}
+          </div>
+        </section>
+      </main>
+    </div>
+  );
+}
diff --git a/frontend/src/features/roomSetup/RoomSetupComponents.tsx b/frontend/src/features/roomSetup/RoomSetupComponents.tsx
index 1f7f0feb0c6da121acbcae1cec120e7f53a1e5bd..90a6e81d69a8ca1895689ebc1c32538920d5bea0 100644
--- a/frontend/src/features/roomSetup/RoomSetupComponents.tsx
+++ b/frontend/src/features/roomSetup/RoomSetupComponents.tsx
@@ -1,62 +1,62 @@
-import {
-  type RoomCategory,
-  type RoomItem,
-  categorias,
-} from "../../data/roomSetupData";
-
-type FilterButtonProps = {
-  category: RoomCategory;
-  active: boolean;
-  onSelect: (id: string) => void;
-};
-
-export function FilterButton({
-  category,
-  active,
-  onSelect,
-}: FilterButtonProps) {
-  return (
-    <button
-      type="button"
-      onClick={() => onSelect(category.id)}
-      className={`px-4 py-2 rounded-lg text-sm font-medium transition-all duration-200 border ${
-        active
-          ? "bg-[#0047AB] border-[#0047AB] text-white shadow-sm"
-          : "bg-white border-[#0047AB] text-[#0047AB] hover:bg-[#eaf1ff]"
-      }`}
-    >
-      {category.label} ({category.count})
-    </button>
-  );
-}
-
-type RoomCardProps = {
-  room: RoomItem;
-  onSelect: (url: string) => void;
-};
-
-export function RoomCard({ room, onSelect }: RoomCardProps) {
-  const categoryLabel =
-    categorias.find((cat) => cat.id === room.category)?.label ?? room.category;
-
-  return (
-    <button
-      type="button"
-      onClick={() => onSelect(room.img)}
-      className="group cursor-pointer text-left"
-    >
-      <div className="relative aspect-[4/3] rounded-2xl overflow-hidden mb-3 bg-[#edf4ff]">
-        <img
-          src={room.img}
-          alt={room.title}
-          className="w-full h-full object-cover transition-transform duration-500 group-hover:scale-105"
-        />
-        <div className="absolute inset-0 bg-black/0 group-hover:bg-black/10 transition-colors duration-300" />
-      </div>
-      <div className="px-1">
-        <h3 className="text-[#333333] font-medium text-sm">{room.title}</h3>
-        <p className="text-[#707070] text-xs mt-1">{categoryLabel}</p>
-      </div>
-    </button>
-  );
-}
+import {
+  type RoomCategory,
+  type RoomItem,
+  categorias,
+} from "../../data/roomSetupData";
+
+type FilterButtonProps = {
+  category: RoomCategory;
+  active: boolean;
+  onSelect: (id: string) => void;
+};
+
+export function FilterButton({
+  category,
+  active,
+  onSelect,
+}: FilterButtonProps) {
+  return (
+    <button
+      type="button"
+      onClick={() => onSelect(category.id)}
+      className={`px-4 py-2 rounded-lg text-sm font-medium transition-all duration-200 border ${
+        active
+          ? "bg-[#0047AB] border-[#0047AB] text-white shadow-sm"
+          : "bg-white border-[#0047AB] text-[#0047AB] hover:bg-[#eaf1ff]"
+      }`}
+    >
+      {category.label} ({category.count})
+    </button>
+  );
+}
+
+type RoomCardProps = {
+  room: RoomItem;
+  onSelect: (url: string) => void;
+};
+
+export function RoomCard({ room, onSelect }: RoomCardProps) {
+  const categoryLabel =
+    categorias.find((cat) => cat.id === room.category)?.label ?? room.category;
+
+  return (
+    <button
+      type="button"
+      onClick={() => onSelect(room.img)}
+      className="group cursor-pointer text-left"
+    >
+      <div className="relative aspect-[4/3] rounded-2xl overflow-hidden mb-3 bg-[#edf4ff]">
+        <img
+          src={room.img}
+          alt={room.title}
+          className="w-full h-full object-cover transition-transform duration-500 group-hover:scale-105"
+        />
+        <div className="absolute inset-0 bg-black/0 group-hover:bg-black/10 transition-colors duration-300" />
+      </div>
+      <div className="px-1">
+        <h3 className="text-[#333333] font-medium text-sm">{room.title}</h3>
+        <p className="text-[#707070] text-xs mt-1">{categoryLabel}</p>
+      </div>
+    </button>
+  );
+}
diff --git a/frontend/src/features/roomSetup/roomSetup.types.ts b/frontend/src/features/roomSetup/roomSetup.types.ts
index e8263125b3cecd0abbaa50e9f5138840a0f9db57..7a5b12df707d822799851e192ee6cbec02f71b3e 100644
--- a/frontend/src/features/roomSetup/roomSetup.types.ts
+++ b/frontend/src/features/roomSetup/roomSetup.types.ts
@@ -1,6 +1,6 @@
-// Tipos específicos de la feature roomSetup.
-
-export type RoomSetupState = {
-  previewImage: string | null;
-  uploadMessage: string | null;
-};
+// Tipos específicos de la feature roomSetup.
+
+export type RoomSetupState = {
+  previewImage: string | null;
+  uploadMessage: string | null;
+};
diff --git a/frontend/src/features/roomSetup/roomSetupHooks.ts b/frontend/src/features/roomSetup/roomSetupHooks.ts
index f1a6bcea1f405d751cd2df07017b9489a614c549..a851d363d2997200b20da243b685025eb0cd69fb 100644
--- a/frontend/src/features/roomSetup/roomSetupHooks.ts
+++ b/frontend/src/features/roomSetup/roomSetupHooks.ts
@@ -7,8 +7,11 @@ import {
   type RefObject,
 } from "react";
 import { useNavigate } from "react-router-dom";
-import useAppStore, { useHistoryStore } from "../../store/useAppStore";
-import { uploadRoomImage, buildApiUrl } from "../../api/client";
+import useAppStore from "../../store/useAppStore";
+import { useHistoryStore } from "../../store/useAppStore";
+import { useSegmentUpload } from "../../hooks/useSegmentUpload";
+import { API_BASE } from "../../api/client";
+import { saveSessionToBackend } from "../../hooks/useSessionSync";
 
 export function useRoomSetup(): {
   isDragging: boolean;
@@ -37,9 +40,7 @@ export function useRoomSetup(): {
   const addToHistory = useHistoryStore((state) => state.addToHistory);
   const userId = useHistoryStore((state) => state.userId);
 
-  const setUploadedFile = useAppStore((s) => s.setUploadedFile);
-  // applyTextureOpenAI is unused in this hook; call it from the visualizer where needed
-  const isUploading = false;
+  const { uploadAndSegment, isUploading } = useSegmentUpload();
 
   const clearPreviewImage = useCallback(() => {
     setPreviewImage(null);
@@ -52,30 +53,35 @@ export function useRoomSetup(): {
       // Blob URL used only for local preview while uploading; replaced with server URL after
       const objectUrl = URL.createObjectURL(file);
       setPreviewImage(objectUrl);
-      setUploadMessage("Imagen lista — selecciona un producto para aplicar");
-      setUploadedFile(file);
-
-      // Start uploading in background so backend has a stable URL for processing.
-      (async () => {
-        try {
-          const res = await uploadRoomImage(file);
-          if (res?.url) {
-            const serverUrl = buildApiUrl(res.url as string);
-            setPreviewImage(serverUrl);
-            setUploadMessage("Imagen subida al servidor");
-          }
-        } catch (err) {
-          const msg =
-            err instanceof Error ? err.message : "Error al subir la imagen";
-          setUploadMessage(msg);
-        }
-      })();
+      setUploadMessage("Iniciando segmentación...");
 
       try {
-        // Ahora el flujo es: usuario sube imagen → selecciona producto → backend /api/generate-image
-        // Navegamos al visualizador con la preview local y el usuario selecciona producto allí.
+        const { filename, maskCount } = await uploadAndSegment(
+          file,
+          (progress, message) => {
+            setSegmentProgress(progress);
+            setUploadMessage(message);
+          },
+        );
+
+        setSegmentResult(filename, maskCount);
+        setUploadMessage(`Segmentación completa — ${maskCount} zonas detectadas`);
+
+        // Server URL persists across page refreshes; blob URL does not
+        const serverImageUrl = `${API_BASE}/seg/image/${filename}`;
+        setPreviewImage(serverImageUrl);
+
+        const historyItem = {
+          filename,
+          previewUrl: serverImageUrl,
+          maskCount,
+          uploadedAt: Date.now(),
+        };
+        addToHistory(historyItem);
+        saveSessionToBackend(userId, historyItem);
+
         navigate("/visualizer", {
-          state: { previewImage: objectUrl },
+          state: { previewImage: serverImageUrl },
         });
       } catch (err) {
         const message =
@@ -89,6 +95,7 @@ export function useRoomSetup(): {
       setUploadMessage,
       setSegmentResult,
       setSegmentProgress,
+      uploadAndSegment,
       addToHistory,
       userId,
     ],
diff --git a/frontend/src/features/roomVisualizer/MaskLayer.tsx b/frontend/src/features/roomVisualizer/MaskLayer.tsx
index 8e39e8ab8a3f61be4a2e2d75e5ed9e76b9240dbb..6027adf3d876c3bdf2a4391b196429e90634dfb7 100644
--- a/frontend/src/features/roomVisualizer/MaskLayer.tsx
+++ b/frontend/src/features/roomVisualizer/MaskLayer.tsx
@@ -1,45 +1,45 @@
-import React from "react";
-
-interface MaskLayerProps {
-  maskUrl: string;
-  color: string;
-  onMouseEnter: (maskUrl: string) => void;
-  onClick: (maskUrl: string) => void;
-}
-
-/**
- * Componente para renderizar una única capa de máscara.
- * Usa React.memo para evitar re-renderizados si las props no cambian.
- */
-const MaskLayer = React.memo(function MaskLayer({
-  maskUrl,
-  color,
-  onMouseEnter,
-  onClick,
-}: MaskLayerProps) {
-  // Creamos los manejadores de eventos aquí para pasar la URL de la máscara.
-  // Como el componente está memoizado, estas funciones solo se recrean si las props cambian.
-  const handleMouseEnter = () => onMouseEnter(maskUrl);
-  const handleClick = () => onClick(maskUrl);
-
-  return (
-    <div
-      className="absolute top-0 left-0 w-full h-full transition-opacity duration-200"
-      style={{
-        backgroundColor: color,
-        maskImage: `url(${maskUrl})`,
-        WebkitMaskImage: `url(${maskUrl})`,
-        maskSize: "contain",
-        WebkitMaskSize: "contain",
-        maskRepeat: "no-repeat",
-        WebkitMaskRepeat: "no-repeat",
-        maskPosition: "center",
-        WebkitMaskPosition: "center",
-      }}
-      onMouseEnter={handleMouseEnter}
-      onClick={handleClick}
-    />
-  );
-});
-
-export default MaskLayer;
+import React from "react";
+
+interface MaskLayerProps {
+  maskUrl: string;
+  color: string;
+  onMouseEnter: (maskUrl: string) => void;
+  onClick: (maskUrl: string) => void;
+}
+
+/**
+ * Componente para renderizar una única capa de máscara.
+ * Usa React.memo para evitar re-renderizados si las props no cambian.
+ */
+const MaskLayer = React.memo(function MaskLayer({
+  maskUrl,
+  color,
+  onMouseEnter,
+  onClick,
+}: MaskLayerProps) {
+  // Creamos los manejadores de eventos aquí para pasar la URL de la máscara.
+  // Como el componente está memoizado, estas funciones solo se recrean si las props cambian.
+  const handleMouseEnter = () => onMouseEnter(maskUrl);
+  const handleClick = () => onClick(maskUrl);
+
+  return (
+    <div
+      className="absolute top-0 left-0 w-full h-full transition-opacity duration-200"
+      style={{
+        backgroundColor: color,
+        maskImage: `url(${maskUrl})`,
+        WebkitMaskImage: `url(${maskUrl})`,
+        maskSize: "contain",
+        WebkitMaskSize: "contain",
+        maskRepeat: "no-repeat",
+        WebkitMaskRepeat: "no-repeat",
+        maskPosition: "center",
+        WebkitMaskPosition: "center",
+      }}
+      onMouseEnter={handleMouseEnter}
+      onClick={handleClick}
+    />
+  );
+});
+
+export default MaskLayer;
diff --git a/frontend/src/features/roomVisualizer/RoomPreviewPanel.tsx b/frontend/src/features/roomVisualizer/RoomPreviewPanel.tsx
index a7274afc59a48c66ee166add6333d49648c0ae81..07231bdd9c8c8b5d55f7ddc059880954dadd7eac 100644
--- a/frontend/src/features/roomVisualizer/RoomPreviewPanel.tsx
+++ b/frontend/src/features/roomVisualizer/RoomPreviewPanel.tsx
@@ -1,338 +1,329 @@
-import {
-  type PointerEvent,
-  type SyntheticEvent,
-  type RefObject,
-} from "react";
-import {
-  ArrowLeft,
-  Share2,
-  Download,
-  MapPin,
-  ShoppingCart,
-  RefreshCw,
-  RotateCcw,
-  Paintbrush,
-  Loader2,
-} from "lucide-react";
-import type { Product } from "../../types";
-import type { SegmentMeta } from "../../hooks/useSegmentCanvas";
-
-interface RoomPreviewPanelProps {
-  previewImage?: string | null;
-  offset: { x: number; y: number };
-  zoom: number;
-  imageSize: { width: number; height: number };
-  wrapperRef: RefObject<HTMLDivElement | null>;
-  canvasRef: RefObject<HTMLCanvasElement | null>;
-  selectedProduct: Product | null;
-  selectedMasks: Set<number>;
-  hoveredMask: number;
-  segmentMeta: Map<number, SegmentMeta>;
-  isApplying: boolean;
-  onBack: () => void;
-  onPointerDown: (event: PointerEvent<HTMLDivElement>) => void;
-  onPointerMove: (event: PointerEvent<HTMLDivElement>) => void;
-  onPointerUp: (event: PointerEvent<HTMLDivElement>) => void;
-  updateImageSize: (img: HTMLImageElement) => void;
-  onCanvasMouseMove: (e: React.MouseEvent<HTMLCanvasElement>) => void;
-  onCanvasMouseLeave: () => void;
-  onCanvasClick: (e: React.MouseEvent<HTMLCanvasElement>) => void;
-  onApplyTexture: () => void;
-  onReset: () => void;
-  onDownload: () => Promise<void>;
-  onShare: () => Promise<void>;
-  maskCount?: number;
-}
-
-
-export function RoomPreviewPanel({
-  previewImage,
-  offset,
-  zoom,
-  imageSize,
-  wrapperRef,
-  canvasRef,
-  selectedProduct,
-  selectedMasks,
-  hoveredMask,
-  segmentMeta,
-  isApplying,
-  onBack,
-  onPointerDown,
-  onPointerMove,
-  onPointerUp,
-  updateImageSize,
-  onCanvasMouseMove,
-  onCanvasMouseLeave,
-  onCanvasClick,
-  onApplyTexture,
-  onReset,
-  onDownload,
-  onShare,
-  maskCount = 0,
-}: RoomPreviewPanelProps) {
-  const canApply = (selectedMasks.size > 0 || maskCount === 0) && selectedProduct != null;
-
-
-  const getLabel = (index: number) =>
-    segmentMeta.get(index)?.label ?? `Zona ${index}`;
-
-  return (
-    <div className="w-full h-full bg-white overflow-hidden">
-      <div className="relative h-full overflow-hidden lg:rounded-lg bg-[#f4f8ff]">
-
-        {/* ── Mobile top bar ───────────────────────────────────────── */}
-        {/* pr-12 reserva espacio a la derecha para el botón .hr-close del padre */}
-        <div className="lg:hidden absolute left-0 right-0 top-0 z-10 h-12 bg-white shadow-sm flex items-center justify-between px-3 pr-12">
-          <button
-            onClick={onBack}
-            className="p-2 rounded-full hover:bg-gray-100 transition-colors"
-          >
-            <ArrowLeft className="h-5 w-5 text-[#333]" />
-          </button>
-          <div className="flex items-center gap-1">
-            <button
-              onClick={onShare}
-              className="p-2 rounded-full hover:bg-[#eaf1ff] transition-colors"
-            >
-              <Share2 className="h-5 w-5 text-[#0047AB]" />
-            </button>
-            <button
-              onClick={onDownload}
-              className="p-2 rounded-full hover:bg-[#eaf1ff] transition-colors"
-            >
-              <Download className="h-5 w-5 text-[#0047AB]" />
-            </button>
-          </div>
-        </div>
-
-        {/* ── Desktop top bar ──────────────────────────────────────── */}
-        <div className="pointer-events-none hidden lg:flex absolute left-1/2 top-0 z-10 -translate-x-1/2 w-[80%] h-16 rounded-b-md bg-white shadow-sm items-center justify-center gap-4 px-3">
-          <button
-            onClick={onBack}
-            className="pointer-events-auto rounded-full bg-[#333333] px-4 py-2 text-sm font-semibold text-white hover:bg-black flex items-center gap-2"
-          >
-            <ArrowLeft className="h-4 w-4" /> Cambiar de Habitación
-          </button>
-          <span className="text-gray-400">|</span>
-          <button
-            onClick={onShare}
-            className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
-          >
-            <Share2 className="h-4 w-4 text-[#0047AB]" />
-            Compartir
-          </button>
-          <button
-            onClick={onDownload}
-            className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
-          >
-            <Download className="h-4 w-4 text-[#0047AB]" /> Descargar
-          </button>
-          <a
-            href="https://nauffargermany.com/gt/sucursales-2/"
-            target="_blank"
-            rel="noopener noreferrer"
-            className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
-          >
-            <MapPin className="h-4 w-4 text-[#0047AB]" /> Encuentra tu tienda
-          </a>
-          {selectedProduct?.detailUrl ? (
-            <a
-              href={selectedProduct.detailUrl}
-              target="_blank"
-              rel="noopener noreferrer"
-              className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
-            >
-              <ShoppingCart className="h-4 w-4 text-[#0047AB]" /> Ir a la página del producto
-            </a>
-          ) : (
-            <button
-              disabled
-              className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-gray-300 flex items-center gap-2 cursor-default"
-            >
-              <ShoppingCart className="h-4 w-4 text-gray-300" /> Ir a la página del producto
-            </button>
-          )}
-        </div>
-
-        {/* ── Área de imagen + canvas ──────────────────────────────── */}
-        <div
-          ref={wrapperRef}
-          className="absolute inset-x-0 top-12 lg:top-16 bottom-12 lg:bottom-16 flex items-center justify-center bg-[#edf4ff] overflow-hidden"
-          onPointerDown={onPointerDown}
-          onPointerMove={onPointerMove}
-          onPointerUp={onPointerUp}
-        >
-          {previewImage ? (
-            <div
-              style={{
-                transform: `translate(${offset.x}px, ${offset.y}px) scale(${zoom})`,
-                transformOrigin: "center center",
-                position: "relative",
-                display: "inline-flex",
-                lineHeight: 0,
-                ...(imageSize.width > 0
-                  ? { width: imageSize.width, height: imageSize.height }
-                  : {}),
-              }}
-            >
-              <img
-                src={previewImage}
-                alt="Vista previa de la habitación"
-                draggable={false}
-                onDragStart={(e) => e.preventDefault()}
-                onLoad={(event: SyntheticEvent<HTMLImageElement>) =>
-                  updateImageSize(event.currentTarget)
-                }
-                style={{
-                  display: "block",
-                  width: imageSize.width > 0 ? "100%" : "auto",
-                  height: imageSize.height > 0 ? "100%" : "auto",
-                  maxWidth: imageSize.width > 0 ? "none" : "100%",
-                  maxHeight: imageSize.height > 0 ? "none" : "100%",
-                  objectFit: "contain",
-                }}
-              />
-              <canvas
-                ref={canvasRef}
-                style={{
-                  position: "absolute",
-                  inset: 0,
-                  width: "100%",
-                  height: "100%",
-                  cursor: "crosshair",
-                }}
-                onMouseMove={onCanvasMouseMove}
-                onMouseLeave={onCanvasMouseLeave}
-                onClick={onCanvasClick}
-              />
-            </div>
-          ) : (
-            <div className="flex h-full w-full items-center justify-center text-[#707070] text-sm px-6 text-center">
-              No hay vista previa disponible aún.
-            </div>
-          )}
-        </div>
-
-        {/* ── Hint de selección ────────────────────────────────────── */}
-        {previewImage && selectedMasks.size === 0 && (
-          <div className="pointer-events-none absolute top-14 lg:top-20 left-1/2 -translate-x-1/2 z-10 bg-black/50 text-white text-xs px-3 py-1.5 rounded-full whitespace-nowrap">
-            {maskCount > 0 ? (
-              hoveredMask > 0
-                ? `${getLabel(hoveredMask)} — haz clic para seleccionar`
-                : "Haz clic sobre una zona de la imagen para seleccionarla"
-            ) : (
-              "Selecciona un producto de la lista para visualizarlo con IA"
-            )}
-          </div>
-        )}
-
-
-        {/* ── Mobile bottom bar ────────────────────────────────────── */}
-        <div className="pointer-events-none lg:hidden absolute left-0 right-0 bottom-0 z-10 h-12 bg-white border-t border-gray-100 shadow-sm flex items-center px-3 gap-2">
-          {selectedProduct && (
-            <div className="flex items-center gap-2 min-w-0 flex-1">
-              <img
-                src={selectedProduct.image}
-                alt={selectedProduct.name}
-                className="w-8 h-8 object-cover rounded-md border border-gray-200 shrink-0"
-              />
-              <div className="min-w-0">
-                <p className="text-[10px] text-[#707070] truncate">{selectedProduct.brand}</p>
-                <p className="text-xs font-semibold text-[#333] truncate leading-tight">{selectedProduct.name}</p>
-              </div>
-            </div>
-          )}
-          {!selectedProduct && selectedMasks.size > 0 && (
-            <p className="text-xs text-[#0047AB] font-medium truncate flex-1">
-              {[...selectedMasks].map(getLabel).join(", ")}
-            </p>
-          )}
-          {!selectedProduct && selectedMasks.size === 0 && <div className="flex-1" />}
-
-          <div className="flex items-center gap-1 ml-auto shrink-0">
-            {canApply && (
-              <button
-                onClick={onApplyTexture}
-                disabled={isApplying}
-                className="pointer-events-auto flex items-center gap-1.5 bg-[#0047AB] text-white px-3 py-1.5 rounded-full text-xs font-semibold hover:bg-[#003a94] disabled:opacity-60 transition-colors"
-              >
-                {isApplying ? (
-                  <Loader2 className="h-3 w-3 animate-spin" />
-                ) : (
-                  <Paintbrush className="h-3 w-3" />
-                )}
-                {isApplying ? "Aplicando..." : "Aplicar"}
-              </button>
-            )}
-            <button
-              onClick={onReset}
-              className="pointer-events-auto p-2 rounded-full hover:bg-[#eaf1ff] transition-colors"
-            >
-              <RefreshCw className="h-4 w-4 text-[#0047AB]" />
-            </button>
-          </div>
-        </div>
-
-        {/* ── Desktop bottom bar ───────────────────────────────────── */}
-        <div className="pointer-events-none hidden lg:flex absolute left-1/2 bottom-0 z-10 -translate-x-1/2 w-[80%] h-16 rounded-t-md bg-white border border-[#0047AB]/10 shadow-sm items-center justify-start gap-4 px-4">
-          {selectedProduct && (
-            <div className="pointer-events-none flex items-center gap-3">
-              <img
-                src={selectedProduct.image}
-                alt={selectedProduct.name}
-                className="w-10 h-10 object-cover rounded-md border border-gray-200"
-              />
-              <div>
-                <p className="text-[#707070] text-xs">{selectedProduct.brand}</p>
-                <p className="font-semibold text-[#333333] text-sm leading-tight">
-                  {selectedProduct.name}
-                </p>
-              </div>
-            </div>
-          )}
-
-          {selectedMasks.size > 0 && (
-            <p className="text-xs text-[#0047AB] font-medium truncate max-w-[260px]">
-              {[...selectedMasks].map(getLabel).join(", ")}
-            </p>
-          )}
-
-          <div className="flex-1" />
-
-          {canApply && (
-            <button
-              onClick={onApplyTexture}
-              disabled={isApplying}
-              className="pointer-events-auto flex items-center gap-2 bg-[#0047AB] text-white px-4 py-2 rounded-full text-sm font-semibold hover:bg-[#003a94] disabled:opacity-60 transition-colors"
-            >
-              {isApplying ? (
-                <Loader2 className="h-4 w-4 animate-spin" />
-              ) : (
-                <Paintbrush className="h-4 w-4" />
-              )}
-              {isApplying ? "Aplicando..." : "Aplicar textura"}
-            </button>
-          )}
-
-          <button
-            onClick={onReset}
-            className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
-          >
-            <span className="inline-flex items-center justify-center rounded-full bg-[#eaf1ff] p-2">
-              <RefreshCw className="h-4 w-4 text-[#0047AB]" />
-            </span>
-            Reiniciar
-          </button>
-          <button className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2">
-            <span className="inline-flex items-center justify-center rounded-full bg-[#eaf1ff] p-2">
-              <RotateCcw className="h-4 w-4 text-[#0047AB]" />
-            </span>
-            Girar
-          </button>
-        </div>
-
-      </div>
-    </div>
-  );
-}
+import {
+  type PointerEvent,
+  type SyntheticEvent,
+  type RefObject,
+} from "react";
+import {
+  ArrowLeft,
+  Share2,
+  Download,
+  MapPin,
+  ShoppingCart,
+  RefreshCw,
+  RotateCcw,
+  Paintbrush,
+  Loader2,
+} from "lucide-react";
+import type { Product } from "../../types";
+import type { SegmentMeta } from "../../hooks/useSegmentCanvas";
+
+interface RoomPreviewPanelProps {
+  previewImage?: string | null;
+  offset: { x: number; y: number };
+  zoom: number;
+  imageSize: { width: number; height: number };
+  wrapperRef: RefObject<HTMLDivElement | null>;
+  canvasRef: RefObject<HTMLCanvasElement | null>;
+  selectedProduct: Product | null;
+  selectedMasks: Set<number>;
+  hoveredMask: number;
+  segmentMeta: Map<number, SegmentMeta>;
+  isApplying: boolean;
+  onBack: () => void;
+  onPointerDown: (event: PointerEvent<HTMLDivElement>) => void;
+  onPointerMove: (event: PointerEvent<HTMLDivElement>) => void;
+  onPointerUp: (event: PointerEvent<HTMLDivElement>) => void;
+  updateImageSize: (img: HTMLImageElement) => void;
+  onCanvasMouseMove: (e: React.MouseEvent<HTMLCanvasElement>) => void;
+  onCanvasMouseLeave: () => void;
+  onCanvasClick: (e: React.MouseEvent<HTMLCanvasElement>) => void;
+  onApplyTexture: () => void;
+  onReset: () => void;
+  onDownload: () => Promise<void>;
+  onShare: () => Promise<void>;
+}
+
+export function RoomPreviewPanel({
+  previewImage,
+  offset,
+  zoom,
+  imageSize,
+  wrapperRef,
+  canvasRef,
+  selectedProduct,
+  selectedMasks,
+  hoveredMask,
+  segmentMeta,
+  isApplying,
+  onBack,
+  onPointerDown,
+  onPointerMove,
+  onPointerUp,
+  updateImageSize,
+  onCanvasMouseMove,
+  onCanvasMouseLeave,
+  onCanvasClick,
+  onApplyTexture,
+  onReset,
+  onDownload,
+  onShare,
+}: RoomPreviewPanelProps) {
+  const canApply = selectedMasks.size > 0 && selectedProduct != null;
+
+  const getLabel = (index: number) =>
+    segmentMeta.get(index)?.label ?? `Zona ${index}`;
+
+  return (
+    <div className="w-full h-full bg-white overflow-hidden">
+      <div className="relative h-full overflow-hidden lg:rounded-lg bg-[#f4f8ff]">
+
+        {/* ── Mobile top bar ───────────────────────────────────────── */}
+        {/* pr-12 reserva espacio a la derecha para el botón .hr-close del padre */}
+        <div className="lg:hidden absolute left-0 right-0 top-0 z-10 h-12 bg-white shadow-sm flex items-center justify-between px-3 pr-12">
+          <button
+            onClick={onBack}
+            className="p-2 rounded-full hover:bg-gray-100 transition-colors"
+          >
+            <ArrowLeft className="h-5 w-5 text-[#333]" />
+          </button>
+          <div className="flex items-center gap-1">
+            <button
+              onClick={onShare}
+              className="p-2 rounded-full hover:bg-[#eaf1ff] transition-colors"
+            >
+              <Share2 className="h-5 w-5 text-[#0047AB]" />
+            </button>
+            <button
+              onClick={onDownload}
+              className="p-2 rounded-full hover:bg-[#eaf1ff] transition-colors"
+            >
+              <Download className="h-5 w-5 text-[#0047AB]" />
+            </button>
+          </div>
+        </div>
+
+        {/* ── Desktop top bar ──────────────────────────────────────── */}
+        <div className="pointer-events-none hidden lg:flex absolute left-1/2 top-0 z-10 -translate-x-1/2 w-[80%] h-16 rounded-b-md bg-white shadow-sm items-center justify-center gap-4 px-3">
+          <button
+            onClick={onBack}
+            className="pointer-events-auto rounded-full bg-[#333333] px-4 py-2 text-sm font-semibold text-white hover:bg-black flex items-center gap-2"
+          >
+            <ArrowLeft className="h-4 w-4" /> Cambiar de Habitación
+          </button>
+          <span className="text-gray-400">|</span>
+          <button
+            onClick={onShare}
+            className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
+          >
+            <Share2 className="h-4 w-4 text-[#0047AB]" />
+            Compartir
+          </button>
+          <button
+            onClick={onDownload}
+            className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
+          >
+            <Download className="h-4 w-4 text-[#0047AB]" /> Descargar
+          </button>
+          <a
+            href="https://nauffargermany.com/gt/sucursales-2/"
+            target="_blank"
+            rel="noopener noreferrer"
+            className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
+          >
+            <MapPin className="h-4 w-4 text-[#0047AB]" /> Encuentra tu tienda
+          </a>
+          {selectedProduct?.detailUrl ? (
+            <a
+              href={selectedProduct.detailUrl}
+              target="_blank"
+              rel="noopener noreferrer"
+              className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
+            >
+              <ShoppingCart className="h-4 w-4 text-[#0047AB]" /> Ir a la página del producto
+            </a>
+          ) : (
+            <button
+              disabled
+              className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-gray-300 flex items-center gap-2 cursor-default"
+            >
+              <ShoppingCart className="h-4 w-4 text-gray-300" /> Ir a la página del producto
+            </button>
+          )}
+        </div>
+
+        {/* ── Área de imagen + canvas ──────────────────────────────── */}
+        <div
+          ref={wrapperRef}
+          className="absolute inset-x-0 top-12 lg:top-16 bottom-12 lg:bottom-16 flex items-center justify-center bg-[#edf4ff] overflow-hidden"
+          onPointerDown={onPointerDown}
+          onPointerMove={onPointerMove}
+          onPointerUp={onPointerUp}
+        >
+          {previewImage ? (
+            <div
+              style={{
+                transform: `translate(${offset.x}px, ${offset.y}px) scale(${zoom})`,
+                transformOrigin: "center center",
+                position: "relative",
+                display: "inline-flex",
+                lineHeight: 0,
+                ...(imageSize.width > 0
+                  ? { width: imageSize.width, height: imageSize.height }
+                  : {}),
+              }}
+            >
+              <img
+                src={previewImage}
+                alt="Vista previa de la habitación"
+                draggable={false}
+                onDragStart={(e) => e.preventDefault()}
+                onLoad={(event: SyntheticEvent<HTMLImageElement>) =>
+                  updateImageSize(event.currentTarget)
+                }
+                style={{
+                  display: "block",
+                  width: imageSize.width > 0 ? "100%" : "auto",
+                  height: imageSize.height > 0 ? "100%" : "auto",
+                  maxWidth: imageSize.width > 0 ? "none" : "100%",
+                  maxHeight: imageSize.height > 0 ? "none" : "100%",
+                  objectFit: "contain",
+                }}
+              />
+              <canvas
+                ref={canvasRef}
+                style={{
+                  position: "absolute",
+                  inset: 0,
+                  width: "100%",
+                  height: "100%",
+                  cursor: "crosshair",
+                }}
+                onMouseMove={onCanvasMouseMove}
+                onMouseLeave={onCanvasMouseLeave}
+                onClick={onCanvasClick}
+              />
+            </div>
+          ) : (
+            <div className="flex h-full w-full items-center justify-center text-[#707070] text-sm px-6 text-center">
+              No hay vista previa disponible aún.
+            </div>
+          )}
+        </div>
+
+        {/* ── Hint de selección ────────────────────────────────────── */}
+        {previewImage && selectedMasks.size === 0 && (
+          <div className="pointer-events-none absolute top-14 lg:top-20 left-1/2 -translate-x-1/2 z-10 bg-black/50 text-white text-xs px-3 py-1.5 rounded-full whitespace-nowrap">
+            {hoveredMask > 0
+              ? `${getLabel(hoveredMask)} — haz clic para seleccionar`
+              : "Haz clic sobre una zona de la imagen para seleccionarla"}
+          </div>
+        )}
+
+        {/* ── Mobile bottom bar ────────────────────────────────────── */}
+        <div className="pointer-events-none lg:hidden absolute left-0 right-0 bottom-0 z-10 h-12 bg-white border-t border-gray-100 shadow-sm flex items-center px-3 gap-2">
+          {selectedProduct && (
+            <div className="flex items-center gap-2 min-w-0 flex-1">
+              <img
+                src={selectedProduct.image}
+                alt={selectedProduct.name}
+                className="w-8 h-8 object-cover rounded-md border border-gray-200 shrink-0"
+              />
+              <div className="min-w-0">
+                <p className="text-[10px] text-[#707070] truncate">{selectedProduct.brand}</p>
+                <p className="text-xs font-semibold text-[#333] truncate leading-tight">{selectedProduct.name}</p>
+              </div>
+            </div>
+          )}
+          {!selectedProduct && selectedMasks.size > 0 && (
+            <p className="text-xs text-[#0047AB] font-medium truncate flex-1">
+              {[...selectedMasks].map(getLabel).join(", ")}
+            </p>
+          )}
+          {!selectedProduct && selectedMasks.size === 0 && <div className="flex-1" />}
+
+          <div className="flex items-center gap-1 ml-auto shrink-0">
+            {canApply && (
+              <button
+                onClick={onApplyTexture}
+                disabled={isApplying}
+                className="pointer-events-auto flex items-center gap-1.5 bg-[#0047AB] text-white px-3 py-1.5 rounded-full text-xs font-semibold hover:bg-[#003a94] disabled:opacity-60 transition-colors"
+              >
+                {isApplying ? (
+                  <Loader2 className="h-3 w-3 animate-spin" />
+                ) : (
+                  <Paintbrush className="h-3 w-3" />
+                )}
+                {isApplying ? "Aplicando..." : "Aplicar"}
+              </button>
+            )}
+            <button
+              onClick={onReset}
+              className="pointer-events-auto p-2 rounded-full hover:bg-[#eaf1ff] transition-colors"
+            >
+              <RefreshCw className="h-4 w-4 text-[#0047AB]" />
+            </button>
+          </div>
+        </div>
+
+        {/* ── Desktop bottom bar ───────────────────────────────────── */}
+        <div className="pointer-events-none hidden lg:flex absolute left-1/2 bottom-0 z-10 -translate-x-1/2 w-[80%] h-16 rounded-t-md bg-white border border-[#0047AB]/10 shadow-sm items-center justify-start gap-4 px-4">
+          {selectedProduct && (
+            <div className="pointer-events-none flex items-center gap-3">
+              <img
+                src={selectedProduct.image}
+                alt={selectedProduct.name}
+                className="w-10 h-10 object-cover rounded-md border border-gray-200"
+              />
+              <div>
+                <p className="text-[#707070] text-xs">{selectedProduct.brand}</p>
+                <p className="font-semibold text-[#333333] text-sm leading-tight">
+                  {selectedProduct.name}
+                </p>
+              </div>
+            </div>
+          )}
+
+          {selectedMasks.size > 0 && (
+            <p className="text-xs text-[#0047AB] font-medium truncate max-w-[260px]">
+              {[...selectedMasks].map(getLabel).join(", ")}
+            </p>
+          )}
+
+          <div className="flex-1" />
+
+          {canApply && (
+            <button
+              onClick={onApplyTexture}
+              disabled={isApplying}
+              className="pointer-events-auto flex items-center gap-2 bg-[#0047AB] text-white px-4 py-2 rounded-full text-sm font-semibold hover:bg-[#003a94] disabled:opacity-60 transition-colors"
+            >
+              {isApplying ? (
+                <Loader2 className="h-4 w-4 animate-spin" />
+              ) : (
+                <Paintbrush className="h-4 w-4" />
+              )}
+              {isApplying ? "Aplicando..." : "Aplicar textura"}
+            </button>
+          )}
+
+          <button
+            onClick={onReset}
+            className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2"
+          >
+            <span className="inline-flex items-center justify-center rounded-full bg-[#eaf1ff] p-2">
+              <RefreshCw className="h-4 w-4 text-[#0047AB]" />
+            </span>
+            Reiniciar
+          </button>
+          <button className="pointer-events-auto rounded-full bg-transparent px-4 py-2 text-sm font-medium text-[#0047AB] hover:bg-[#eaf1ff] flex items-center gap-2">
+            <span className="inline-flex items-center justify-center rounded-full bg-[#eaf1ff] p-2">
+              <RotateCcw className="h-4 w-4 text-[#0047AB]" />
+            </span>
+            Girar
+          </button>
+        </div>
+
+      </div>
+    </div>
+  );
+}
diff --git a/frontend/src/features/roomVisualizer/RoomVisualizer.tsx b/frontend/src/features/roomVisualizer/RoomVisualizer.tsx
index 71f1564a0ffe7ce042b4f15ed99868f6bc7e4a65..fa8f365fe8b33f3b1ac6c04521b1e5ded1795538 100644
--- a/frontend/src/features/roomVisualizer/RoomVisualizer.tsx
+++ b/frontend/src/features/roomVisualizer/RoomVisualizer.tsx
@@ -1,1000 +1,617 @@
-import {
-  useCallback,
-  useEffect,
-  useRef,
-  useState,
-  type PointerEvent,
-} from "react";
-import { ChevronDown } from "lucide-react";
-import { createRoot } from "react-dom/client";
-import { useLocation, useNavigate } from "react-router-dom";
-import { LayoutGrid, Search, SlidersHorizontal, Menu, X } from "lucide-react";
-import Swal from "sweetalert2";
-import {
-  WhatsappShareButton,
-  WhatsappIcon,
-  TelegramShareButton,
-  TelegramIcon,
-  TwitterShareButton,
-  XIcon,
-  FacebookShareButton,
-  FacebookIcon,
-  EmailShareButton,
-  EmailIcon,
-} from "react-share";
-import { ProductGroupCard, IndividualProductCard } from "./ProductCards";
-import { useRoomVisualizer } from "./roomVisualizerHooks";
-import { useCatalogProducts } from "./useCatalogProducts";
-import { RoomPreviewPanel } from "./RoomPreviewPanel";
-import useAppStore from "../../store/useAppStore";
-import { API_BASE } from "../../api/client";
-// No segmentation canvas: we remove mask-based flows and use defaults
-import { useApplyTexture } from "../../hooks/useApplyTexture";
-import type { SegmentMeta } from "../../hooks/useSegmentCanvas";
-
-type RoomVisualizerState = {
-  previewImage?: string;
-  filename?: string;
-  maskCount?: number;
-};
-
-// ── Hook para detectar mobile (< 1024px) ─────────────────────────────────────
-function useIsMobile() {
-  const [isMobile, setIsMobile] = useState(() => window.innerWidth < 1024);
-  useEffect(() => {
-    const handler = () => setIsMobile(window.innerWidth < 1024);
-    window.addEventListener("resize", handler);
-    return () => window.removeEventListener("resize", handler);
-  }, []);
-  return isMobile;
-}
-
-export default function RoomVisualizer() {
-  const location = useLocation();
-  const navigate = useNavigate();
-  const state = location.state as RoomVisualizerState | null;
-  const isMobile = useIsMobile();
-
-  const storedPreviewImage = useAppStore((store) => store.previewImage);
-  const segmentFilename = useAppStore((store) => store.segmentFilename);
-  const accumulatedFilename = useAppStore((store) => store.accumulatedFilename);
-  const setAccumulatedFilename = useAppStore(
-    (store) => store.setAccumulatedFilename,
-  );
-  const setSegmentResult = useAppStore((store) => store.setSegmentResult);
-  const setPreviewImage = useAppStore((store) => store.setPreviewImage);
-
-  // Restaurar segmentFilename y previewImage cuando se abre una sesión del historial
-  useEffect(() => {
-    if (state?.filename && state.filename !== segmentFilename) {
-      setSegmentResult(state.filename, state.maskCount ?? 0);
-      setAccumulatedFilename(null); // limpiar ediciones de sesión anterior
-    }
-    if (state?.previewImage) {
-      setPreviewImage(state.previewImage);
-    }
-    // Solo al montar — state no cambia tras la navegación
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, []);
-
-  const [currentPreviewImage, setCurrentPreviewImage] = useState<string | null>(
-    () => {
-      if (accumulatedFilename)
-        return `${API_BASE}/seg/image/${accumulatedFilename}`;
-      return state?.previewImage ?? storedPreviewImage ?? null;
-    },
-  );
-
-  const [zoom, setZoom] = useState(1);
-  const [offset, setOffset] = useState({ x: 0, y: 0 });
-  const [dragStart, setDragStart] = useState<{ x: number; y: number } | null>(
-    null,
-  );
-  const [imageSize, setImageSize] = useState({ width: 0, height: 0 });
-  const wrapperRef = useRef<HTMLDivElement>(null);
-
-  const { products, categories, loading, error } = useCatalogProducts();
-
-  // null = sin interacción (primera categoría abierta por defecto)
-  // Set vacío = usuario cerró todo deliberadamente
-  const [openCategoryIds, setOpenCategoryIds] = useState<Set<string> | null>(
-    null,
-  );
-
-  const isCategoryOpen = useCallback(
-    (id: string) => {
-      if (openCategoryIds === null) {
-        return categories.length > 0 && id === categories[0].id;
-      }
-      return openCategoryIds.has(id);
-    },
-    [openCategoryIds, categories],
-  );
-
-  const toggleCategory = useCallback(
-    (id: string) => {
-      setOpenCategoryIds((prev) => {
-        const base =
-          prev === null
-            ? categories.length > 0
-              ? new Set([categories[0].id])
-              : new Set<string>()
-            : new Set(prev);
-        if (base.has(id)) base.delete(id);
-        else base.add(id);
-        return base;
-      });
-    },
-    [categories],
-  );
-
-  const {
-    viewMode,
-    showGrid,
-    showList,
-    openProductId,
-    handleSelectProduct,
-    selectedProduct,
-    isSearchOpen,
-    setIsSearchOpen,
-    searchQuery,
-    setSearchQuery,
-    closeSearch,
-    filteredProducts,
-    chunkArray,
-  } = useRoomVisualizer(products);
-
-  useEffect(() => {
-    showList();
-  }, [showList]);
-
-  // Masks/segmentation removed: provide safe defaults/noops so panels keep working
-  const canvasRef = useRef<HTMLCanvasElement | null>(null);
-  const hoveredMask = -1;
-  const selectedMasks = new Set<number>();
-  const segmentMeta = new Map<number, SegmentMeta>();
-  const handleCanvasMouseMove = () => {};
-  const handleCanvasMouseLeave = () => {};
-  const handleCanvasClick = () => {};
-
-  const {
-    applyTexture,
-    applyTextureAI,
-    applyTextureOpenAI,
-    isApplying,
-    resetResult,
-  } = useApplyTexture();
-  const uploadedFile = useAppStore((s) => s.uploadedFile);
-
-  const applyTextureWith = useCallback(
-    async (texturePath: string) => {
-      if (isApplying) {
-        Swal.fire(
-          "Espera",
-          "Ya hay una operación en curso. Espera a que termine.",
-          "info",
-        );
-        return;
-      }
-      // Si el usuario subió una imagen en esta sesión, preferimos usar el endpoint OpenAI
-      if (uploadedFile) {
-        try {
-          // If the image was already uploaded to server, prefer passing the server filename (avoid sending generated previews)
-          const serverUrl = state?.previewImage ?? storedPreviewImage ?? null;
-          let source: File | string = uploadedFile;
-          // If preview points to uploads path, extract filename and send it instead
-          if (
-            typeof serverUrl === "string" &&
-            serverUrl.includes("/uploads/")
-          ) {
-            // serverUrl may be e.g. "http://localhost:8000/uploads/<filename>" or "/uploads/<filename>"
-            const idx = serverUrl.lastIndexOf("/uploads/");
-            const filename = serverUrl.substring(idx + "/uploads/".length);
-            source = filename;
-          }
-          const data = await applyTextureOpenAI(source, texturePath);
-          if (data?.url) {
-            setCurrentPreviewImage(data.url);
-          }
-        } catch (err) {
-          Swal.fire(
-            "Error",
-            err instanceof Error ? err.message : "Error al procesar",
-            "error",
-          );
-        }
-        return;
-      }
-      // Si no hay imagen subida y no hay segmentFilename, no hay flujo sin máscaras disponible
-      if (!segmentFilename) {
-        Swal.fire(
-          "Atención",
-          "Sube primero una imagen para aplicar el producto.",
-          "info",
-        );
-        return;
-      }
-      const baseFilename = accumulatedFilename ?? segmentFilename;
-      try {
-        // Si no hay máscaras seleccionadas (o no existen en el flujo simplificado), usamos IA
-        if (selectedMasks.size === 0) {
-          const data = await applyTextureAI(
-            baseFilename,
-            texturePath,
-            segmentFilename,
-          );
-
-          let resultData = data;
-          // Si es un job asíncrono, poll para esperar el resultado
-          if (data.job_id) {
-            const poll = async () => {
-              while (true) {
-                const res = await fetch(`${API_BASE}/seg/jobs/${data.job_id}`);
-                const job = await res.json();
-                if (job.status === "done") return job.result;
-                if (job.status === "failed")
-                  throw new Error(job.message || "AI failed");
-                await new Promise((r) => setTimeout(r, 2000));
-              }
-            };
-            resultData = await poll();
-          }
-
-          if (resultData?.url) {
-            setCurrentPreviewImage(
-              `${API_BASE}${resultData.url}?t=${Date.now()}`,
-            );
-            setAccumulatedFilename(resultData.filename);
-          }
-          return;
-        }
-
-        // Flujo tradicional (si hubiera máscaras)
-        const data = await applyTexture(
-          baseFilename,
-          [...selectedMasks],
-          texturePath,
-          segmentFilename,
-        );
-        if (data?.output_url) {
-          setCurrentPreviewImage(
-            `${API_BASE}${data.output_url}?t=${Date.now()}`,
-          );
-          setAccumulatedFilename(data.output_filename);
-        }
-      } catch (err) {
-        Swal.fire(
-          "Error",
-          err instanceof Error ? err.message : "Error al procesar",
-          "error",
-        );
-      }
-    },
-    [
-      applyTexture,
-      applyTextureAI,
-      segmentFilename,
-      selectedMasks,
-      accumulatedFilename,
-      setAccumulatedFilename,
-    ],
-  );
-
-  const handleApplyTexture = useCallback(async () => {
-    if (selectedProduct) await applyTextureWith(selectedProduct.ref);
-  }, [applyTextureWith, selectedProduct]);
-
-  const handleProductSelect = useCallback(
-    async (id: string | number | null) => {
-      handleSelectProduct(id);
-      if (!id) return;
-      const product = products.find((p) => p.id === id);
-      if (!product) return;
-      // If user uploaded a file, use OpenAI flow; otherwise require existing segmentFilename
-      if (uploadedFile) {
-        await applyTextureWith(product.ref);
-        return;
-      }
-      if (!segmentFilename) {
-        Swal.fire(
-          "Atención",
-          "Sube primero una imagen para aplicar el producto.",
-          "info",
-        );
-        return;
-      }
-      await applyTextureWith(product.ref);
-    },
-    [handleSelectProduct, segmentFilename, products, applyTextureWith],
-  );
-
-  const handleReset = useCallback(() => {
-    const original = state?.previewImage ?? storedPreviewImage ?? null;
-    setCurrentPreviewImage(original);
-    setAccumulatedFilename(null);
-    resetResult();
-  }, [state, storedPreviewImage, setAccumulatedFilename, resetResult]);
-
-  const handleDownload = useCallback(async () => {
-    if (!currentPreviewImage) return;
-    const response = await fetch(currentPreviewImage);
-    const blob = await response.blob();
-    const url = URL.createObjectURL(blob);
-    const a = document.createElement("a");
-    a.href = url;
-    a.download = `hyper-reality-${Date.now()}.jpg`;
-    document.body.appendChild(a);
-    a.click();
-    document.body.removeChild(a);
-    URL.revokeObjectURL(url);
-  }, [currentPreviewImage]);
-
-  const handleShare = useCallback(async (): Promise<void> => {
-    let shareUrl = window.location.href;
-    const outputFilename = accumulatedFilename;
-    if (outputFilename) {
-      try {
-        const res = await fetch(`${API_BASE}/api/share`, {
-          method: "POST",
-          headers: { "Content-Type": "application/json" },
-          body: JSON.stringify({
-            output_filename: outputFilename,
-            segment_filename: segmentFilename,
-          }),
-        });
-        if (res.ok) {
-          const data = (await res.json()) as { share_id: string };
-          shareUrl = `${window.location.origin}/app/share/${data.share_id}`;
-        }
-      } catch {
-        // fallback to current URL
-      }
-    }
-
-    const title = "My design with Hyper Reality Visualizer";
-    let reactRoot: ReturnType<typeof createRoot> | null = null;
-
-    await Swal.fire({
-      title: "Compartir diseño",
-      html: `
-        <div style="text-align:left">
-          <p style="font-size:13px;color:#666;margin-bottom:8px">Enlace de tu diseño:</p>
-          <div style="display:flex;gap:8px;align-items:center;margin-bottom:20px">
-            <input id="swal-share-url" readonly value="${shareUrl}"
-              style="flex:1;padding:8px 12px;border:1px solid #ddd;border-radius:8px;font-size:12px;background:#f9f9f9;outline:none;color:#333;" />
-            <button id="swal-copy-btn"
-              style="padding:8px 16px;background:#0047AB;color:white;border:none;border-radius:8px;cursor:pointer;font-size:13px;white-space:nowrap;font-weight:600;">
-              Copiar
-            </button>
-          </div>
-          <p style="font-size:13px;color:#666;margin-bottom:12px">Compartir en:</p>
-          <div id="swal-share-buttons" style="display:flex;gap:12px;flex-wrap:wrap;"></div>
-        </div>
-      `,
-      showConfirmButton: false,
-      showCloseButton: true,
-      width: 500,
-      didOpen: () => {
-        const copyBtn = document.getElementById("swal-copy-btn");
-        copyBtn?.addEventListener("click", async () => {
-          await navigator.clipboard.writeText(shareUrl).catch(() => {});
-          if (copyBtn) {
-            copyBtn.textContent = "¡Copiado!";
-            copyBtn.style.background = "#16a34a";
-          }
-          setTimeout(() => {
-            if (copyBtn) {
-              copyBtn.textContent = "Copiar";
-              copyBtn.style.background = "#0047AB";
-            }
-          }, 2000);
-        });
-        const container = document.getElementById("swal-share-buttons");
-        if (container) {
-          reactRoot = createRoot(container);
-          reactRoot.render(
-            <>
-              <WhatsappShareButton url={shareUrl} title={title}>
-                <WhatsappIcon size={48} round />
-              </WhatsappShareButton>
-              <TelegramShareButton url={shareUrl} title={title}>
-                <TelegramIcon size={48} round />
-              </TelegramShareButton>
-              <TwitterShareButton url={shareUrl} title={title}>
-                <XIcon size={48} round />
-              </TwitterShareButton>
-              <FacebookShareButton url={shareUrl}>
-                <FacebookIcon size={48} round />
-              </FacebookShareButton>
-              <EmailShareButton
-                url={shareUrl}
-                subject={title}
-                body="Mira mi diseño de habitación:"
-              >
-                <EmailIcon size={48} round />
-              </EmailShareButton>
-            </>,
-          );
-        }
-      },
-      willClose: () => {
-        reactRoot?.unmount();
-      },
-    });
-  }, [segmentFilename, accumulatedFilename]);
-
-  const clampOffset = useCallback(
-    (x: number, y: number, zoomValue: number) => {
-      const wrapper = wrapperRef.current;
-      if (!wrapper || imageSize.width === 0 || imageSize.height === 0)
-        return { x, y };
-      const containerRect = wrapper.getBoundingClientRect();
-      const scaledWidth = imageSize.width * zoomValue;
-      const scaledHeight = imageSize.height * zoomValue;
-      const maxX = Math.max(0, (scaledWidth - containerRect.width) / 2);
-      const maxY = Math.max(0, (scaledHeight - containerRect.height) / 2);
-      return {
-        x: Math.max(-maxX, Math.min(maxX, x)),
-        y: Math.max(-maxY, Math.min(maxY, y)),
-      };
-    },
-    [imageSize],
-  );
-
-  const updateImageSize = useCallback(
-    (img: HTMLImageElement) => {
-      const wrapper = wrapperRef.current;
-      if (!wrapper) return;
-      const containerRect = wrapper.getBoundingClientRect();
-      const naturalRatio = img.naturalWidth / img.naturalHeight;
-      const containerRatio = containerRect.width / containerRect.height;
-      const width =
-        naturalRatio > containerRatio
-          ? containerRect.width
-          : containerRect.height * naturalRatio;
-      const height =
-        naturalRatio > containerRatio
-          ? containerRect.width / naturalRatio
-          : containerRect.height;
-      setImageSize({ width, height });
-      setOffset((current) => clampOffset(current.x, current.y, zoom));
-    },
-    [clampOffset, zoom],
-  );
-
-  const handleWheel = useCallback(
-    (event: WheelEvent) => {
-      event.preventDefault();
-      setZoom((currentZoom) => {
-        const next = Math.min(
-          3,
-          Math.max(1, currentZoom - event.deltaY * 0.0015),
-        );
-        setOffset((current) => clampOffset(current.x, current.y, next));
-        return next;
-      });
-    },
-    [clampOffset],
-  );
-
-  useEffect(() => {
-    const el = wrapperRef.current;
-    if (!el) return;
-    el.addEventListener("wheel", handleWheel, { passive: false });
-    return () => el.removeEventListener("wheel", handleWheel);
-  }, [handleWheel]);
-
-  const handlePointerDown = useCallback(
-    (event: PointerEvent<HTMLDivElement>) => {
-      setDragStart({ x: event.clientX, y: event.clientY });
-    },
-    [],
-  );
-
-  const handlePointerMove = useCallback(
-    (event: PointerEvent<HTMLDivElement>) => {
-      if (!dragStart || zoom <= 1) return;
-      const dx = event.clientX - dragStart.x;
-      const dy = event.clientY - dragStart.y;
-      setOffset((current) => clampOffset(current.x + dx, current.y + dy, zoom));
-      setDragStart({ x: event.clientX, y: event.clientY });
-    },
-    [clampOffset, dragStart, zoom],
-  );
-
-  const handlePointerUp = useCallback(() => setDragStart(null), []);
-
-  // Props compartidos entre mobile y desktop para RoomPreviewPanel
-  const previewPanelProps = {
-    previewImage: currentPreviewImage,
-    offset,
-    zoom,
-    imageSize,
-    wrapperRef,
-    canvasRef,
-    selectedProduct,
-    selectedMasks,
-    hoveredMask,
-    segmentMeta,
-    isApplying,
-    onBack: () => navigate("/app"),
-    onPointerDown: handlePointerDown,
-    onPointerMove: handlePointerMove,
-    onPointerUp: handlePointerUp,
-    updateImageSize,
-    onCanvasMouseMove: handleCanvasMouseMove,
-    onCanvasMouseLeave: handleCanvasMouseLeave,
-    onCanvasClick: handleCanvasClick,
-    onApplyTexture: handleApplyTexture,
-    onReset: handleReset,
-    onDownload: handleDownload,
-    onShare: handleShare,
-    maskCount: state?.maskCount ?? 0,
-  };
-
-  // ── Mobile strip: thumbnails + búsqueda ──────────────────────────────────
-  const MobileProductStrip = (
-    <div
-      style={{
-        background: "#fff",
-        borderTop: "1px solid #e5e7eb",
-        flexShrink: 0,
-      }}
-    >
-      {isSearchOpen && (
-        <div style={{ padding: "8px 12px 4px" }}>
-          <div style={{ position: "relative" }}>
-            <Search
-              style={{
-                position: "absolute",
-                left: 10,
-                top: "50%",
-                transform: "translateY(-50%)",
-                width: 16,
-                height: 16,
-                color: "#9ca3af",
-              }}
-            />
-            <input
-              autoFocus
-              type="text"
-              placeholder="Buscar productos..."
-              value={searchQuery}
-              onChange={(e) => setSearchQuery(e.target.value)}
-              style={{
-                width: "100%",
-                paddingLeft: 34,
-                paddingRight: 32,
-                paddingTop: 8,
-                paddingBottom: 8,
-                borderRadius: 8,
-                border: "2px solid #0047AB",
-                outline: "none",
-                fontSize: 14,
-                color: "#333",
-                boxSizing: "border-box",
-              }}
-            />
-            <button
-              onClick={closeSearch}
-              style={{
-                position: "absolute",
-                right: 8,
-                top: "50%",
-                transform: "translateY(-50%)",
-                background: "none",
-                border: "none",
-                cursor: "pointer",
-                padding: 4,
-              }}
-            >
-              <X style={{ width: 14, height: 14, color: "#9ca3af" }} />
-            </button>
-          </div>
-        </div>
-      )}
-
-      {/* Thumbnails con scroll horizontal */}
-      <div
-        style={{
-          display: "flex",
-          overflowX: "auto",
-          gap: 8,
-          padding: "8px 12px",
-          scrollbarWidth: "none",
-        }}
-      >
-        {loading ? (
-          <div
-            style={{
-              display: "flex",
-              alignItems: "center",
-              justifyContent: "center",
-              width: "100%",
-              height: 64,
-              fontSize: 12,
-              color: "#9ca3af",
-            }}
-          >
-            Cargando...
-          </div>
-        ) : (
-          filteredProducts.map((product) => (
-            <button
-              key={product.id}
-              onClick={() => handleProductSelect(product.id)}
-              style={{
-                flexShrink: 0,
-                width: 64,
-                height: 64,
-                borderRadius: 12,
-                overflow: "hidden",
-                border:
-                  openProductId === product.id
-                    ? "2.5px solid #0047AB"
-                    : "2px solid #e5e7eb",
-                boxShadow:
-                  openProductId === product.id ? "0 0 0 2px #dbe7ff" : "none",
-                cursor: "pointer",
-                padding: 0,
-                background: "none",
-                transition: "border-color 0.15s",
-              }}
-            >
-              <img
-                src={product.image}
-                alt={product.name}
-                style={{
-                  width: "100%",
-                  height: "100%",
-                  objectFit: "cover",
-                  display: "block",
-                }}
-              />
-            </button>
-          ))
-        )}
-      </div>
-
-      {/* Info del producto + íconos */}
-      <div
-        style={{
-          display: "flex",
-          alignItems: "center",
-          padding: "0 12px 10px",
-          gap: 8,
-          minHeight: 36,
-        }}
-      >
-        {selectedProduct ? (
-          <div style={{ flex: 1, minWidth: 0 }}>
-            <p
-              style={{
-                fontSize: 10,
-                color: "#707070",
-                textTransform: "uppercase",
-                letterSpacing: "0.05em",
-                margin: 0,
-                lineHeight: 1,
-              }}
-            >
-              {selectedProduct.brand}
-            </p>
-            <p
-              style={{
-                fontSize: 12,
-                fontWeight: 600,
-                color: "#333",
-                margin: 0,
-                overflow: "hidden",
-                textOverflow: "ellipsis",
-                whiteSpace: "nowrap",
-              }}
-            >
-              {selectedProduct.name}
-            </p>
-          </div>
-        ) : (
-          <div style={{ flex: 1 }} />
-        )}
-        <div style={{ display: "flex", gap: 4, flexShrink: 0 }}>
-          <button
-            onClick={() => setIsSearchOpen(!isSearchOpen)}
-            style={{
-              padding: 6,
-              borderRadius: 8,
-              border: "none",
-              background: "none",
-              cursor: "pointer",
-            }}
-          >
-            <Search style={{ width: 16, height: 16, color: "#0047AB" }} />
-          </button>
-          <button
-            style={{
-              padding: 6,
-              borderRadius: 8,
-              border: "none",
-              background: "none",
-              cursor: "pointer",
-            }}
-          >
-            <SlidersHorizontal
-              style={{ width: 16, height: 16, color: "#0047AB" }}
-            />
-          </button>
-        </div>
-      </div>
-    </div>
-  );
-
-  // ── Desktop sidebar ───────────────────────────────────────────────────────
-  const DesktopSidebar = (
-    <div
-      style={{
-        width: "25%",
-        height: "100%",
-        display: "flex",
-        flexDirection: "column",
-        borderRight: "1px solid rgba(0,71,171,0.1)",
-        background: "#fff",
-        flexShrink: 0,
-      }}
-    >
-      <div style={{ padding: "24px 24px 0" }}>
-        <div style={{ height: 1, background: "#e5e7eb", width: "100%" }} />
-
-        {/* Barra de herramientas */}
-        <div
-          style={{ display: "flex", alignItems: "center", gap: 8, height: 46 }}
-        >
-          {!isSearchOpen && (
-            <button
-              onClick={() => setIsSearchOpen(true)}
-              className="p-3 rounded-lg border border-[#0047AB] bg-[#0047AB] text-white hover:bg-[#003a94] transition-all duration-300 flex items-center justify-center shadow-sm"
-            >
-              <Search className="w-5 h-5" />
-            </button>
-          )}
-          <button className="flex-1 flex items-center justify-center gap-2 px-4 py-2.5 rounded-lg border border-[#0047AB] bg-white text-[#0047AB] hover:bg-[#eaf1ff] transition-all duration-300 shadow-sm">
-            <SlidersHorizontal className="w-4 h-4 text-[#0047AB]" />
-            <span className="font-medium text-sm">Filtros</span>
-          </button>
-          <div className="flex border border-gray-300 rounded-lg overflow-hidden shadow-sm">
-            <button
-              onClick={showList}
-              className={`p-2.5 flex items-center justify-center transition-colors ${viewMode === "list" ? "bg-[#0047AB] text-white" : "bg-white text-[#0047AB] hover:bg-[#eaf1ff] border-r border-[#dbe7ff]"}`}
-            >
-              <Menu className="w-5 h-5" />
-            </button>
-            <button
-              onClick={showGrid}
-              className={`p-2.5 flex items-center justify-center transition-colors ${viewMode === "grid" ? "bg-[#0047AB] text-white" : "bg-white text-[#0047AB] hover:bg-[#eaf1ff]"}`}
-            >
-              <LayoutGrid className="w-5 h-5" />
-            </button>
-          </div>
-        </div>
-
-        {isSearchOpen && (
-          <div className="animate-in slide-in-from-top-2 fade-in duration-300">
-            <div className="relative">
-              <Search className="absolute left-3 top-1/2 -translate-y-1/2 w-5 h-5 text-gray-400" />
-              <input
-                autoFocus
-                type="text"
-                placeholder="¿Qué estás buscando?..."
-                value={searchQuery}
-                onChange={(e) => setSearchQuery(e.target.value)}
-                className="w-full pl-11 pr-10 py-3 rounded-lg border-2 border-[#0047AB] bg-white focus:outline-none transition-all text-sm text-[#333333]"
-              />
-              <button
-                onClick={closeSearch}
-                className="absolute right-3 top-1/2 -translate-y-1/2 p-1 text-gray-400 hover:text-gray-600 bg-white rounded-full shadow-sm"
-              >
-                <X className="w-4 h-4" />
-              </button>
-            </div>
-          </div>
-        )}
-      </div>
-
-      {/* Lista de productos con acordeón por categoría */}
-      <div className="flex-1 overflow-y-auto py-2">
-        {loading ? (
-          <div className="flex items-center justify-center h-32 text-sm text-gray-400">
-            Cargando productos...
-          </div>
-        ) : error ? (
-          <div className="flex items-center justify-center h-32 text-sm text-red-400">
-            {error}
-          </div>
-        ) : searchQuery ? (
-          /* Búsqueda activa → lista plana de resultados */
-          <div className={viewMode === "grid" ? "px-4" : "px-2"}>
-            {filteredProducts.length === 0 ? (
-              <div className="flex items-center justify-center h-24 text-sm text-gray-400">
-                Sin resultados
-              </div>
-            ) : viewMode === "grid" ? (
-              <div className="flex flex-col gap-4">
-                {chunkArray(filteredProducts, 3).map((group, i) => (
-                  <ProductGroupCard
-                    key={i}
-                    group={group}
-                    openProductId={openProductId}
-                    onSelectProduct={handleProductSelect}
-                  />
-                ))}
-              </div>
-            ) : (
-              <div className="grid grid-cols-1 gap-3">
-                {filteredProducts.map((product) => (
-                  <IndividualProductCard
-                    key={product.id}
-                    product={product}
-                    isSelected={openProductId === product.id}
-                    onToggle={() => handleProductSelect(product.id)}
-                  />
-                ))}
-              </div>
-            )}
-          </div>
-        ) : (
-          /* Sin búsqueda → acordeón por categoría */
-          <div className="flex flex-col">
-            {categories.map((cat) => {
-              const isOpen = isCategoryOpen(cat.id);
-              return (
-                <div
-                  key={cat.id}
-                  className="border-b border-gray-100 last:border-0"
-                >
-                  <button
-                    onClick={() => toggleCategory(cat.id)}
-                    className="w-full flex items-center justify-between px-4 py-3 hover:bg-[#f4f8ff] transition-colors text-left"
-                  >
-                    <div className="flex items-center gap-2 min-w-0">
-                      <span className="font-semibold text-sm text-[#333] truncate">
-                        {cat.nombre}
-                      </span>
-                      <span className="text-xs text-[#0047AB] bg-[#eaf1ff] px-1.5 py-0.5 rounded-full flex-shrink-0">
-                        {cat.products.length}
-                      </span>
-                    </div>
-                    <ChevronDown
-                      className={`w-4 h-4 text-[#0047AB] flex-shrink-0 transition-transform duration-200 ${isOpen ? "rotate-180" : ""}`}
-                    />
-                  </button>
-
-                  {isOpen && (
-                    <div
-                      className={
-                        viewMode === "grid" ? "px-4 pb-4" : "px-2 pb-2"
-                      }
-                    >
-                      {viewMode === "grid" ? (
-                        <div className="flex flex-col gap-4">
-                          {chunkArray(cat.products, 3).map((group, i) => (
-                            <ProductGroupCard
-                              key={i}
-                              group={group}
-                              openProductId={openProductId}
-                              onSelectProduct={handleProductSelect}
-                            />
-                          ))}
-                        </div>
-                      ) : (
-                        <div className="grid grid-cols-1 gap-3">
-                          {cat.products.map((product) => (
-                            <IndividualProductCard
-                              key={product.id}
-                              product={product}
-                              isSelected={openProductId === product.id}
-                              onToggle={() => handleProductSelect(product.id)}
-                            />
-                          ))}
-                        </div>
-                      )}
-                    </div>
-                  )}
-                </div>
-              );
-            })}
-          </div>
-        )}
-      </div>
-    </div>
-  );
-
-  return (
-    <div
-      style={{
-        height: "100svh",
-        width: "100%",
-        background: "#fff",
-        fontFamily: "sans-serif",
-        color: "#000",
-        display: "flex",
-        flexDirection: "column",
-      }}
-    >
-      {isApplying && (
-        <div
-          aria-hidden={!isApplying}
-          style={{
-            position: "fixed",
-            inset: 0,
-            display: "flex",
-            alignItems: "center",
-            justifyContent: "center",
-            background: "rgba(0,0,0,0.45)",
-            zIndex: 9999,
-            backdropFilter: "blur(2px)",
-            WebkitBackdropFilter: "blur(2px)",
-          }}
-        >
-          <div
-            style={{
-              display: "flex",
-              flexDirection: "column",
-              alignItems: "center",
-              gap: 12,
-              padding: 20,
-              borderRadius: 12,
-              background: "rgba(255,255,255,0.98)",
-              boxShadow: "0 6px 24px rgba(0,0,0,0.3)",
-              minWidth: 220,
-            }}
-          >
-            <div
-              style={{
-                width: 48,
-                height: 48,
-                borderRadius: 24,
-                border: "4px solid #e6e6e6",
-                borderTopColor: "#0047AB",
-                animation: "hr-spin 1s linear infinite",
-              }}
-            />
-            <div style={{ fontSize: 14, color: "#111", textAlign: "center" }}>
-              Generando imagen… Por favor espera
-            </div>
-          </div>
-          <style>{`@keyframes hr-spin { from { transform: rotate(0deg) } to { transform: rotate(360deg) } }`}</style>
-        </div>
-      )}
-      {isMobile ? (
-        // ── Layout Mobile: imagen arriba, strip de thumbnails abajo ──────────
-        <div
-          style={{
-            flex: 1,
-            display: "flex",
-            flexDirection: "column",
-            minHeight: 0,
-          }}
-        >
-          <div style={{ flex: 1, minHeight: 0, overflow: "hidden" }}>
-            <RoomPreviewPanel {...previewPanelProps} />
-          </div>
-          {MobileProductStrip}
-        </div>
-      ) : (
-        // ── Layout Desktop: sidebar izquierda + imagen derecha ───────────────
-        <div
-          style={{
-            flex: 1,
-            display: "flex",
-            flexDirection: "row",
-            minHeight: 0,
-          }}
-        >
-          {DesktopSidebar}
-          <div style={{ flex: 1, minWidth: 0, overflow: "hidden" }}>
-            <RoomPreviewPanel {...previewPanelProps} />
-          </div>
-        </div>
-      )}
-    </div>
-  );
-}
+import {
+  useCallback,
+  useEffect,
+  useRef,
+  useState,
+  type PointerEvent,
+} from "react";
+import { ChevronDown } from "lucide-react";
+import { createRoot } from "react-dom/client";
+import { useLocation, useNavigate } from "react-router-dom";
+import {
+  LayoutGrid,
+  Search,
+  SlidersHorizontal,
+  Menu,
+  X,
+} from "lucide-react";
+import Swal from "sweetalert2";
+import {
+  WhatsappShareButton, WhatsappIcon,
+  TelegramShareButton, TelegramIcon,
+  TwitterShareButton, XIcon,
+  FacebookShareButton, FacebookIcon,
+  EmailShareButton, EmailIcon,
+} from "react-share";
+import { ProductGroupCard, IndividualProductCard } from "./ProductCards";
+import { useRoomVisualizer } from "./roomVisualizerHooks";
+import { useCatalogProducts } from "./useCatalogProducts";
+import { RoomPreviewPanel } from "./RoomPreviewPanel";
+import useAppStore from "../../store/useAppStore";
+import { useSegmentCanvas } from "../../hooks/useSegmentCanvas";
+import { useApplyTexture } from "../../hooks/useApplyTexture";
+import { API_BASE } from "../../api/client";
+
+type RoomVisualizerState = {
+  previewImage?: string;
+  filename?: string;
+  maskCount?: number;
+};
+
+// ── Hook para detectar mobile (< 1024px) ─────────────────────────────────────
+function useIsMobile() {
+  const [isMobile, setIsMobile] = useState(() => window.innerWidth < 1024);
+  useEffect(() => {
+    const handler = () => setIsMobile(window.innerWidth < 1024);
+    window.addEventListener("resize", handler);
+    return () => window.removeEventListener("resize", handler);
+  }, []);
+  return isMobile;
+}
+
+export default function RoomVisualizer() {
+  const location = useLocation();
+  const navigate = useNavigate();
+  const state = location.state as RoomVisualizerState | null;
+  const isMobile = useIsMobile();
+
+  const storedPreviewImage = useAppStore((store) => store.previewImage);
+  const segmentFilename = useAppStore((store) => store.segmentFilename);
+  const accumulatedFilename = useAppStore((store) => store.accumulatedFilename);
+  const setAccumulatedFilename = useAppStore((store) => store.setAccumulatedFilename);
+  const setSegmentResult = useAppStore((store) => store.setSegmentResult);
+  const setPreviewImage = useAppStore((store) => store.setPreviewImage);
+
+  // Restaurar segmentFilename y previewImage cuando se abre una sesión del historial
+  useEffect(() => {
+    if (state?.filename && state.filename !== segmentFilename) {
+      setSegmentResult(state.filename, state.maskCount ?? 0);
+      setAccumulatedFilename(null); // limpiar ediciones de sesión anterior
+    }
+    if (state?.previewImage) {
+      setPreviewImage(state.previewImage);
+    }
+  // Solo al montar — state no cambia tras la navegación
+  // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, []);
+
+  const [currentPreviewImage, setCurrentPreviewImage] = useState<string | null>(() => {
+    if (accumulatedFilename) return `${API_BASE}/seg/image/${accumulatedFilename}`;
+    return state?.previewImage ?? storedPreviewImage ?? null;
+  });
+
+  const [zoom, setZoom] = useState(1);
+  const [offset, setOffset] = useState({ x: 0, y: 0 });
+  const [dragStart, setDragStart] = useState<{ x: number; y: number } | null>(null);
+  const [imageSize, setImageSize] = useState({ width: 0, height: 0 });
+  const wrapperRef = useRef<HTMLDivElement>(null);
+
+  const { products, categories, loading, error } = useCatalogProducts();
+
+  // null = sin interacción (primera categoría abierta por defecto)
+  // Set vacío = usuario cerró todo deliberadamente
+  const [openCategoryIds, setOpenCategoryIds] = useState<Set<string> | null>(null);
+
+  const isCategoryOpen = useCallback(
+    (id: string) => {
+      if (openCategoryIds === null) {
+        return categories.length > 0 && id === categories[0].id;
+      }
+      return openCategoryIds.has(id);
+    },
+    [openCategoryIds, categories],
+  );
+
+  const toggleCategory = useCallback((id: string) => {
+    setOpenCategoryIds((prev) => {
+      const base =
+        prev === null
+          ? categories.length > 0
+            ? new Set([categories[0].id])
+            : new Set<string>()
+          : new Set(prev);
+      if (base.has(id)) base.delete(id);
+      else base.add(id);
+      return base;
+    });
+  }, [categories]);
+
+  const {
+    viewMode, showGrid, showList,
+    openProductId, handleSelectProduct, selectedProduct,
+    isSearchOpen, setIsSearchOpen,
+    searchQuery, setSearchQuery, closeSearch,
+    filteredProducts, chunkArray,
+  } = useRoomVisualizer(products);
+
+  useEffect(() => { showList(); }, [showList]);
+
+
+  const {
+    canvasRef,
+    hoveredMask,
+    selectedMasks,
+    segmentMeta,
+    handleCanvasMouseMove,
+    handleCanvasMouseLeave,
+    handleCanvasClick,
+    clearSelection,
+  } = useSegmentCanvas(segmentFilename);
+
+  const { applyTexture, isApplying, resetResult } = useApplyTexture();
+
+  const applyTextureWith = useCallback(
+    async (texturePath: string) => {
+      if (!segmentFilename || selectedMasks.size === 0) return;
+      const baseFilename = accumulatedFilename ?? segmentFilename;
+      try {
+        const data = await applyTexture(baseFilename, [...selectedMasks], texturePath, segmentFilename);
+        if (data?.output_url) {
+          setCurrentPreviewImage(`${API_BASE}${data.output_url}?t=${Date.now()}`);
+          setAccumulatedFilename(data.output_filename);
+          clearSelection();
+        }
+      } catch {
+        // error ya guardado en el hook
+      }
+    },
+    [applyTexture, segmentFilename, selectedMasks, clearSelection, accumulatedFilename, setAccumulatedFilename],
+  );
+
+  const handleApplyTexture = useCallback(async () => {
+    if (selectedProduct) await applyTextureWith(selectedProduct.ref);
+  }, [applyTextureWith, selectedProduct]);
+
+  const handleProductSelect = useCallback(
+    async (id: string | number | null) => {
+      handleSelectProduct(id);
+      if (!id || selectedMasks.size === 0 || !segmentFilename) return;
+      const product = products.find((p) => p.id === id);
+      if (product) await applyTextureWith(product.ref);
+    },
+    [handleSelectProduct, selectedMasks, segmentFilename, products, applyTextureWith],
+  );
+
+  const handleReset = useCallback(() => {
+    const original = state?.previewImage ?? storedPreviewImage ?? null;
+    setCurrentPreviewImage(original);
+    setAccumulatedFilename(null);
+    clearSelection();
+    resetResult();
+  }, [state, storedPreviewImage, setAccumulatedFilename, clearSelection, resetResult]);
+
+  const handleDownload = useCallback(async () => {
+    if (!currentPreviewImage) return;
+    const response = await fetch(currentPreviewImage);
+    const blob = await response.blob();
+    const url = URL.createObjectURL(blob);
+    const a = document.createElement("a");
+    a.href = url;
+    a.download = `hyper-reality-${Date.now()}.jpg`;
+    document.body.appendChild(a);
+    a.click();
+    document.body.removeChild(a);
+    URL.revokeObjectURL(url);
+  }, [currentPreviewImage]);
+
+  const handleShare = useCallback(async (): Promise<void> => {
+    let shareUrl = window.location.href;
+    const outputFilename = accumulatedFilename;
+    if (outputFilename) {
+      try {
+        const res = await fetch(`${API_BASE}/api/share`, {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify({ output_filename: outputFilename, segment_filename: segmentFilename }),
+        });
+        if (res.ok) {
+          const data = (await res.json()) as { share_id: string };
+          shareUrl = `${window.location.origin}/app/share/${data.share_id}`;
+        }
+      } catch {
+        // fallback to current URL
+      }
+    }
+
+    const title = "My design with Hyper Reality Visualizer";
+    let reactRoot: ReturnType<typeof createRoot> | null = null;
+
+    await Swal.fire({
+      title: "Compartir diseño",
+      html: `
+        <div style="text-align:left">
+          <p style="font-size:13px;color:#666;margin-bottom:8px">Enlace de tu diseño:</p>
+          <div style="display:flex;gap:8px;align-items:center;margin-bottom:20px">
+            <input id="swal-share-url" readonly value="${shareUrl}"
+              style="flex:1;padding:8px 12px;border:1px solid #ddd;border-radius:8px;font-size:12px;background:#f9f9f9;outline:none;color:#333;" />
+            <button id="swal-copy-btn"
+              style="padding:8px 16px;background:#0047AB;color:white;border:none;border-radius:8px;cursor:pointer;font-size:13px;white-space:nowrap;font-weight:600;">
+              Copiar
+            </button>
+          </div>
+          <p style="font-size:13px;color:#666;margin-bottom:12px">Compartir en:</p>
+          <div id="swal-share-buttons" style="display:flex;gap:12px;flex-wrap:wrap;"></div>
+        </div>
+      `,
+      showConfirmButton: false,
+      showCloseButton: true,
+      width: 500,
+      didOpen: () => {
+        const copyBtn = document.getElementById("swal-copy-btn");
+        copyBtn?.addEventListener("click", async () => {
+          await navigator.clipboard.writeText(shareUrl).catch(() => {});
+          if (copyBtn) { copyBtn.textContent = "¡Copiado!"; copyBtn.style.background = "#16a34a"; }
+          setTimeout(() => {
+            if (copyBtn) { copyBtn.textContent = "Copiar"; copyBtn.style.background = "#0047AB"; }
+          }, 2000);
+        });
+        const container = document.getElementById("swal-share-buttons");
+        if (container) {
+          reactRoot = createRoot(container);
+          reactRoot.render(
+            <>
+              <WhatsappShareButton url={shareUrl} title={title}><WhatsappIcon size={48} round /></WhatsappShareButton>
+              <TelegramShareButton url={shareUrl} title={title}><TelegramIcon size={48} round /></TelegramShareButton>
+              <TwitterShareButton url={shareUrl} title={title}><XIcon size={48} round /></TwitterShareButton>
+              <FacebookShareButton url={shareUrl}><FacebookIcon size={48} round /></FacebookShareButton>
+              <EmailShareButton url={shareUrl} subject={title} body="Mira mi diseño de habitación:"><EmailIcon size={48} round /></EmailShareButton>
+            </>,
+          );
+        }
+      },
+      willClose: () => { reactRoot?.unmount(); },
+    });
+  }, [segmentFilename, accumulatedFilename]);
+
+  const clampOffset = useCallback(
+    (x: number, y: number, zoomValue: number) => {
+      const wrapper = wrapperRef.current;
+      if (!wrapper || imageSize.width === 0 || imageSize.height === 0) return { x, y };
+      const containerRect = wrapper.getBoundingClientRect();
+      const scaledWidth = imageSize.width * zoomValue;
+      const scaledHeight = imageSize.height * zoomValue;
+      const maxX = Math.max(0, (scaledWidth - containerRect.width) / 2);
+      const maxY = Math.max(0, (scaledHeight - containerRect.height) / 2);
+      return {
+        x: Math.max(-maxX, Math.min(maxX, x)),
+        y: Math.max(-maxY, Math.min(maxY, y)),
+      };
+    },
+    [imageSize],
+  );
+
+  const updateImageSize = useCallback(
+    (img: HTMLImageElement) => {
+      const wrapper = wrapperRef.current;
+      if (!wrapper) return;
+      const containerRect = wrapper.getBoundingClientRect();
+      const naturalRatio = img.naturalWidth / img.naturalHeight;
+      const containerRatio = containerRect.width / containerRect.height;
+      const width = naturalRatio > containerRatio ? containerRect.width : containerRect.height * naturalRatio;
+      const height = naturalRatio > containerRatio ? containerRect.width / naturalRatio : containerRect.height;
+      setImageSize({ width, height });
+      setOffset((current) => clampOffset(current.x, current.y, zoom));
+    },
+    [clampOffset, zoom],
+  );
+
+  const handleWheel = useCallback(
+    (event: WheelEvent) => {
+      event.preventDefault();
+      setZoom((currentZoom) => {
+        const next = Math.min(3, Math.max(1, currentZoom - event.deltaY * 0.0015));
+        setOffset((current) => clampOffset(current.x, current.y, next));
+        return next;
+      });
+    },
+    [clampOffset],
+  );
+
+  useEffect(() => {
+    const el = wrapperRef.current;
+    if (!el) return;
+    el.addEventListener("wheel", handleWheel, { passive: false });
+    return () => el.removeEventListener("wheel", handleWheel);
+  }, [handleWheel]);
+
+  const handlePointerDown = useCallback((event: PointerEvent<HTMLDivElement>) => {
+    setDragStart({ x: event.clientX, y: event.clientY });
+  }, []);
+
+  const handlePointerMove = useCallback(
+    (event: PointerEvent<HTMLDivElement>) => {
+      if (!dragStart || zoom <= 1) return;
+      const dx = event.clientX - dragStart.x;
+      const dy = event.clientY - dragStart.y;
+      setOffset((current) => clampOffset(current.x + dx, current.y + dy, zoom));
+      setDragStart({ x: event.clientX, y: event.clientY });
+    },
+    [clampOffset, dragStart, zoom],
+  );
+
+  const handlePointerUp = useCallback(() => setDragStart(null), []);
+
+  // Props compartidos entre mobile y desktop para RoomPreviewPanel
+  const previewPanelProps = {
+    previewImage: currentPreviewImage,
+    offset,
+    zoom,
+    imageSize,
+    wrapperRef,
+    canvasRef,
+    selectedProduct,
+    selectedMasks,
+    hoveredMask,
+    segmentMeta,
+    isApplying,
+    onBack: () => navigate("/app"),
+    onPointerDown: handlePointerDown,
+    onPointerMove: handlePointerMove,
+    onPointerUp: handlePointerUp,
+    updateImageSize,
+    onCanvasMouseMove: handleCanvasMouseMove,
+    onCanvasMouseLeave: handleCanvasMouseLeave,
+    onCanvasClick: handleCanvasClick,
+    onApplyTexture: handleApplyTexture,
+    onReset: handleReset,
+    onDownload: handleDownload,
+    onShare: handleShare,
+  };
+
+  // ── Mobile strip: thumbnails + búsqueda ──────────────────────────────────
+  const MobileProductStrip = (
+    <div style={{ background: "#fff", borderTop: "1px solid #e5e7eb", flexShrink: 0 }}>
+      {isSearchOpen && (
+        <div style={{ padding: "8px 12px 4px" }}>
+          <div style={{ position: "relative" }}>
+            <Search style={{ position: "absolute", left: 10, top: "50%", transform: "translateY(-50%)", width: 16, height: 16, color: "#9ca3af" }} />
+            <input
+              autoFocus
+              type="text"
+              placeholder="Buscar productos..."
+              value={searchQuery}
+              onChange={(e) => setSearchQuery(e.target.value)}
+              style={{
+                width: "100%",
+                paddingLeft: 34,
+                paddingRight: 32,
+                paddingTop: 8,
+                paddingBottom: 8,
+                borderRadius: 8,
+                border: "2px solid #0047AB",
+                outline: "none",
+                fontSize: 14,
+                color: "#333",
+                boxSizing: "border-box",
+              }}
+            />
+            <button
+              onClick={closeSearch}
+              style={{ position: "absolute", right: 8, top: "50%", transform: "translateY(-50%)", background: "none", border: "none", cursor: "pointer", padding: 4 }}
+            >
+              <X style={{ width: 14, height: 14, color: "#9ca3af" }} />
+            </button>
+          </div>
+        </div>
+      )}
+
+      {/* Thumbnails con scroll horizontal */}
+      <div style={{ display: "flex", overflowX: "auto", gap: 8, padding: "8px 12px", scrollbarWidth: "none" }}>
+        {loading ? (
+          <div style={{ display: "flex", alignItems: "center", justifyContent: "center", width: "100%", height: 64, fontSize: 12, color: "#9ca3af" }}>
+            Cargando...
+          </div>
+        ) : (
+          filteredProducts.map((product) => (
+            <button
+              key={product.id}
+              onClick={() => handleProductSelect(product.id)}
+              style={{
+                flexShrink: 0,
+                width: 64,
+                height: 64,
+                borderRadius: 12,
+                overflow: "hidden",
+                border: openProductId === product.id ? "2.5px solid #0047AB" : "2px solid #e5e7eb",
+                boxShadow: openProductId === product.id ? "0 0 0 2px #dbe7ff" : "none",
+                cursor: "pointer",
+                padding: 0,
+                background: "none",
+                transition: "border-color 0.15s",
+              }}
+            >
+              <img
+                src={product.image}
+                alt={product.name}
+                style={{ width: "100%", height: "100%", objectFit: "cover", display: "block" }}
+              />
+            </button>
+          ))
+        )}
+      </div>
+
+      {/* Info del producto + íconos */}
+      <div style={{ display: "flex", alignItems: "center", padding: "0 12px 10px", gap: 8, minHeight: 36 }}>
+        {selectedProduct ? (
+          <div style={{ flex: 1, minWidth: 0 }}>
+            <p style={{ fontSize: 10, color: "#707070", textTransform: "uppercase", letterSpacing: "0.05em", margin: 0, lineHeight: 1 }}>
+              {selectedProduct.brand}
+            </p>
+            <p style={{ fontSize: 12, fontWeight: 600, color: "#333", margin: 0, overflow: "hidden", textOverflow: "ellipsis", whiteSpace: "nowrap" }}>
+              {selectedProduct.name}
+            </p>
+          </div>
+        ) : (
+          <div style={{ flex: 1 }} />
+        )}
+        <div style={{ display: "flex", gap: 4, flexShrink: 0 }}>
+          <button
+            onClick={() => setIsSearchOpen(!isSearchOpen)}
+            style={{ padding: 6, borderRadius: 8, border: "none", background: "none", cursor: "pointer" }}
+          >
+            <Search style={{ width: 16, height: 16, color: "#0047AB" }} />
+          </button>
+          <button
+            style={{ padding: 6, borderRadius: 8, border: "none", background: "none", cursor: "pointer" }}
+          >
+            <SlidersHorizontal style={{ width: 16, height: 16, color: "#0047AB" }} />
+          </button>
+        </div>
+      </div>
+    </div>
+  );
+
+  // ── Desktop sidebar ───────────────────────────────────────────────────────
+  const DesktopSidebar = (
+    <div style={{ width: "25%", height: "100%", display: "flex", flexDirection: "column", borderRight: "1px solid rgba(0,71,171,0.1)", background: "#fff", flexShrink: 0 }}>
+      <div style={{ padding: "24px 24px 0" }}>
+        <div style={{ height: 1, background: "#e5e7eb", width: "100%" }} />
+
+        {/* Barra de herramientas */}
+        <div style={{ display: "flex", alignItems: "center", gap: 8, height: 46 }}>
+          {!isSearchOpen && (
+            <button
+              onClick={() => setIsSearchOpen(true)}
+              className="p-3 rounded-lg border border-[#0047AB] bg-[#0047AB] text-white hover:bg-[#003a94] transition-all duration-300 flex items-center justify-center shadow-sm"
+            >
+              <Search className="w-5 h-5" />
+            </button>
+          )}
+          <button className="flex-1 flex items-center justify-center gap-2 px-4 py-2.5 rounded-lg border border-[#0047AB] bg-white text-[#0047AB] hover:bg-[#eaf1ff] transition-all duration-300 shadow-sm">
+            <SlidersHorizontal className="w-4 h-4 text-[#0047AB]" />
+            <span className="font-medium text-sm">Filtros</span>
+          </button>
+          <div className="flex border border-gray-300 rounded-lg overflow-hidden shadow-sm">
+            <button
+              onClick={showList}
+              className={`p-2.5 flex items-center justify-center transition-colors ${viewMode === "list" ? "bg-[#0047AB] text-white" : "bg-white text-[#0047AB] hover:bg-[#eaf1ff] border-r border-[#dbe7ff]"}`}
+            >
+              <Menu className="w-5 h-5" />
+            </button>
+            <button
+              onClick={showGrid}
+              className={`p-2.5 flex items-center justify-center transition-colors ${viewMode === "grid" ? "bg-[#0047AB] text-white" : "bg-white text-[#0047AB] hover:bg-[#eaf1ff]"}`}
+            >
+              <LayoutGrid className="w-5 h-5" />
+            </button>
+          </div>
+        </div>
+
+        {isSearchOpen && (
+          <div className="animate-in slide-in-from-top-2 fade-in duration-300">
+            <div className="relative">
+              <Search className="absolute left-3 top-1/2 -translate-y-1/2 w-5 h-5 text-gray-400" />
+              <input
+                autoFocus
+                type="text"
+                placeholder="¿Qué estás buscando?..."
+                value={searchQuery}
+                onChange={(e) => setSearchQuery(e.target.value)}
+                className="w-full pl-11 pr-10 py-3 rounded-lg border-2 border-[#0047AB] bg-white focus:outline-none transition-all text-sm text-[#333333]"
+              />
+              <button
+                onClick={closeSearch}
+                className="absolute right-3 top-1/2 -translate-y-1/2 p-1 text-gray-400 hover:text-gray-600 bg-white rounded-full shadow-sm"
+              >
+                <X className="w-4 h-4" />
+              </button>
+            </div>
+          </div>
+        )}
+      </div>
+
+      {/* Lista de productos con acordeón por categoría */}
+      <div className="flex-1 overflow-y-auto py-2">
+        {loading ? (
+          <div className="flex items-center justify-center h-32 text-sm text-gray-400">Cargando productos...</div>
+        ) : error ? (
+          <div className="flex items-center justify-center h-32 text-sm text-red-400">{error}</div>
+        ) : searchQuery ? (
+          /* Búsqueda activa → lista plana de resultados */
+          <div className={viewMode === "grid" ? "px-4" : "px-2"}>
+            {filteredProducts.length === 0 ? (
+              <div className="flex items-center justify-center h-24 text-sm text-gray-400">Sin resultados</div>
+            ) : viewMode === "grid" ? (
+              <div className="flex flex-col gap-4">
+                {chunkArray(filteredProducts, 3).map((group, i) => (
+                  <ProductGroupCard key={i} group={group} openProductId={openProductId} onSelectProduct={handleProductSelect} />
+                ))}
+              </div>
+            ) : (
+              <div className="grid grid-cols-1 gap-3">
+                {filteredProducts.map((product) => (
+                  <IndividualProductCard key={product.id} product={product} isSelected={openProductId === product.id} onToggle={() => handleProductSelect(product.id)} />
+                ))}
+              </div>
+            )}
+          </div>
+        ) : (
+          /* Sin búsqueda → acordeón por categoría */
+          <div className="flex flex-col">
+            {categories.map((cat) => {
+              const isOpen = isCategoryOpen(cat.id);
+              return (
+                <div key={cat.id} className="border-b border-gray-100 last:border-0">
+                  <button
+                    onClick={() => toggleCategory(cat.id)}
+                    className="w-full flex items-center justify-between px-4 py-3 hover:bg-[#f4f8ff] transition-colors text-left"
+                  >
+                    <div className="flex items-center gap-2 min-w-0">
+                      <span className="font-semibold text-sm text-[#333] truncate">{cat.nombre}</span>
+                      <span className="text-xs text-[#0047AB] bg-[#eaf1ff] px-1.5 py-0.5 rounded-full flex-shrink-0">
+                        {cat.products.length}
+                      </span>
+                    </div>
+                    <ChevronDown
+                      className={`w-4 h-4 text-[#0047AB] flex-shrink-0 transition-transform duration-200 ${isOpen ? "rotate-180" : ""}`}
+                    />
+                  </button>
+
+                  {isOpen && (
+                    <div className={viewMode === "grid" ? "px-4 pb-4" : "px-2 pb-2"}>
+                      {viewMode === "grid" ? (
+                        <div className="flex flex-col gap-4">
+                          {chunkArray(cat.products, 3).map((group, i) => (
+                            <ProductGroupCard key={i} group={group} openProductId={openProductId} onSelectProduct={handleProductSelect} />
+                          ))}
+                        </div>
+                      ) : (
+                        <div className="grid grid-cols-1 gap-3">
+                          {cat.products.map((product) => (
+                            <IndividualProductCard key={product.id} product={product} isSelected={openProductId === product.id} onToggle={() => handleProductSelect(product.id)} />
+                          ))}
+                        </div>
+                      )}
+                    </div>
+                  )}
+                </div>
+              );
+            })}
+          </div>
+        )}
+      </div>
+    </div>
+  );
+
+  return (
+    <div style={{ height: "100svh", width: "100%", background: "#fff", fontFamily: "sans-serif", color: "#000", display: "flex", flexDirection: "column" }}>
+      {isMobile ? (
+        // ── Layout Mobile: imagen arriba, strip de thumbnails abajo ──────────
+        <div style={{ flex: 1, display: "flex", flexDirection: "column", minHeight: 0 }}>
+          <div style={{ flex: 1, minHeight: 0, overflow: "hidden" }}>
+            <RoomPreviewPanel {...previewPanelProps} />
+          </div>
+          {MobileProductStrip}
+        </div>
+      ) : (
+        // ── Layout Desktop: sidebar izquierda + imagen derecha ───────────────
+        <div style={{ flex: 1, display: "flex", flexDirection: "row", minHeight: 0 }}>
+          {DesktopSidebar}
+          <div style={{ flex: 1, minWidth: 0, overflow: "hidden" }}>
+            <RoomPreviewPanel {...previewPanelProps} />
+          </div>
+        </div>
+      )}
+    </div>
+  );
+}
diff --git a/frontend/src/features/roomVisualizer/roomVisualizer.types.ts b/frontend/src/features/roomVisualizer/roomVisualizer.types.ts
index 2b414ec214b0ca28d60e05dff2b15235aaed8501..d1a78b2b0ce0e3840d0fb3c9f87c75b7a3310632 100644
--- a/frontend/src/features/roomVisualizer/roomVisualizer.types.ts
+++ b/frontend/src/features/roomVisualizer/roomVisualizer.types.ts
@@ -1,5 +1,5 @@
-// Tipos específicos de la feature roomVisualizer.
-
-export type ProductSelection = {
-  openProductId: string | number | null;
-};
+// Tipos específicos de la feature roomVisualizer.
+
+export type ProductSelection = {
+  openProductId: string | number | null;
+};
diff --git a/frontend/src/features/roomVisualizer/roomVisualizerHooks.ts b/frontend/src/features/roomVisualizer/roomVisualizerHooks.ts
index 4990b710c535d7281d165db15c4d191df9a1c116..b633c9512e57d06680077708792e968899b0c41d 100644
--- a/frontend/src/features/roomVisualizer/roomVisualizerHooks.ts
+++ b/frontend/src/features/roomVisualizer/roomVisualizerHooks.ts
@@ -1,70 +1,70 @@
-import { useCallback, useMemo, useState } from "react";
-import useAppStore from "../../store/useAppStore";
-import type { Product } from "../../types";
-
-export function useRoomVisualizer(products: Product[]) {
-  const viewMode = useAppStore((store) => store.viewMode);
-  const setViewMode = useAppStore((store) => store.setViewMode);
-  const openProductId = useAppStore((store) => store.openProductId);
-  const setOpenProductId = useAppStore((store) => store.setOpenProductId);
-
-  const [isSearchOpen, setIsSearchOpen] = useState(false);
-  const [searchQuery, setSearchQuery] = useState("");
-
-  const filteredProducts = useMemo(() => {
-    const normalizedQuery = searchQuery.trim().toLowerCase();
-    return products.filter((product) => {
-      return (
-        normalizedQuery.length === 0 ||
-        product.brand.toLowerCase().includes(normalizedQuery) ||
-        product.name.toLowerCase().includes(normalizedQuery) ||
-        product.ref.toLowerCase().includes(normalizedQuery) ||
-        product.size.toLowerCase().includes(normalizedQuery)
-      );
-    });
-  }, [products, searchQuery]);
-
-  const handleSelectProduct = useCallback(
-    (id: string | number | null) => {
-      setOpenProductId(openProductId === id ? null : id);
-    },
-    [openProductId, setOpenProductId],
-  );
-
-  const closeSearch = useCallback(() => {
-    setIsSearchOpen(false);
-    setSearchQuery("");
-  }, []);
-
-  const showGrid = useCallback(() => setViewMode("grid"), [setViewMode]);
-  const showList = useCallback(() => setViewMode("list"), [setViewMode]);
-
-  const chunkArray = useCallback(<T>(arr: T[], size: number): T[][] => {
-    const chunks: T[][] = [];
-    for (let i = 0; i < arr.length; i += size) {
-      chunks.push(arr.slice(i, i + size));
-    }
-    return chunks;
-  }, []);
-
-  const selectedProduct = useMemo(
-    () => products.find((product) => product.id === openProductId) ?? null,
-    [products, openProductId],
-  );
-
-  return {
-    viewMode,
-    showGrid,
-    showList,
-    openProductId,
-    handleSelectProduct,
-    selectedProduct,
-    isSearchOpen,
-    setIsSearchOpen,
-    searchQuery,
-    setSearchQuery,
-    closeSearch,
-    filteredProducts,
-    chunkArray,
-  };
-}
+import { useCallback, useMemo, useState } from "react";
+import useAppStore from "../../store/useAppStore";
+import type { Product } from "../../types";
+
+export function useRoomVisualizer(products: Product[]) {
+  const viewMode = useAppStore((store) => store.viewMode);
+  const setViewMode = useAppStore((store) => store.setViewMode);
+  const openProductId = useAppStore((store) => store.openProductId);
+  const setOpenProductId = useAppStore((store) => store.setOpenProductId);
+
+  const [isSearchOpen, setIsSearchOpen] = useState(false);
+  const [searchQuery, setSearchQuery] = useState("");
+
+  const filteredProducts = useMemo(() => {
+    const normalizedQuery = searchQuery.trim().toLowerCase();
+    return products.filter((product) => {
+      return (
+        normalizedQuery.length === 0 ||
+        product.brand.toLowerCase().includes(normalizedQuery) ||
+        product.name.toLowerCase().includes(normalizedQuery) ||
+        product.ref.toLowerCase().includes(normalizedQuery) ||
+        product.size.toLowerCase().includes(normalizedQuery)
+      );
+    });
+  }, [products, searchQuery]);
+
+  const handleSelectProduct = useCallback(
+    (id: string | number | null) => {
+      setOpenProductId(openProductId === id ? null : id);
+    },
+    [openProductId, setOpenProductId],
+  );
+
+  const closeSearch = useCallback(() => {
+    setIsSearchOpen(false);
+    setSearchQuery("");
+  }, []);
+
+  const showGrid = useCallback(() => setViewMode("grid"), [setViewMode]);
+  const showList = useCallback(() => setViewMode("list"), [setViewMode]);
+
+  const chunkArray = useCallback(<T>(arr: T[], size: number): T[][] => {
+    const chunks: T[][] = [];
+    for (let i = 0; i < arr.length; i += size) {
+      chunks.push(arr.slice(i, i + size));
+    }
+    return chunks;
+  }, []);
+
+  const selectedProduct = useMemo(
+    () => products.find((product) => product.id === openProductId) ?? null,
+    [products, openProductId],
+  );
+
+  return {
+    viewMode,
+    showGrid,
+    showList,
+    openProductId,
+    handleSelectProduct,
+    selectedProduct,
+    isSearchOpen,
+    setIsSearchOpen,
+    searchQuery,
+    setSearchQuery,
+    closeSearch,
+    filteredProducts,
+    chunkArray,
+  };
+}
diff --git a/frontend/src/features/roomVisualizer/useCatalogProducts.ts b/frontend/src/features/roomVisualizer/useCatalogProducts.ts
index 6a539ca74e1f5a448d15d8539078bd58184df50c..37dd7008e8bb9da7653168f2606e1d1e27bdfb60 100644
--- a/frontend/src/features/roomVisualizer/useCatalogProducts.ts
+++ b/frontend/src/features/roomVisualizer/useCatalogProducts.ts
@@ -1,97 +1,97 @@
-import { useEffect, useState } from "react";
-import type { Product } from "../../types";
-
-const API_BASE = import.meta.env.VITE_API_URL ?? "";
-
-interface CatalogProduct {
-  id: string;
-  nombre: string;
-  textura: string;
-  url_preview: string;
-  dimensiones: string[];
-}
-
-interface CatalogCategory {
-  id: string;
-  nombre: string;
-  tipo?: string;
-  descripcion: string;
-  especificaciones?: string[];
-  url_detalle?: string;
-  productos: CatalogProduct[];
-}
-
-interface CatalogResponse {
-  categories: CatalogCategory[];
-}
-
-function mapToProduct(item: CatalogProduct, category: CatalogCategory): Product {
-  return {
-    id: item.id,
-    brand: category.nombre,
-    name: item.nombre,
-    ref: item.textura,
-    size: item.dimensiones.length > 0 ? item.dimensiones.join(" / ") : "—",
-    image: `${API_BASE}${item.url_preview}`,
-    description: category.especificaciones,
-    detailUrl: category.url_detalle,
-    tipo: (category.tipo as "suelos" | "paredes") ?? undefined,
-    categoria: category.id,
-  };
-}
-
-export interface ProductCategory {
-  id: string;
-  nombre: string;
-  tipo?: string;
-  descripcion: string;
-  especificaciones?: string[];
-  products: Product[];
-}
-
-export function useCatalogProducts() {
-  const [products, setProducts] = useState<Product[]>([]);
-  const [categories, setCategories] = useState<ProductCategory[]>([]);
-  const [loading, setLoading] = useState(true);
-  const [error, setError] = useState<string | null>(null);
-
-  useEffect(() => {
-    let cancelled = false;
-
-    async function fetchCatalog() {
-      try {
-        const res = await fetch(`${API_BASE}/api/catalog/textures`);
-        if (!res.ok) throw new Error(`Error ${res.status}`);
-        const data: CatalogResponse = await res.json();
-
-        const cats: ProductCategory[] = data.categories.map((category) => ({
-          id: category.id,
-          nombre: category.nombre,
-          tipo: category.tipo,
-          descripcion: category.descripcion,
-          especificaciones: category.especificaciones,
-          products: category.productos.map((item) => mapToProduct(item, category)),
-        }));
-
-        const flat = cats.flatMap((c) => c.products);
-
-        if (!cancelled) {
-          setCategories(cats);
-          setProducts(flat);
-          setError(null);
-        }
-      } catch (err) {
-        if (!cancelled) {
-          setError(err instanceof Error ? err.message : "Error al cargar productos");
-        }
-      } finally {
-        if (!cancelled) setLoading(false);
-      }
-    }
-
-    fetchCatalog();
-    return () => { cancelled = true; };
-  }, []);
-
-  return { products, categories, loading, error };
-}
+import { useEffect, useState } from "react";
+import type { Product } from "../../types";
+
+const API_BASE = import.meta.env.VITE_API_URL ?? "";
+
+interface CatalogProduct {
+  id: string;
+  nombre: string;
+  textura: string;
+  url_preview: string;
+  dimensiones: string[];
+}
+
+interface CatalogCategory {
+  id: string;
+  nombre: string;
+  tipo?: string;
+  descripcion: string;
+  especificaciones?: string[];
+  url_detalle?: string;
+  productos: CatalogProduct[];
+}
+
+interface CatalogResponse {
+  categories: CatalogCategory[];
+}
+
+function mapToProduct(item: CatalogProduct, category: CatalogCategory): Product {
+  return {
+    id: item.id,
+    brand: category.nombre,
+    name: item.nombre,
+    ref: item.textura,
+    size: item.dimensiones.length > 0 ? item.dimensiones.join(" / ") : "—",
+    image: `${API_BASE}${item.url_preview}`,
+    description: category.especificaciones,
+    detailUrl: category.url_detalle,
+    tipo: (category.tipo as "suelos" | "paredes") ?? undefined,
+    categoria: category.id,
+  };
+}
+
+export interface ProductCategory {
+  id: string;
+  nombre: string;
+  tipo?: string;
+  descripcion: string;
+  especificaciones?: string[];
+  products: Product[];
+}
+
+export function useCatalogProducts() {
+  const [products, setProducts] = useState<Product[]>([]);
+  const [categories, setCategories] = useState<ProductCategory[]>([]);
+  const [loading, setLoading] = useState(true);
+  const [error, setError] = useState<string | null>(null);
+
+  useEffect(() => {
+    let cancelled = false;
+
+    async function fetchCatalog() {
+      try {
+        const res = await fetch(`${API_BASE}/api/catalog/textures`);
+        if (!res.ok) throw new Error(`Error ${res.status}`);
+        const data: CatalogResponse = await res.json();
+
+        const cats: ProductCategory[] = data.categories.map((category) => ({
+          id: category.id,
+          nombre: category.nombre,
+          tipo: category.tipo,
+          descripcion: category.descripcion,
+          especificaciones: category.especificaciones,
+          products: category.productos.map((item) => mapToProduct(item, category)),
+        }));
+
+        const flat = cats.flatMap((c) => c.products);
+
+        if (!cancelled) {
+          setCategories(cats);
+          setProducts(flat);
+          setError(null);
+        }
+      } catch (err) {
+        if (!cancelled) {
+          setError(err instanceof Error ? err.message : "Error al cargar productos");
+        }
+      } finally {
+        if (!cancelled) setLoading(false);
+      }
+    }
+
+    fetchCatalog();
+    return () => { cancelled = true; };
+  }, []);
+
+  return { products, categories, loading, error };
+}
diff --git a/frontend/src/features/roomVisualizer/useRoomVisualizer.ts b/frontend/src/features/roomVisualizer/useRoomVisualizer.ts
index 41759507c45418dc6d9236d87c53470c0f112a82..ba2fb386191cfe80789dc9bb51f0e00f513917ab 100644
--- a/frontend/src/features/roomVisualizer/useRoomVisualizer.ts
+++ b/frontend/src/features/roomVisualizer/useRoomVisualizer.ts
@@ -1,36 +1,36 @@
-import { useState, useRef, useCallback } from "react";
-
-export function useRoomVisualizer() {
-  const [hoveredMask, setHoveredMask] = useState<string | null>(null);
-  const [selectedMasks, setSelectedMasks] = useState<Set<string>>(new Set());
-  const containerRef = useRef<HTMLDivElement>(null);
-
-  const handleMaskMouseEnter = useCallback((maskUrl: string) => {
-    setHoveredMask(maskUrl);
-  }, []);
-
-  const handleMaskMouseLeave = useCallback(() => {
-    setHoveredMask(null);
-  }, []);
-
-  const handleMaskClick = useCallback((maskUrl: string) => {
-    setSelectedMasks((prev) => {
-      const newSelected = new Set(prev);
-      if (newSelected.has(maskUrl)) {
-        newSelected.delete(maskUrl);
-      } else {
-        newSelected.add(maskUrl);
-      }
-      return newSelected;
-    });
-  }, []);
-
-  return {
-    containerRef,
-    hoveredMask,
-    selectedMasks,
-    handleMaskClick,
-    handleMaskMouseEnter,
-    handleMaskMouseLeave,
-  };
-}
+import { useState, useRef, useCallback } from "react";
+
+export function useRoomVisualizer() {
+  const [hoveredMask, setHoveredMask] = useState<string | null>(null);
+  const [selectedMasks, setSelectedMasks] = useState<Set<string>>(new Set());
+  const containerRef = useRef<HTMLDivElement>(null);
+
+  const handleMaskMouseEnter = useCallback((maskUrl: string) => {
+    setHoveredMask(maskUrl);
+  }, []);
+
+  const handleMaskMouseLeave = useCallback(() => {
+    setHoveredMask(null);
+  }, []);
+
+  const handleMaskClick = useCallback((maskUrl: string) => {
+    setSelectedMasks((prev) => {
+      const newSelected = new Set(prev);
+      if (newSelected.has(maskUrl)) {
+        newSelected.delete(maskUrl);
+      } else {
+        newSelected.add(maskUrl);
+      }
+      return newSelected;
+    });
+  }, []);
+
+  return {
+    containerRef,
+    hoveredMask,
+    selectedMasks,
+    handleMaskClick,
+    handleMaskMouseEnter,
+    handleMaskMouseLeave,
+  };
+}
diff --git a/frontend/src/features/routes/RouteList.tsx b/frontend/src/features/routes/RouteList.tsx
index a397c232bbb73bb8f76d04d7038da343c90d0c4b..c2a4d8e5cbd0cf7be51541318c50507c9374cff5 100644
--- a/frontend/src/features/routes/RouteList.tsx
+++ b/frontend/src/features/routes/RouteList.tsx
@@ -1,20 +1,20 @@
-import type { RouteItem } from "../../types";
-
-interface RouteListProps {
-  routes: RouteItem[];
-}
-
-export default function RouteList({ routes }: RouteListProps) {
-  return (
-    <section className="route-index">
-      <h2>Rutas disponibles</h2>
-      <ul>
-        {routes.map((route) => (
-          <li key={route.path}>
-            <strong>{route.label}:</strong> <code>{route.path}</code>
-          </li>
-        ))}
-      </ul>
-    </section>
-  );
-}
+import type { RouteItem } from "../../types";
+
+interface RouteListProps {
+  routes: RouteItem[];
+}
+
+export default function RouteList({ routes }: RouteListProps) {
+  return (
+    <section className="route-index">
+      <h2>Rutas disponibles</h2>
+      <ul>
+        {routes.map((route) => (
+          <li key={route.path}>
+            <strong>{route.label}:</strong> <code>{route.path}</code>
+          </li>
+        ))}
+      </ul>
+    </section>
+  );
+}
diff --git a/frontend/src/features/routes/RoutesPage.tsx b/frontend/src/features/routes/RoutesPage.tsx
index f5e562af5b7367bf23533e6a27c2a9d789c1a859..7f78a357fea20a68e153caee662a3b123c965705 100644
--- a/frontend/src/features/routes/RoutesPage.tsx
+++ b/frontend/src/features/routes/RoutesPage.tsx
@@ -1,29 +1,29 @@
-import { Link } from "react-router-dom";
-import RouteList from "./RouteList";
-import type { RouteItem } from "../../types";
-
-const AVAILABLE_ROUTES: RouteItem[] = [
-  { label: "Room Setup", path: "/" },
-  { label: "Viewer", path: "/viewer" },
-  { label: "Rutas", path: "/routes" },
-  { label: "Configuración", path: "/settings" },
-  { label: "Home", path: "/" },
-  { label: "Panel admin", path: "/admin" },
-  { label: "Vista previa iframe", path: "/preview" },
-  { label: "Generar token", path: "/api/token" },
-  { label: "Obtener clientes", path: "/api/keys" },
-  { label: "Generar API key", path: "/api/generate-key" },
-  { label: "Sesiones activas", path: "/api/active-sessions" },
-  { label: "Obtener config", path: "/config?token..." },
-];
-
-export default function RoutesPage() {
-  return (
-    <>
-      <RouteList routes={AVAILABLE_ROUTES} />
-      <p>
-        Volver a <Link to="/">la pantalla principal</Link>.
-      </p>
-    </>
-  );
-}
+import { Link } from "react-router-dom";
+import RouteList from "./RouteList";
+import type { RouteItem } from "../../types";
+
+const AVAILABLE_ROUTES: RouteItem[] = [
+  { label: "Room Setup", path: "/" },
+  { label: "Viewer", path: "/viewer" },
+  { label: "Rutas", path: "/routes" },
+  { label: "Configuración", path: "/settings" },
+  { label: "Home", path: "/" },
+  { label: "Panel admin", path: "/admin" },
+  { label: "Vista previa iframe", path: "/preview" },
+  { label: "Generar token", path: "/api/token" },
+  { label: "Obtener clientes", path: "/api/keys" },
+  { label: "Generar API key", path: "/api/generate-key" },
+  { label: "Sesiones activas", path: "/api/active-sessions" },
+  { label: "Obtener config", path: "/config?token..." },
+];
+
+export default function RoutesPage() {
+  return (
+    <>
+      <RouteList routes={AVAILABLE_ROUTES} />
+      <p>
+        Volver a <Link to="/">la pantalla principal</Link>.
+      </p>
+    </>
+  );
+}
diff --git a/frontend/src/features/settings/SettingsPage.tsx b/frontend/src/features/settings/SettingsPage.tsx
index 367f44403b206e5e94a6caa3f39cd90529b23b7d..db81d0330f616dddb324737a9245f3915b5fefa0 100644
--- a/frontend/src/features/settings/SettingsPage.tsx
+++ b/frontend/src/features/settings/SettingsPage.tsx
@@ -1,83 +1,83 @@
-import { useEffect, useState } from "react";
-import type { FormEvent } from "react";
-import {
-  loadSettings,
-  saveSettings,
-  DEFAULT_SETTINGS,
-  type AppSettings,
-} from "../../utils/settings";
-
-export default function SettingsPage() {
-  const [settings, setSettings] = useState<AppSettings>(DEFAULT_SETTINGS);
-  const [status, setStatus] = useState<string>("");
-
-  useEffect(() => {
-    setSettings(loadSettings());
-  }, []);
-
-  const handleChange = (field: keyof AppSettings, value: string | boolean) => {
-    setSettings((current) => ({
-      ...current,
-      [field]: value,
-    }));
-  };
-
-  const handleSubmit = (event: FormEvent<HTMLFormElement>) => {
-    event.preventDefault();
-    saveSettings(settings);
-    setStatus("Configuración guardada correctamente.");
-    window.setTimeout(() => setStatus(""), 3000);
-  };
-
-  return (
-    <section className="panel">
-      <h2>Configuración</h2>
-      <p>Controla ajustes de la aplicación que se guardan en tu navegador.</p>
-
-      <form onSubmit={handleSubmit} className="form-row">
-        <label htmlFor="customApiBase">Base URL de la API</label>
-        <input
-          id="customApiBase"
-          type="text"
-          value={settings.customApiBase}
-          onChange={(event) =>
-            handleChange("customApiBase", event.target.value)
-          }
-          placeholder="http://localhost:8000"
-        />
-      </form>
-
-      <div className="form-row">
-        <label>
-          <input
-            type="checkbox"
-            checked={settings.showRouteList}
-            onChange={(event) =>
-              handleChange("showRouteList", event.target.checked)
-            }
-          />
-          Mostrar la lista de rutas en el Viewer
-        </label>
-      </div>
-
-      <div className="form-row">
-        <label>
-          <input
-            type="checkbox"
-            checked={settings.autoDevToken}
-            onChange={(event) =>
-              handleChange("autoDevToken", event.target.checked)
-            }
-          />
-          Generar token de prueba automáticamente en desarrollo
-        </label>
-      </div>
-
-      <button className="button" type="submit">
-        Guardar configuración
-      </button>
-
-      {status && <div className="status">{status}</div>}
-    </section>
-  );
-}
+import { useEffect, useState } from "react";
+import type { FormEvent } from "react";
+import {
+  loadSettings,
+  saveSettings,
+  DEFAULT_SETTINGS,
+  type AppSettings,
+} from "../../utils/settings";
+
+export default function SettingsPage() {
+  const [settings, setSettings] = useState<AppSettings>(DEFAULT_SETTINGS);
+  const [status, setStatus] = useState<string>("");
+
+  useEffect(() => {
+    setSettings(loadSettings());
+  }, []);
+
+  const handleChange = (field: keyof AppSettings, value: string | boolean) => {
+    setSettings((current) => ({
+      ...current,
+      [field]: value,
+    }));
+  };
+
+  const handleSubmit = (event: FormEvent<HTMLFormElement>) => {
+    event.preventDefault();
+    saveSettings(settings);
+    setStatus("Configuración guardada correctamente.");
+    window.setTimeout(() => setStatus(""), 3000);
+  };
+
+  return (
+    <section className="panel">
+      <h2>Configuración</h2>
+      <p>Controla ajustes de la aplicación que se guardan en tu navegador.</p>
+
+      <form onSubmit={handleSubmit} className="form-row">
+        <label htmlFor="customApiBase">Base URL de la API</label>
+        <input
+          id="customApiBase"
+          type="text"
+          value={settings.customApiBase}
+          onChange={(event) =>
+            handleChange("customApiBase", event.target.value)
+          }
+          placeholder="http://localhost:8000"
+        />
+      </form>
+
+      <div className="form-row">
+        <label>
+          <input
+            type="checkbox"
+            checked={settings.showRouteList}
+            onChange={(event) =>
+              handleChange("showRouteList", event.target.checked)
+            }
+          />
+          Mostrar la lista de rutas en el Viewer
+        </label>
+      </div>
+
+      <div className="form-row">
+        <label>
+          <input
+            type="checkbox"
+            checked={settings.autoDevToken}
+            onChange={(event) =>
+              handleChange("autoDevToken", event.target.checked)
+            }
+          />
+          Generar token de prueba automáticamente en desarrollo
+        </label>
+      </div>
+
+      <button className="button" type="submit">
+        Guardar configuración
+      </button>
+
+      {status && <div className="status">{status}</div>}
+    </section>
+  );
+}
diff --git a/frontend/src/features/viewer/BridgePanel.tsx b/frontend/src/features/viewer/BridgePanel.tsx
index 4c02f8f559926f8ff7836364bce5cae8ba39f091..c45201524775d8b27056f196f8b18b969ddf1c4e 100644
--- a/frontend/src/features/viewer/BridgePanel.tsx
+++ b/frontend/src/features/viewer/BridgePanel.tsx
@@ -1,18 +1,18 @@
-interface BridgePanelProps {
-  messages: string[];
-}
-
-export default function BridgePanel({ messages }: BridgePanelProps) {
-  if (messages.length === 0) return null;
-
-  return (
-    <div className="bridge-panel">
-      <h3>Mensajes del padre</h3>
-      <ul>
-        {messages.map((message, index) => (
-          <li key={index}>{message}</li>
-        ))}
-      </ul>
-    </div>
-  );
-}
+interface BridgePanelProps {
+  messages: string[];
+}
+
+export default function BridgePanel({ messages }: BridgePanelProps) {
+  if (messages.length === 0) return null;
+
+  return (
+    <div className="bridge-panel">
+      <h3>Mensajes del padre</h3>
+      <ul>
+        {messages.map((message, index) => (
+          <li key={index}>{message}</li>
+        ))}
+      </ul>
+    </div>
+  );
+}
diff --git a/frontend/src/features/viewer/ClientPanel.tsx b/frontend/src/features/viewer/ClientPanel.tsx
index 4dab822e3cdfec27d6b77aa223e7e262856899a6..5f3584e9694ab18b728e09f266df593bf3b1f033 100644
--- a/frontend/src/features/viewer/ClientPanel.tsx
+++ b/frontend/src/features/viewer/ClientPanel.tsx
@@ -1,18 +1,18 @@
-import type { ClientData } from "../../types";
-
-interface ClientPanelProps {
-  cliente: ClientData;
-  onNotify: () => void;
-}
-
-export default function ClientPanel({ cliente, onNotify }: ClientPanelProps) {
-  return (
-    <section className="viewer-panel">
-      <h2>Panel de Control</h2>
-      <p className="client-detail">ID del cliente: {cliente.client_id}</p>
-      <button className="button" onClick={onNotify}>
-        Notificar al sitio padre
-      </button>
-    </section>
-  );
-}
+import type { ClientData } from "../../types";
+
+interface ClientPanelProps {
+  cliente: ClientData;
+  onNotify: () => void;
+}
+
+export default function ClientPanel({ cliente, onNotify }: ClientPanelProps) {
+  return (
+    <section className="viewer-panel">
+      <h2>Panel de Control</h2>
+      <p className="client-detail">ID del cliente: {cliente.client_id}</p>
+      <button className="button" onClick={onNotify}>
+        Notificar al sitio padre
+      </button>
+    </section>
+  );
+}
diff --git a/frontend/src/features/viewer/Viewer.tsx b/frontend/src/features/viewer/Viewer.tsx
index fa8bde8299c70a1d981cc9a9ce735fd148796a13..5c28dee7a4d8ea9a4e0b513202b7292caab8ef82 100644
--- a/frontend/src/features/viewer/Viewer.tsx
+++ b/frontend/src/features/viewer/Viewer.tsx
@@ -1,181 +1,181 @@
-import { useEffect, useState } from "react";
-import { Link } from "react-router-dom";
-import { startSession } from "../../api/client";
-import { useClientConfig } from "../../hooks/useClientConfig";
-import {
-  DEFAULT_SETTINGS,
-  loadSettings,
-  type AppSettings,
-} from "../../utils/settings";
-import type { ClientData, RouteItem } from "../../types";
-import ClientPanel from "./ClientPanel";
-import BridgePanel from "./BridgePanel";
-import RouteList from "../routes/RouteList";
-
-const AVAILABLE_ROUTES: RouteItem[] = [
-  { label: "Home", path: "/" },
-  { label: "Panel admin", path: "/admin" },
-  { label: "Vista previa iframe", path: "/preview" },
-  { label: "Generar token", path: "/api/token" },
-  { label: "Obtener clientes", path: "/api/keys" },
-  { label: "Generar API key", path: "/api/generate-key" },
-  { label: "Sesiones activas", path: "/api/active-sessions" },
-  { label: "Obtener config", path: "/config?token=..." },
-];
-
-export default function Viewer() {
-  const [overrideCliente, setOverrideCliente] = useState<ClientData | null>(
-    null,
-  );
-  const [bridgeMessages, setBridgeMessages] = useState<string[]>([]);
-  const [settings, setSettings] = useState<AppSettings>(DEFAULT_SETTINGS);
-
-  const params = new URLSearchParams(window.location.search);
-  const token = params.get("token") ?? "";
-  const clientKey = params.get("key") ?? "";
-  const isDev = import.meta.env.DEV;
-
-  useEffect(() => {
-    setSettings(loadSettings());
-  }, []);
-
-  const { data, error, isLoading } = useClientConfig(
-    token,
-    clientKey,
-    settings,
-  );
-
-  const queryCliente = data?.cliente ?? null;
-  const cliente = overrideCliente ?? queryCliente;
-  const showRouteList = settings.showRouteList && !token && !isDev;
-
-  useEffect(() => {
-    if (!data) return;
-
-    window.parent.postMessage(
-      { type: "app-loaded", clientId: data.cliente.client_id },
-      "*",
-    );
-    startSession(data.query, settings.customApiBase).catch(() => {
-      // Silenciar errores de sesión de inicio para no interrumpir la vista.
-    });
-  }, [data, settings.customApiBase]);
-
-  const displayError =
-    !isDev && !token && !clientKey
-      ? "No se encontró el token o key en la URL."
-      : error instanceof Error
-        ? error.message
-        : typeof error === "string"
-          ? error
-          : null;
-
-  useEffect(() => {
-    const handleParentMessage = (event: MessageEvent) => {
-      if (!event.data || typeof event.data !== "object") return;
-      const data = event.data as {
-        type?: string;
-        command?: string;
-        payload?: { value?: string };
-      };
-      if (data.type !== "preview-command" || !data.command) return;
-
-      setBridgeMessages((current) => [
-        `Recibido comando: ${data.command}${data.payload?.value ? ` (${data.payload.value})` : ""}`,
-        ...current.slice(0, 9),
-      ]);
-
-      if (data.command === "ping") {
-        window.parent.postMessage(
-          { type: "preview-response", status: "pong" },
-          "*",
-        );
-      }
-
-      if (data.command === "status") {
-        window.parent.postMessage(
-          {
-            type: "preview-response",
-            status: "ready",
-            client: cliente?.client_id ?? "desconocido",
-          },
-          "*",
-        );
-      }
-
-      if (data.command === "set-color" && data.payload?.value) {
-        document.body.style.backgroundColor = data.payload.value;
-        window.parent.postMessage(
-          {
-            type: "preview-response",
-            status: "color-cambiado",
-            color: data.payload.value,
-          },
-          "*",
-        );
-      }
-
-      if (data.command === "set-name" && data.payload?.value) {
-        const newName = data.payload.value;
-        setOverrideCliente((current) => {
-          const base = current ?? queryCliente;
-          return base ? { ...base, nombre: newName } : current;
-        });
-        window.parent.postMessage(
-          {
-            type: "preview-response",
-            status: "nombre-cambiado",
-            nombre: newName,
-          },
-          "*",
-        );
-      }
-    };
-
-    window.addEventListener("message", handleParentMessage);
-    return () => window.removeEventListener("message", handleParentMessage);
-  }, [cliente, queryCliente]);
-
-  const enviarMensaje = () => {
-    if (!cliente) return;
-    window.parent.postMessage(
-      {
-        type: "saas-session-active",
-        nombreCliente: cliente.nombre,
-      },
-      "*",
-    );
-  };
-
-  return (
-    <>
-      {isLoading ? (
-        <div className="empty-state">Cargando cliente...</div>
-      ) : displayError ? (
-        <div className="error-box">{displayError}</div>
-      ) : cliente ? (
-        <>
-          <ClientPanel cliente={cliente} onNotify={enviarMensaje} />
-          <BridgePanel messages={bridgeMessages} />
-        </>
-      ) : (
-        <section className="viewer-panel">
-          <h2>Ruta de cliente</h2>
-          <div className="empty-state">
-            No se encontró información del cliente.
-          </div>
-        </section>
-      )}
-
-      {showRouteList && (
-        <>
-          <RouteList routes={AVAILABLE_ROUTES} />
-          <p>
-            También puedes ver esta lista desde{" "}
-            <Link to="/routes">la página de rutas</Link>.
-          </p>
-        </>
-      )}
-    </>
-  );
-}
+import { useEffect, useState } from "react";
+import { Link } from "react-router-dom";
+import { startSession } from "../../api/client";
+import { useClientConfig } from "../../hooks/useClientConfig";
+import {
+  DEFAULT_SETTINGS,
+  loadSettings,
+  type AppSettings,
+} from "../../utils/settings";
+import type { ClientData, RouteItem } from "../../types";
+import ClientPanel from "./ClientPanel";
+import BridgePanel from "./BridgePanel";
+import RouteList from "../routes/RouteList";
+
+const AVAILABLE_ROUTES: RouteItem[] = [
+  { label: "Home", path: "/" },
+  { label: "Panel admin", path: "/admin" },
+  { label: "Vista previa iframe", path: "/preview" },
+  { label: "Generar token", path: "/api/token" },
+  { label: "Obtener clientes", path: "/api/keys" },
+  { label: "Generar API key", path: "/api/generate-key" },
+  { label: "Sesiones activas", path: "/api/active-sessions" },
+  { label: "Obtener config", path: "/config?token=..." },
+];
+
+export default function Viewer() {
+  const [overrideCliente, setOverrideCliente] = useState<ClientData | null>(
+    null,
+  );
+  const [bridgeMessages, setBridgeMessages] = useState<string[]>([]);
+  const [settings, setSettings] = useState<AppSettings>(DEFAULT_SETTINGS);
+
+  const params = new URLSearchParams(window.location.search);
+  const token = params.get("token") ?? "";
+  const clientKey = params.get("key") ?? "";
+  const isDev = import.meta.env.DEV;
+
+  useEffect(() => {
+    setSettings(loadSettings());
+  }, []);
+
+  const { data, error, isLoading } = useClientConfig(
+    token,
+    clientKey,
+    settings,
+  );
+
+  const queryCliente = data?.cliente ?? null;
+  const cliente = overrideCliente ?? queryCliente;
+  const showRouteList = settings.showRouteList && !token && !isDev;
+
+  useEffect(() => {
+    if (!data) return;
+
+    window.parent.postMessage(
+      { type: "app-loaded", clientId: data.cliente.client_id },
+      "*",
+    );
+    startSession(data.query, settings.customApiBase).catch(() => {
+      // Silenciar errores de sesión de inicio para no interrumpir la vista.
+    });
+  }, [data, settings.customApiBase]);
+
+  const displayError =
+    !isDev && !token && !clientKey
+      ? "No se encontró el token o key en la URL."
+      : error instanceof Error
+        ? error.message
+        : typeof error === "string"
+          ? error
+          : null;
+
+  useEffect(() => {
+    const handleParentMessage = (event: MessageEvent) => {
+      if (!event.data || typeof event.data !== "object") return;
+      const data = event.data as {
+        type?: string;
+        command?: string;
+        payload?: { value?: string };
+      };
+      if (data.type !== "preview-command" || !data.command) return;
+
+      setBridgeMessages((current) => [
+        `Recibido comando: ${data.command}${data.payload?.value ? ` (${data.payload.value})` : ""}`,
+        ...current.slice(0, 9),
+      ]);
+
+      if (data.command === "ping") {
+        window.parent.postMessage(
+          { type: "preview-response", status: "pong" },
+          "*",
+        );
+      }
+
+      if (data.command === "status") {
+        window.parent.postMessage(
+          {
+            type: "preview-response",
+            status: "ready",
+            client: cliente?.client_id ?? "desconocido",
+          },
+          "*",
+        );
+      }
+
+      if (data.command === "set-color" && data.payload?.value) {
+        document.body.style.backgroundColor = data.payload.value;
+        window.parent.postMessage(
+          {
+            type: "preview-response",
+            status: "color-cambiado",
+            color: data.payload.value,
+          },
+          "*",
+        );
+      }
+
+      if (data.command === "set-name" && data.payload?.value) {
+        const newName = data.payload.value;
+        setOverrideCliente((current) => {
+          const base = current ?? queryCliente;
+          return base ? { ...base, nombre: newName } : current;
+        });
+        window.parent.postMessage(
+          {
+            type: "preview-response",
+            status: "nombre-cambiado",
+            nombre: newName,
+          },
+          "*",
+        );
+      }
+    };
+
+    window.addEventListener("message", handleParentMessage);
+    return () => window.removeEventListener("message", handleParentMessage);
+  }, [cliente, queryCliente]);
+
+  const enviarMensaje = () => {
+    if (!cliente) return;
+    window.parent.postMessage(
+      {
+        type: "saas-session-active",
+        nombreCliente: cliente.nombre,
+      },
+      "*",
+    );
+  };
+
+  return (
+    <>
+      {isLoading ? (
+        <div className="empty-state">Cargando cliente...</div>
+      ) : displayError ? (
+        <div className="error-box">{displayError}</div>
+      ) : cliente ? (
+        <>
+          <ClientPanel cliente={cliente} onNotify={enviarMensaje} />
+          <BridgePanel messages={bridgeMessages} />
+        </>
+      ) : (
+        <section className="viewer-panel">
+          <h2>Ruta de cliente</h2>
+          <div className="empty-state">
+            No se encontró información del cliente.
+          </div>
+        </section>
+      )}
+
+      {showRouteList && (
+        <>
+          <RouteList routes={AVAILABLE_ROUTES} />
+          <p>
+            También puedes ver esta lista desde{" "}
+            <Link to="/routes">la página de rutas</Link>.
+          </p>
+        </>
+      )}
+    </>
+  );
+}
diff --git a/frontend/src/hooks/useApplyTexture.ts b/frontend/src/hooks/useApplyTexture.ts
index d74c3f0d7db437ebcf67990923c54e7868026a5a..c2b5f3813bffe2655a3db0844c7dd21abe044749 100644
--- a/frontend/src/hooks/useApplyTexture.ts
+++ b/frontend/src/hooks/useApplyTexture.ts
@@ -1,197 +1,57 @@
-import { useCallback, useState } from "react";
-import { API_BASE } from "../api/client";
-import { useHistoryStore } from "../store/useAppStore";
-
-interface ApplyTextureResult {
-  output_url: string;
-  output_filename: string;
-}
-
-export function useApplyTexture() {
-  const [isApplying, setIsApplying] = useState(false);
-  const [resultUrl, setResultUrl] = useState<string | null>(null);
-  const [error, setError] = useState<string | null>(null);
-
-  const applyTexture = useCallback(
-    async (
-      filename: string,
-      maskIndices: number[],
-      textureName: string,
-      originalFilename?: string,
-    ) => {
-      setIsApplying(true);
-      setError(null);
-      try {
-        const res = await fetch(`${API_BASE}/seg/apply_texture`, {
-          method: "POST",
-          headers: { "Content-Type": "application/json" },
-          body: JSON.stringify({
-            filename,
-            mask_indices: maskIndices,
-            texture_name: textureName,
-            original_filename: originalFilename ?? filename,
-            direction_mode: "auto",
-            angle_degrees: 0,
-          }),
-        });
-
-        if (!res.ok) {
-          const text = await res.text();
-          throw new Error(text || `Error ${res.status}`);
-        }
-
-        const data: ApplyTextureResult = await res.json();
-        setResultUrl(`${API_BASE}${data.output_url}`);
-        return data;
-      } catch (err) {
-        const message =
-          err instanceof Error ? err.message : "Error al aplicar textura";
-        setError(message);
-        throw new Error(message);
-      } finally {
-        setIsApplying(false);
-      }
-    },
-    [],
-  );
-
-  const applyTextureAI = useCallback(
-    async (
-      filename: string,
-      textureName: string,
-      originalFilename?: string,
-    ) => {
-      setIsApplying(true);
-      setError(null);
-      try {
-        const res = await fetch(`${API_BASE}/seg/apply_texture_ai`, {
-          method: "POST",
-          headers: { "Content-Type": "application/json" },
-          body: JSON.stringify({
-            filename,
-            texture_name: textureName,
-            original_filename: originalFilename ?? filename,
-            prompt: "", // El backend generará uno por defecto basado en texture_name
-          }),
-        });
-
-        if (!res.ok) {
-          const text = await res.text();
-          throw new Error(text || `Error ${res.status}`);
-        }
-
-        const data = await res.json();
-
-        // Si es asíncrono, necesitamos esperar/poll.
-        // Pero por ahora asumiremos que devuelve el resultado o un job_id.
-        if (data.job_id) {
-          // Poll the job status until it's done or failed, then return result
-          const jobId = data.job_id as string;
-          const poll = async () => {
-            const start = Date.now();
-            const timeoutMs = 3 * 60 * 1000; // 3 minutes max
-            while (Date.now() - start < timeoutMs) {
-              const res = await fetch(`${API_BASE}/seg/jobs/${jobId}`);
-              if (!res.ok) throw new Error(`Job status error ${res.status}`);
-              const job = await res.json();
-              if (job.status === "done") return job.result;
-              if (job.status === "failed")
-                throw new Error(job.message || "AI job failed");
-              await new Promise((r) => setTimeout(r, 2000));
-            }
-            throw new Error("Timed out waiting for AI job");
-          };
-
-          const result = await poll();
-          if (result?.url) {
-            setResultUrl(`${API_BASE}${result.url}`);
-          }
-          return result;
-        }
-
-        setResultUrl(`${API_BASE}${data.url}`);
-        return data;
-      } catch (err) {
-        const message =
-          err instanceof Error
-            ? err.message
-            : "Error al aplicar textura con IA";
-        setError(message);
-        throw new Error(message);
-      } finally {
-        setIsApplying(false);
-      }
-    },
-    [],
-  );
-
-  const applyTextureOpenAI = useCallback(
-    async (
-      fileOrFilename: File | string,
-      textureName: string,
-      apiKey?: string | null,
-    ) => {
-      if (isApplying) throw new Error("Ya hay una operación en curso");
-      setIsApplying(true);
-      setError(null);
-      try {
-        const form = new FormData();
-        // Accept either a File object (client-side upload) or a server filename (string)
-        if (typeof fileOrFilename === "string") {
-          // server-side filename returned by uploadRoomImage, e.g. "/uploads/abcd.png" or full URL
-          const name = fileOrFilename.includes("/uploads/")
-            ? fileOrFilename.split("/uploads/").pop() || fileOrFilename
-            : fileOrFilename;
-          form.append("source_filename", name);
-        } else {
-          form.append("file", fileOrFilename);
-        }
-        form.append("texture", textureName);
-        const userId =
-          useHistoryStore.getState?.()?.userId ??
-          useHistoryStore((s) => s.userId);
-        if (userId) form.append("user_id", userId);
-        if (apiKey) form.append("api_key", apiKey);
-
-        const res = await fetch(`${API_BASE}/api/generate-image`, {
-          method: "POST",
-          body: form,
-        });
-
-        if (!res.ok) {
-          const text = await res.text();
-          throw new Error(text || `Error ${res.status}`);
-        }
-
-        const data = await res.json();
-        if (!data.result_b64) throw new Error("No result returned from server");
-        const dataUrl = `data:image/png;base64,${data.result_b64}`;
-        setResultUrl(dataUrl);
-        return { url: dataUrl, message: data.message };
-      } catch (err) {
-        const message =
-          err instanceof Error ? err.message : "Error al generar imagen con IA";
-        setError(message);
-        throw new Error(message);
-      } finally {
-        setIsApplying(false);
-      }
-    },
-    [],
-  );
-
-  const resetResult = useCallback(() => {
-    setResultUrl(null);
-    setError(null);
-  }, []);
-
-  return {
-    applyTexture,
-    applyTextureAI,
-    applyTextureOpenAI,
-    isApplying,
-    resultUrl,
-    error,
-    resetResult,
-  };
-}
+import { useCallback, useState } from "react";
+import { API_BASE } from "../api/client";
+
+interface ApplyTextureResult {
+  output_url: string;
+  output_filename: string;
+}
+
+export function useApplyTexture() {
+  const [isApplying, setIsApplying] = useState(false);
+  const [resultUrl, setResultUrl] = useState<string | null>(null);
+  const [error, setError] = useState<string | null>(null);
+
+  const applyTexture = useCallback(
+    async (filename: string, maskIndices: number[], textureName: string, originalFilename?: string) => {
+      setIsApplying(true);
+      setError(null);
+      try {
+        const res = await fetch(`${API_BASE}/seg/apply_texture`, {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify({
+            filename,
+            mask_indices: maskIndices,
+            texture_name: textureName,
+            original_filename: originalFilename ?? filename,
+            direction_mode: "auto",
+            angle_degrees: 0,
+          }),
+        });
+
+        if (!res.ok) {
+          const text = await res.text();
+          throw new Error(text || `Error ${res.status}`);
+        }
+
+        const data: ApplyTextureResult = await res.json();
+        setResultUrl(`${API_BASE}${data.output_url}`);
+        return data;
+      } catch (err) {
+        const message = err instanceof Error ? err.message : "Error al aplicar textura";
+        setError(message);
+        throw new Error(message);
+      } finally {
+        setIsApplying(false);
+      }
+    },
+    [],
+  );
+
+  const resetResult = useCallback(() => {
+    setResultUrl(null);
+    setError(null);
+  }, []);
+
+  return { applyTexture, isApplying, resultUrl, error, resetResult };
+}
diff --git a/frontend/src/hooks/useClientConfig.ts b/frontend/src/hooks/useClientConfig.ts
index c366c18e840d9f6f426c4487b3165b15a6acfff0..ceec08d3d6ad29c91263178a2d921a9425ad7b13 100644
--- a/frontend/src/hooks/useClientConfig.ts
+++ b/frontend/src/hooks/useClientConfig.ts
@@ -1,28 +1,28 @@
-import { useQuery } from "@tanstack/react-query";
-import { fetchClientConfig } from "../api/client";
-import type { AppSettings } from "../utils/settings";
-
-export function useClientConfig(
-  token: string,
-  clientKey: string,
-  settings: AppSettings,
-) {
-  return useQuery({
-    queryKey: [
-      "client-config",
-      token,
-      clientKey,
-      settings.customApiBase,
-      settings.autoDevToken,
-    ],
-    queryFn: () =>
-      fetchClientConfig(
-        token,
-        clientKey,
-        settings.customApiBase,
-        settings.autoDevToken,
-      ),
-    enabled: import.meta.env.DEV || Boolean(token || clientKey),
-    retry: false,
-  });
-}
+import { useQuery } from "@tanstack/react-query";
+import { fetchClientConfig } from "../api/client";
+import type { AppSettings } from "../utils/settings";
+
+export function useClientConfig(
+  token: string,
+  clientKey: string,
+  settings: AppSettings,
+) {
+  return useQuery({
+    queryKey: [
+      "client-config",
+      token,
+      clientKey,
+      settings.customApiBase,
+      settings.autoDevToken,
+    ],
+    queryFn: () =>
+      fetchClientConfig(
+        token,
+        clientKey,
+        settings.customApiBase,
+        settings.autoDevToken,
+      ),
+    enabled: import.meta.env.DEV || Boolean(token || clientKey),
+    retry: false,
+  });
+}
diff --git a/frontend/src/hooks/useSegmentUpload.ts b/frontend/src/hooks/useSegmentUpload.ts
index ffa4cc49cdd2b5c67eab36aaca2d818b2a984ac4..1077bb3941d83d287c2ddd6fc085d5e8be49bdce 100644
--- a/frontend/src/hooks/useSegmentUpload.ts
+++ b/frontend/src/hooks/useSegmentUpload.ts
@@ -1,81 +1,81 @@
-import { useCallback, useState } from "react";
-import { API_BASE } from "../api/client";
-
-interface JobStatus {
-  status: "processing" | "done" | "failed" | "timeout";
-  progress?: number;
-  stage?: string;
-  eta_seconds?: number;
-  filename?: string;
-  mask_count?: number;
-  message?: string;
-}
-
-async function pollJob(
-  jobId: string,
-  onProgress: (progress: number, message: string) => void,
-  intervalMs = 2000,
-): Promise<{ filename: string; mask_count: number }> {
-  while (true) {
-    const res = await fetch(`${API_BASE}/seg/jobs/${jobId}`);
-    if (!res.ok) throw new Error(`Error al consultar el job: ${res.status}`);
-    const job: JobStatus = await res.json();
-
-    if (job.status === "done" && job.filename && job.mask_count != null) {
-      return { filename: job.filename, mask_count: job.mask_count };
-    }
-    if (job.status === "failed" || job.status === "timeout") {
-      throw new Error(job.message ?? "La segmentación falló");
-    }
-
-    onProgress(job.progress ?? 0, job.message ?? "Procesando...");
-    await new Promise((r) => setTimeout(r, intervalMs));
-  }
-}
-
-export function useSegmentUpload() {
-  const [isUploading, setIsUploading] = useState(false);
-  const [error, setError] = useState<string | null>(null);
-
-  const uploadAndSegment = useCallback(
-    async (
-      file: File,
-      onProgress: (progress: number, message: string) => void,
-    ): Promise<{ filename: string; maskCount: number }> => {
-      setIsUploading(true);
-      setError(null);
-
-      try {
-        const form = new FormData();
-        form.append("file", file);
-
-        onProgress(2, "Subiendo imagen...");
-        const res = await fetch(`${API_BASE}/seg/upload_async`, {
-          method: "POST",
-          body: form,
-        });
-
-        if (!res.ok) {
-          const text = await res.text();
-          throw new Error(text || `Error al subir imagen: ${res.status}`);
-        }
-
-        const { job_id } = await res.json();
-        onProgress(10, "Imagen recibida. Iniciando segmentación...");
-
-        const result = await pollJob(job_id, onProgress);
-        return { filename: result.filename, maskCount: result.mask_count };
-      } catch (err) {
-        const message =
-          err instanceof Error ? err.message : "Error en la segmentación";
-        setError(message);
-        throw new Error(message);
-      } finally {
-        setIsUploading(false);
-      }
-    },
-    [],
-  );
-
-  return { uploadAndSegment, isUploading, error };
-}
+import { useCallback, useState } from "react";
+import { API_BASE } from "../api/client";
+
+interface JobStatus {
+  status: "processing" | "done" | "failed" | "timeout";
+  progress?: number;
+  stage?: string;
+  eta_seconds?: number;
+  filename?: string;
+  mask_count?: number;
+  message?: string;
+}
+
+async function pollJob(
+  jobId: string,
+  onProgress: (progress: number, message: string) => void,
+  intervalMs = 2000,
+): Promise<{ filename: string; mask_count: number }> {
+  while (true) {
+    const res = await fetch(`${API_BASE}/seg/jobs/${jobId}`);
+    if (!res.ok) throw new Error(`Error al consultar el job: ${res.status}`);
+    const job: JobStatus = await res.json();
+
+    if (job.status === "done" && job.filename && job.mask_count != null) {
+      return { filename: job.filename, mask_count: job.mask_count };
+    }
+    if (job.status === "failed" || job.status === "timeout") {
+      throw new Error(job.message ?? "La segmentación falló");
+    }
+
+    onProgress(job.progress ?? 0, job.message ?? "Procesando...");
+    await new Promise((r) => setTimeout(r, intervalMs));
+  }
+}
+
+export function useSegmentUpload() {
+  const [isUploading, setIsUploading] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+
+  const uploadAndSegment = useCallback(
+    async (
+      file: File,
+      onProgress: (progress: number, message: string) => void,
+    ): Promise<{ filename: string; maskCount: number }> => {
+      setIsUploading(true);
+      setError(null);
+
+      try {
+        const form = new FormData();
+        form.append("file", file);
+
+        onProgress(2, "Subiendo imagen...");
+        const res = await fetch(`${API_BASE}/seg/upload_async`, {
+          method: "POST",
+          body: form,
+        });
+
+        if (!res.ok) {
+          const text = await res.text();
+          throw new Error(text || `Error al subir imagen: ${res.status}`);
+        }
+
+        const { job_id } = await res.json();
+        onProgress(10, "Imagen recibida. Iniciando segmentación...");
+
+        const result = await pollJob(job_id, onProgress);
+        return { filename: result.filename, maskCount: result.mask_count };
+      } catch (err) {
+        const message =
+          err instanceof Error ? err.message : "Error en la segmentación";
+        setError(message);
+        throw new Error(message);
+      } finally {
+        setIsUploading(false);
+      }
+    },
+    [],
+  );
+
+  return { uploadAndSegment, isUploading, error };
+}
diff --git a/frontend/src/hooks/useUploadImage.ts b/frontend/src/hooks/useUploadImage.ts
index 90da3aec1a6871c02a6d9af0f78afb7518e139e7..b85b199c084e293c5f0620dccb40865f3ecb1428 100644
--- a/frontend/src/hooks/useUploadImage.ts
+++ b/frontend/src/hooks/useUploadImage.ts
@@ -1,33 +1,33 @@
-import { useCallback, useState } from "react";
-import { uploadRoomImage } from "../api/client";
-
-export default function useUploadImage() {
-  const [isUploading, setIsUploading] = useState(false);
-  const [uploadError, setUploadError] = useState<string | null>(null);
-
-  const uploadImage = useCallback(
-    async (file: File, customApiBase?: string) => {
-      setIsUploading(true);
-      setUploadError(null);
-
-      try {
-        return await uploadRoomImage(file, customApiBase);
-      } catch (error) {
-        const message =
-          error instanceof Error ? error.message : "Error subiendo la imagen";
-        setUploadError(message);
-        throw new Error(message);
-      } finally {
-        setIsUploading(false);
-      }
-    },
-    [],
-  );
-
-  return {
-    uploadImage,
-    isUploading,
-    uploadError,
-    setUploadError,
-  };
-}
+import { useCallback, useState } from "react";
+import { uploadRoomImage } from "../api/client";
+
+export default function useUploadImage() {
+  const [isUploading, setIsUploading] = useState(false);
+  const [uploadError, setUploadError] = useState<string | null>(null);
+
+  const uploadImage = useCallback(
+    async (file: File, customApiBase?: string) => {
+      setIsUploading(true);
+      setUploadError(null);
+
+      try {
+        return await uploadRoomImage(file, customApiBase);
+      } catch (error) {
+        const message =
+          error instanceof Error ? error.message : "Error subiendo la imagen";
+        setUploadError(message);
+        throw new Error(message);
+      } finally {
+        setIsUploading(false);
+      }
+    },
+    [],
+  );
+
+  return {
+    uploadImage,
+    isUploading,
+    uploadError,
+    setUploadError,
+  };
+}
diff --git a/frontend/src/index.css b/frontend/src/index.css
index 4e0c267b2a173298120513ec41fa426cabf4e05c..a2dbf5649ef99f5c84c0eb47506fb764f9f21922 100644
--- a/frontend/src/index.css
+++ b/frontend/src/index.css
@@ -1,84 +1,84 @@
-@tailwind base;
-@tailwind components;
-@tailwind utilities;
-
-:root {
-  --brand-blue: #0047ab;
-  --brand-black: #333333;
-  --brand-gray: #707070;
-  --brand-surface: #ffffff;
-  --brand-light: #f4f8ff;
-  --brand-border: #dbe7ff;
-  --brand-contrast: #25d366;
-
-  font-family:
-    Inter,
-    ui-sans-serif,
-    system-ui,
-    -apple-system,
-    BlinkMacSystemFont,
-    "Segoe UI",
-    sans-serif;
-  font-size: 16px;
-  color: var(--brand-black);
-  background: var(--brand-light);
-}
-
-*,
-*::before,
-*::after {
-  box-sizing: border-box;
-}
-
-html {
-  height: 100%;
-  /* Prevents elastic overscroll bounce on iOS PWA */
-  overscroll-behavior: none;
-}
-
-body {
-  margin: 0;
-  height: 100%;
-  /* dvh = dynamic viewport height: adjusts when mobile browser chrome appears/disappears */
-  min-height: 100dvh;
-  background: #f8fafc;
-  color: #111827;
-  overscroll-behavior: none;
-}
-
-#root {
-  height: 100%;
-  min-height: 100dvh;
-  display: flex;
-  flex-direction: column;
-}
-
-button,
-input,
-select,
-textarea {
-  font: inherit;
-}
-
-a {
-  color: inherit;
-  text-decoration: none;
-}
-
-img {
-  max-width: 100%;
-  display: block;
-}
-
-h1,
-h2,
-h3,
-p {
-  margin: 0;
-}
-
-ul {
-  margin: 0;
-  padding: 0;
-  list-style: none;
-}
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+:root {
+  --brand-blue: #0047ab;
+  --brand-black: #333333;
+  --brand-gray: #707070;
+  --brand-surface: #ffffff;
+  --brand-light: #f4f8ff;
+  --brand-border: #dbe7ff;
+  --brand-contrast: #25d366;
+
+  font-family:
+    Inter,
+    ui-sans-serif,
+    system-ui,
+    -apple-system,
+    BlinkMacSystemFont,
+    "Segoe UI",
+    sans-serif;
+  font-size: 16px;
+  color: var(--brand-black);
+  background: var(--brand-light);
+}
+
+*,
+*::before,
+*::after {
+  box-sizing: border-box;
+}
+
+html {
+  height: 100%;
+  /* Prevents elastic overscroll bounce on iOS PWA */
+  overscroll-behavior: none;
+}
+
+body {
+  margin: 0;
+  height: 100%;
+  /* dvh = dynamic viewport height: adjusts when mobile browser chrome appears/disappears */
+  min-height: 100dvh;
+  background: #f8fafc;
+  color: #111827;
+  overscroll-behavior: none;
+}
+
+#root {
+  height: 100%;
+  min-height: 100dvh;
+  display: flex;
+  flex-direction: column;
+}
+
+button,
+input,
+select,
+textarea {
+  font: inherit;
+}
+
+a {
+  color: inherit;
+  text-decoration: none;
+}
+
+img {
+  max-width: 100%;
+  display: block;
+}
+
+h1,
+h2,
+h3,
+p {
+  margin: 0;
+}
+
+ul {
+  margin: 0;
+  padding: 0;
+  list-style: none;
+}
diff --git a/frontend/src/main.tsx b/frontend/src/main.tsx
index 32a20a6ed9360f0f44eabb085d5c77c70dedfa66..c9c2724fe9498588c58e9faa7627a77c6eef6fdd 100644
--- a/frontend/src/main.tsx
+++ b/frontend/src/main.tsx
@@ -1,20 +1,20 @@
-import { StrictMode } from "react";
-import { createRoot } from "react-dom/client";
-import { BrowserRouter } from "react-router-dom";
-import { QueryClient, QueryClientProvider } from "@tanstack/react-query";
-import { ReactQueryDevtools } from "@tanstack/react-query-devtools";
-import "./index.css";
-import App from "./App.tsx";
-
-const queryClient = new QueryClient();
-
-createRoot(document.getElementById("root")!).render(
-  <StrictMode>
-    <BrowserRouter basename="/app">
-      <QueryClientProvider client={queryClient}>
-        <App />
-        {import.meta.env.DEV && <ReactQueryDevtools initialIsOpen={false} />}
-      </QueryClientProvider>
-    </BrowserRouter>
-  </StrictMode>,
-);
+import { StrictMode } from "react";
+import { createRoot } from "react-dom/client";
+import { BrowserRouter } from "react-router-dom";
+import { QueryClient, QueryClientProvider } from "@tanstack/react-query";
+import { ReactQueryDevtools } from "@tanstack/react-query-devtools";
+import "./index.css";
+import App from "./App.tsx";
+
+const queryClient = new QueryClient();
+
+createRoot(document.getElementById("root")!).render(
+  <StrictMode>
+    <BrowserRouter basename="/app">
+      <QueryClientProvider client={queryClient}>
+        <App />
+        {import.meta.env.DEV && <ReactQueryDevtools initialIsOpen={false} />}
+      </QueryClientProvider>
+    </BrowserRouter>
+  </StrictMode>,
+);
diff --git a/frontend/src/store/useAppStore.ts b/frontend/src/store/useAppStore.ts
index 1c8fd27395ee7011c28a5972c0d3fd68aeac0b76..406374bd20dfc66f7bd3285d53cf5b6043bd75cc 100644
--- a/frontend/src/store/useAppStore.ts
+++ b/frontend/src/store/useAppStore.ts
@@ -15,10 +15,9 @@ function getOrCreateUserId(): string {
   const key = "hr-user-id";
   let id = localStorage.getItem(key);
   if (!id) {
-    id =
-      typeof crypto !== "undefined" && crypto.randomUUID
-        ? crypto.randomUUID()
-        : `u-${Date.now()}-${Math.random().toString(36).slice(2, 9)}`;
+    id = typeof crypto !== "undefined" && crypto.randomUUID
+      ? crypto.randomUUID()
+      : `u-${Date.now()}-${Math.random().toString(36).slice(2, 9)}`;
     localStorage.setItem(key, id);
   }
   return id;
@@ -50,9 +49,7 @@ export const useHistoryStore = create<HistoryStore>()(
       setSessionHistory: (items) => set({ sessionHistory: items }),
       removeFromHistory: (filename) =>
         set((state) => ({
-          sessionHistory: state.sessionHistory.filter(
-            (h) => h.filename !== filename,
-          ),
+          sessionHistory: state.sessionHistory.filter((h) => h.filename !== filename),
         })),
     }),
     {
@@ -66,7 +63,6 @@ export const useHistoryStore = create<HistoryStore>()(
 type AppStore = {
   previewImage: string | null;
   uploadMessage: string | null;
-  uploadedFile: File | null;
   openProductId: string | number | null;
   viewMode: ViewMode;
   segmentFilename: string | null;
@@ -75,7 +71,6 @@ type AppStore = {
   accumulatedFilename: string | null;
   setPreviewImage: (previewImage: string | null) => void;
   setUploadMessage: (uploadMessage: string | null) => void;
-  setUploadedFile: (f: File | null) => void;
   setOpenProductId: (openProductId: string | number | null) => void;
   setViewMode: (viewMode: ViewMode) => void;
   setSegmentResult: (filename: string, maskCount: number) => void;
@@ -89,7 +84,6 @@ const useAppStore = create<AppStore>()(
     (set) => ({
       previewImage: null,
       uploadMessage: null,
-      uploadedFile: null,
       openProductId: null,
       viewMode: "list",
       segmentFilename: null,
@@ -98,19 +92,16 @@ const useAppStore = create<AppStore>()(
       accumulatedFilename: null,
       setPreviewImage: (previewImage) => set({ previewImage }),
       setUploadMessage: (uploadMessage) => set({ uploadMessage }),
-      setUploadedFile: (uploadedFile) => set({ uploadedFile }),
       setOpenProductId: (openProductId) => set({ openProductId }),
       setViewMode: (viewMode) => set({ viewMode }),
       setSegmentResult: (segmentFilename, maskCount) =>
         set({ segmentFilename, maskCount }),
       setSegmentProgress: (segmentProgress) => set({ segmentProgress }),
-      setAccumulatedFilename: (accumulatedFilename) =>
-        set({ accumulatedFilename }),
+      setAccumulatedFilename: (accumulatedFilename) => set({ accumulatedFilename }),
       reset: () =>
         set({
           previewImage: null,
           uploadMessage: null,
-          uploadedFile: null,
           openProductId: null,
           viewMode: "list",
           segmentFilename: null,
diff --git a/frontend/src/types.ts b/frontend/src/types.ts
index f9dc218a6c6a4469f90cb8da79ddcdc8e575f4a2..6176e3cff964dc9f0f73f7009bb027f83f3d16d4 100644
--- a/frontend/src/types.ts
+++ b/frontend/src/types.ts
@@ -1,24 +1,24 @@
-export interface ClientData {
-  client_id: string;
-  nombre: string;
-  color_primario: string;
-  created_at?: string;
-}
-
-export interface RouteItem {
-  label: string;
-  path: string;
-}
-
-export interface Product {
-  id: number | string;
-  brand: string;
-  name: string;
-  ref: string;
-  size: string;
-  image: string;
-  description?: string[];
-  detailUrl?: string;
-  tipo?: "suelos" | "paredes";
-  categoria?: string;
-}
+export interface ClientData {
+  client_id: string;
+  nombre: string;
+  color_primario: string;
+  created_at?: string;
+}
+
+export interface RouteItem {
+  label: string;
+  path: string;
+}
+
+export interface Product {
+  id: number | string;
+  brand: string;
+  name: string;
+  ref: string;
+  size: string;
+  image: string;
+  description?: string[];
+  detailUrl?: string;
+  tipo?: "suelos" | "paredes";
+  categoria?: string;
+}
diff --git a/frontend/src/utils/settings.ts b/frontend/src/utils/settings.ts
index c6264eb142a8dbe0e70e481b8b30892a2ca740d8..4b54cf32490485fdd13b8f2076d221849c956662 100644
--- a/frontend/src/utils/settings.ts
+++ b/frontend/src/utils/settings.ts
@@ -1,33 +1,33 @@
-export interface AppSettings {
-  showRouteList: boolean;
-  customApiBase: string;
-  autoDevToken: boolean;
-}
-
-export const DEFAULT_SETTINGS: AppSettings = {
-  showRouteList: true,
-  customApiBase: "",
-  autoDevToken: true,
-};
-
-const STORAGE_KEY = "saas-app-settings";
-
-export function loadSettings(): AppSettings {
-  if (typeof window === "undefined") return DEFAULT_SETTINGS;
-  try {
-    const raw = window.localStorage.getItem(STORAGE_KEY);
-    if (!raw) return DEFAULT_SETTINGS;
-    const parsed = JSON.parse(raw) as Partial<AppSettings>;
-    return {
-      ...DEFAULT_SETTINGS,
-      ...parsed,
-    };
-  } catch {
-    return DEFAULT_SETTINGS;
-  }
-}
-
-export function saveSettings(settings: AppSettings) {
-  if (typeof window === "undefined") return;
-  window.localStorage.setItem(STORAGE_KEY, JSON.stringify(settings));
-}
+export interface AppSettings {
+  showRouteList: boolean;
+  customApiBase: string;
+  autoDevToken: boolean;
+}
+
+export const DEFAULT_SETTINGS: AppSettings = {
+  showRouteList: true,
+  customApiBase: "",
+  autoDevToken: true,
+};
+
+const STORAGE_KEY = "saas-app-settings";
+
+export function loadSettings(): AppSettings {
+  if (typeof window === "undefined") return DEFAULT_SETTINGS;
+  try {
+    const raw = window.localStorage.getItem(STORAGE_KEY);
+    if (!raw) return DEFAULT_SETTINGS;
+    const parsed = JSON.parse(raw) as Partial<AppSettings>;
+    return {
+      ...DEFAULT_SETTINGS,
+      ...parsed,
+    };
+  } catch {
+    return DEFAULT_SETTINGS;
+  }
+}
+
+export function saveSettings(settings: AppSettings) {
+  if (typeof window === "undefined") return;
+  window.localStorage.setItem(STORAGE_KEY, JSON.stringify(settings));
+}
diff --git a/frontend/src/version.ts b/frontend/src/version.ts
index b38cdb3c03f4a7577a3e6b69f154a413773de52c..6952112085768231747eae6c5a99c7cbbfc8b84f 100644
--- a/frontend/src/version.ts
+++ b/frontend/src/version.ts
@@ -1 +1 @@
-export const appVersion = "0.1.0-dev.20260512T032221";
+export const appVersion = "0.1.0-dev.20260507T183851";
diff --git a/frontend/tailwind.config.js b/frontend/tailwind.config.js
index dd569bd22d3b37604289da90d901b179a93e8de3..3a400ba050139dd15b3c45e803138d37aa63bcd8 100644
--- a/frontend/tailwind.config.js
+++ b/frontend/tailwind.config.js
@@ -1,7 +1,7 @@
-export default {
-  content: ["./index.html", "./src/**/*.{js,ts,jsx,tsx}"],
-  theme: {
-    extend: {},
-  },
-  plugins: [],
-};
+export default {
+  content: ["./index.html", "./src/**/*.{js,ts,jsx,tsx}"],
+  theme: {
+    extend: {},
+  },
+  plugins: [],
+};
diff --git a/frontend/tempRoomSetup.tsx b/frontend/tempRoomSetup.tsx
index 2584ae88e7c441bd48c69e45e16cc4c55591ea04..2784051afedb2c02e11a4c5f92df349d00b44e24 100644
--- a/frontend/tempRoomSetup.tsx
+++ b/frontend/tempRoomSetup.tsx
@@ -1,284 +1,284 @@
-import React, { useState, useRef } from "react";
-import {
-  X,
-  Camera,
-  Package,
-  Camera as CameraIcon,
-  Smartphone,
-  MousePointer2,
-  Check,
-  Play,
-  UploadCloud,
-} from "lucide-react";
-
-// --- DATOS DE PRUEBA ---
-const categorias = [
-  { id: "todos", label: "Todos", count: 32 },
-  { id: "bano", label: "Baño", count: 5 },
-  { id: "cocina", label: "Cocina", count: 10 },
-  { id: "comedor", label: "Comedor", count: 5 },
-  { id: "dormitorio", label: "Dormitorio", count: 4 },
-  { id: "espacio_abierto", label: "Espacio abierto", count: 3 },
-  { id: "sala", label: "Sala de estar", count: 9 },
-  { id: "terraza", label: "Terraza", count: 6 },
-];
-
-const habitaciones = [
-  {
-    id: 1,
-    title: "Dining Room - Glossy",
-    category: "comedor",
-    img: "https://images.unsplash.com/photo-1617806118233-18e1c0945594?auto=format&fit=crop&w=600&q=80",
-  },
-  {
-    id: 2,
-    title: "Dining Area",
-    category: "comedor",
-    img: "https://images.unsplash.com/photo-1604578762246-41134e37f9cc?auto=format&fit=crop&w=600&q=80",
-  },
-  {
-    id: 3,
-    title: "Dining room",
-    category: "comedor",
-    img: "https://images.unsplash.com/photo-1593696140826-c58b021acf8b?auto=format&fit=crop&w=600&q=80",
-  },
-  {
-    id: 4,
-    title: "Sala de estar",
-    category: "sala",
-    img: "https://images.unsplash.com/photo-1583847268964-b28ce8f30f15?auto=format&fit=crop&w=600&q=80",
-  },
-  {
-    id: 5,
-    title: "Modern Kitchen",
-    category: "cocina",
-    img: "https://images.unsplash.com/photo-1556910103-1c02745a8720?auto=format&fit=crop&w=600&q=80",
-  },
-  {
-    id: 6,
-    title: "Minimalist Bath",
-    category: "bano",
-    img: "https://images.unsplash.com/photo-1600566752355-35792bedcfea?auto=format&fit=crop&w=600&q=80",
-  },
-  {
-    id: 7,
-    title: "Cozy Bedroom",
-    category: "dormitorio",
-    img: "https://images.unsplash.com/photo-1616594039964-ae9021a400a0?auto=format&fit=crop&w=600&q=80",
-  },
-  {
-    id: 8,
-    title: "Open Concept",
-    category: "espacio_abierto",
-    img: "https://images.unsplash.com/photo-1600607686527-6fb886090705?auto=format&fit=crop&w=600&q=80",
-  },
-];
-
-export default function App() {
-  const [categoriaActiva, setCategoriaActiva] = useState("todos");
-  const [isDragging, setIsDragging] = useState(false);
-  const [previewImage, setPreviewImage] = useState<string | null>(null);
-  const fileInputRef = useRef<HTMLInputElement>(null);
-
-  // Filtrar habitaciones
-  const habitacionesFiltradas =
-    categoriaActiva === "todos"
-      ? habitaciones
-      : habitaciones.filter((h) => h.category === categoriaActiva);
-
-  // Manejadores para Drag & Drop
-  const handleDragOver = (e: React.DragEvent) => {
-    e.preventDefault();
-    setIsDragging(true);
-  };
-
-  const handleDragLeave = (e: React.DragEvent) => {
-    e.preventDefault();
-    setIsDragging(false);
-  };
-
-  const handleDrop = (e: React.DragEvent) => {
-    e.preventDefault();
-    setIsDragging(false);
-    const file = e.dataTransfer.files[0];
-    handleFileSelection(file);
-  };
-
-  const handleFileChange = (e: React.ChangeEvent<HTMLInputElement>) => {
-    const file = e.target.files?.[0];
-    if (file) handleFileSelection(file);
-  };
-
-  const handleFileSelection = (file: File) => {
-    if (file && file.type.startsWith("image/")) {
-      const reader = new FileReader();
-      reader.onload = (event) => {
-        setPreviewImage(event.target?.result as string);
-      };
-      reader.readAsDataURL(file);
-    }
-  };
-
-  const triggerFileInput = () => {
-    fileInputRef.current?.click();
-  };
-
-  return (
-    <div className="min-h-screen bg-white font-sans text-gray-800">
-      {/* Contenedor Principal */}
-      <main className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
-        {/* Cabecera / Botón de cerrar */}
-        <div className="mb-6">
-          <button className="p-2 hover:bg-gray-100 rounded-full transition-colors">
-            <X className="w-6 h-6 text-gray-500" />
-          </button>
-        </div>
-
-        {/* SECCIÓN SUPERIOR: Sube tu foto */}
-        <section className="grid grid-cols-1 lg:grid-cols-2 gap-12 mb-20">
-          {/* Columna Izquierda: Textos y Botones */}
-          <div className="flex flex-col justify-center">
-            <h1 className="text-3xl sm:text-4xl font-bold text-[#2A2A35] mb-8">
-              Ver los productos en su cuarto
-            </h1>
-
-            <ul className="space-y-6 mb-10">
-              <li className="flex items-center gap-4 text-lg font-medium text-gray-700">
-                <Camera className="w-6 h-6 text-gray-600" />
-                Sube una foto de tu habitación
-              </li>
-              <li className="flex items-center gap-4 text-lg font-medium text-gray-700">
-                <Package className="w-6 h-6 text-gray-600" />
-                Prueba nuestros productos
-              </li>
-            </ul>
-
-            <div className="space-y-4 max-w-md">
-              <button
-                onClick={triggerFileInput}
-                className="w-full bg-[#FACC15] hover:bg-[#EAB308] text-black font-bold text-lg py-4 px-6 rounded-xl flex items-center justify-center gap-3 transition-colors shadow-sm"
-              >
-                <CameraIcon className="w-6 h-6" strokeWidth={2.5} />
-                Sube tu foto
-              </button>
-
-              <button className="w-full bg-[#F8F9FA] hover:bg-gray-100 border border-gray-200 text-gray-600 font-medium py-3 px-6 rounded-xl flex items-center justify-center gap-3 transition-colors">
-                <div className="p-1 border border-gray-400 rounded">
-                  <Smartphone className="w-4 h-4" />
-                </div>
-                <span className="text-sm">
-                  O escanea un código QR para subir fotos
-                </span>
-              </button>
-            </div>
-          </div>
-
-          {/* Columna Derecha: Dropzone de Imagen */}
-          <div
-            className={`relative rounded-2xl overflow-hidden aspect-[4/3] flex flex-col items-center justify-center border-2 border-dashed transition-all duration-200 ${
-              isDragging
-                ? "border-[#FACC15] bg-[#FACC15]/10"
-                : "border-gray-300 bg-gray-50 hover:bg-gray-100"
-            }`}
-            onDragOver={handleDragOver}
-            onDragLeave={handleDragLeave}
-            onDrop={handleDrop}
-          >
-            {previewImage ? (
-              <div className="relative w-full h-full group">
-                <img
-                  src={previewImage}
-                  alt="Vista previa"
-                  className="w-full h-full object-cover"
-                />
-                <div className="absolute inset-0 bg-black/40 opacity-0 group-hover:opacity-100 transition-opacity flex items-center justify-center backdrop-blur-sm">
-                  <button
-                    onClick={() => setPreviewImage(null)}
-                    className="bg-white text-gray-800 font-medium py-2 px-4 rounded-lg flex items-center gap-2 hover:bg-gray-100 transition-colors shadow-lg"
-                  >
-                    <X className="w-4 h-4" /> Eliminar foto
-                  </button>
-                </div>
-              </div>
-            ) : (
-              <>
-                <input
-                  type="file"
-                  accept="image/*"
-                  onChange={handleFileChange}
-                  ref={fileInputRef}
-                  className="absolute inset-0 w-full h-full opacity-0 cursor-pointer"
-                />
-                <div className="flex flex-col items-center pointer-events-none text-center p-6">
-                  <div
-                    className={`w-16 h-16 rounded-full flex items-center justify-center mb-4 transition-colors ${
-                      isDragging
-                        ? "bg-[#FACC15]/20 text-[#EAB308]"
-                        : "bg-gray-200 text-gray-500"
-                    }`}
-                  >
-                    <UploadCloud className="w-8 h-8" />
-                  </div>
-                  <h3 className="text-xl font-bold text-gray-700 mb-2">
-                    {isDragging
-                      ? "Suelta la imagen aquí"
-                      : "Arrastra tu foto aquí"}
-                  </h3>
-                  <p className="text-gray-500">
-                    o haz clic para explorar en tu dispositivo
-                  </p>
-                  <p className="text-xs text-gray-400 mt-4">
-                    Formatos soportados: JPG, PNG
-                  </p>
-                </div>
-              </>
-            )}
-          </div>
-        </section>
-
-        {/* SECCIÓN INFERIOR: Habitaciones de demostración */}
-        <section>
-          <h2 className="text-2xl font-bold text-gray-600 mb-6">
-            ¿No tienes una foto? Prueba nuestras habitaciones de demostración
-          </h2>
-
-          {/* Filtros */}
-          <div className="flex flex-wrap gap-2 mb-8">
-            {categorias.map((cat) => (
-              <button
-                key={cat.id}
-                onClick={() => setCategoriaActiva(cat.id)}
-                className={`px-4 py-2 rounded-lg text-sm font-medium transition-all duration-200 border ${
-                  categoriaActiva === cat.id
-                    ? "bg-[#FACC15] border-[#FACC15] text-black shadow-sm"
-                    : "bg-white border-gray-300 text-gray-600 hover:bg-gray-50"
-                }`}
-              >
-                {cat.label} ({cat.count})
-              </button>
-            ))}
-          </div>
-
-          {/* Cuadrícula de Imágenes */}
-          <div className="grid grid-cols-1 sm:grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-6">
-            {habitacionesFiltradas.map((hab) => (
-              <div key={hab.id} className="group cursor-pointer">
-                <div className="relative aspect-[4/3] rounded-2xl overflow-hidden mb-3 bg-gray-100">
-                  <img
-                    src={hab.img}
-                    alt={hab.title}
-                    className="w-full h-full object-cover transition-transform duration-500 group-hover:scale-105"
-                  />
-                  <div className="absolute inset-0 bg-black/0 group-hover:bg-black/10 transition-colors duration-300" />
-                </div>
-                <h3 className="text-gray-700 font-medium text-sm px-1">
-                  {hab.title}
-                </h3>
-              </div>
-            ))}
-          </div>
-        </section>
-      </main>
-    </div>
-  );
-}
+import React, { useState, useRef } from "react";
+import {
+  X,
+  Camera,
+  Package,
+  Camera as CameraIcon,
+  Smartphone,
+  MousePointer2,
+  Check,
+  Play,
+  UploadCloud,
+} from "lucide-react";
+
+// --- DATOS DE PRUEBA ---
+const categorias = [
+  { id: "todos", label: "Todos", count: 32 },
+  { id: "bano", label: "Baño", count: 5 },
+  { id: "cocina", label: "Cocina", count: 10 },
+  { id: "comedor", label: "Comedor", count: 5 },
+  { id: "dormitorio", label: "Dormitorio", count: 4 },
+  { id: "espacio_abierto", label: "Espacio abierto", count: 3 },
+  { id: "sala", label: "Sala de estar", count: 9 },
+  { id: "terraza", label: "Terraza", count: 6 },
+];
+
+const habitaciones = [
+  {
+    id: 1,
+    title: "Dining Room - Glossy",
+    category: "comedor",
+    img: "https://images.unsplash.com/photo-1617806118233-18e1c0945594?auto=format&fit=crop&w=600&q=80",
+  },
+  {
+    id: 2,
+    title: "Dining Area",
+    category: "comedor",
+    img: "https://images.unsplash.com/photo-1604578762246-41134e37f9cc?auto=format&fit=crop&w=600&q=80",
+  },
+  {
+    id: 3,
+    title: "Dining room",
+    category: "comedor",
+    img: "https://images.unsplash.com/photo-1593696140826-c58b021acf8b?auto=format&fit=crop&w=600&q=80",
+  },
+  {
+    id: 4,
+    title: "Sala de estar",
+    category: "sala",
+    img: "https://images.unsplash.com/photo-1583847268964-b28ce8f30f15?auto=format&fit=crop&w=600&q=80",
+  },
+  {
+    id: 5,
+    title: "Modern Kitchen",
+    category: "cocina",
+    img: "https://images.unsplash.com/photo-1556910103-1c02745a8720?auto=format&fit=crop&w=600&q=80",
+  },
+  {
+    id: 6,
+    title: "Minimalist Bath",
+    category: "bano",
+    img: "https://images.unsplash.com/photo-1600566752355-35792bedcfea?auto=format&fit=crop&w=600&q=80",
+  },
+  {
+    id: 7,
+    title: "Cozy Bedroom",
+    category: "dormitorio",
+    img: "https://images.unsplash.com/photo-1616594039964-ae9021a400a0?auto=format&fit=crop&w=600&q=80",
+  },
+  {
+    id: 8,
+    title: "Open Concept",
+    category: "espacio_abierto",
+    img: "https://images.unsplash.com/photo-1600607686527-6fb886090705?auto=format&fit=crop&w=600&q=80",
+  },
+];
+
+export default function App() {
+  const [categoriaActiva, setCategoriaActiva] = useState("todos");
+  const [isDragging, setIsDragging] = useState(false);
+  const [previewImage, setPreviewImage] = useState<string | null>(null);
+  const fileInputRef = useRef<HTMLInputElement>(null);
+
+  // Filtrar habitaciones
+  const habitacionesFiltradas =
+    categoriaActiva === "todos"
+      ? habitaciones
+      : habitaciones.filter((h) => h.category === categoriaActiva);
+
+  // Manejadores para Drag & Drop
+  const handleDragOver = (e: React.DragEvent) => {
+    e.preventDefault();
+    setIsDragging(true);
+  };
+
+  const handleDragLeave = (e: React.DragEvent) => {
+    e.preventDefault();
+    setIsDragging(false);
+  };
+
+  const handleDrop = (e: React.DragEvent) => {
+    e.preventDefault();
+    setIsDragging(false);
+    const file = e.dataTransfer.files[0];
+    handleFileSelection(file);
+  };
+
+  const handleFileChange = (e: React.ChangeEvent<HTMLInputElement>) => {
+    const file = e.target.files?.[0];
+    if (file) handleFileSelection(file);
+  };
+
+  const handleFileSelection = (file: File) => {
+    if (file && file.type.startsWith("image/")) {
+      const reader = new FileReader();
+      reader.onload = (event) => {
+        setPreviewImage(event.target?.result as string);
+      };
+      reader.readAsDataURL(file);
+    }
+  };
+
+  const triggerFileInput = () => {
+    fileInputRef.current?.click();
+  };
+
+  return (
+    <div className="min-h-screen bg-white font-sans text-gray-800">
+      {/* Contenedor Principal */}
+      <main className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
+        {/* Cabecera / Botón de cerrar */}
+        <div className="mb-6">
+          <button className="p-2 hover:bg-gray-100 rounded-full transition-colors">
+            <X className="w-6 h-6 text-gray-500" />
+          </button>
+        </div>
+
+        {/* SECCIÓN SUPERIOR: Sube tu foto */}
+        <section className="grid grid-cols-1 lg:grid-cols-2 gap-12 mb-20">
+          {/* Columna Izquierda: Textos y Botones */}
+          <div className="flex flex-col justify-center">
+            <h1 className="text-3xl sm:text-4xl font-bold text-[#2A2A35] mb-8">
+              Ver los productos en su cuarto
+            </h1>
+
+            <ul className="space-y-6 mb-10">
+              <li className="flex items-center gap-4 text-lg font-medium text-gray-700">
+                <Camera className="w-6 h-6 text-gray-600" />
+                Sube una foto de tu habitación
+              </li>
+              <li className="flex items-center gap-4 text-lg font-medium text-gray-700">
+                <Package className="w-6 h-6 text-gray-600" />
+                Prueba nuestros productos
+              </li>
+            </ul>
+
+            <div className="space-y-4 max-w-md">
+              <button
+                onClick={triggerFileInput}
+                className="w-full bg-[#FACC15] hover:bg-[#EAB308] text-black font-bold text-lg py-4 px-6 rounded-xl flex items-center justify-center gap-3 transition-colors shadow-sm"
+              >
+                <CameraIcon className="w-6 h-6" strokeWidth={2.5} />
+                Sube tu foto
+              </button>
+
+              <button className="w-full bg-[#F8F9FA] hover:bg-gray-100 border border-gray-200 text-gray-600 font-medium py-3 px-6 rounded-xl flex items-center justify-center gap-3 transition-colors">
+                <div className="p-1 border border-gray-400 rounded">
+                  <Smartphone className="w-4 h-4" />
+                </div>
+                <span className="text-sm">
+                  O escanea un código QR para subir fotos
+                </span>
+              </button>
+            </div>
+          </div>
+
+          {/* Columna Derecha: Dropzone de Imagen */}
+          <div
+            className={`relative rounded-2xl overflow-hidden aspect-[4/3] flex flex-col items-center justify-center border-2 border-dashed transition-all duration-200 ${
+              isDragging
+                ? "border-[#FACC15] bg-[#FACC15]/10"
+                : "border-gray-300 bg-gray-50 hover:bg-gray-100"
+            }`}
+            onDragOver={handleDragOver}
+            onDragLeave={handleDragLeave}
+            onDrop={handleDrop}
+          >
+            {previewImage ? (
+              <div className="relative w-full h-full group">
+                <img
+                  src={previewImage}
+                  alt="Vista previa"
+                  className="w-full h-full object-cover"
+                />
+                <div className="absolute inset-0 bg-black/40 opacity-0 group-hover:opacity-100 transition-opacity flex items-center justify-center backdrop-blur-sm">
+                  <button
+                    onClick={() => setPreviewImage(null)}
+                    className="bg-white text-gray-800 font-medium py-2 px-4 rounded-lg flex items-center gap-2 hover:bg-gray-100 transition-colors shadow-lg"
+                  >
+                    <X className="w-4 h-4" /> Eliminar foto
+                  </button>
+                </div>
+              </div>
+            ) : (
+              <>
+                <input
+                  type="file"
+                  accept="image/*"
+                  onChange={handleFileChange}
+                  ref={fileInputRef}
+                  className="absolute inset-0 w-full h-full opacity-0 cursor-pointer"
+                />
+                <div className="flex flex-col items-center pointer-events-none text-center p-6">
+                  <div
+                    className={`w-16 h-16 rounded-full flex items-center justify-center mb-4 transition-colors ${
+                      isDragging
+                        ? "bg-[#FACC15]/20 text-[#EAB308]"
+                        : "bg-gray-200 text-gray-500"
+                    }`}
+                  >
+                    <UploadCloud className="w-8 h-8" />
+                  </div>
+                  <h3 className="text-xl font-bold text-gray-700 mb-2">
+                    {isDragging
+                      ? "Suelta la imagen aquí"
+                      : "Arrastra tu foto aquí"}
+                  </h3>
+                  <p className="text-gray-500">
+                    o haz clic para explorar en tu dispositivo
+                  </p>
+                  <p className="text-xs text-gray-400 mt-4">
+                    Formatos soportados: JPG, PNG
+                  </p>
+                </div>
+              </>
+            )}
+          </div>
+        </section>
+
+        {/* SECCIÓN INFERIOR: Habitaciones de demostración */}
+        <section>
+          <h2 className="text-2xl font-bold text-gray-600 mb-6">
+            ¿No tienes una foto? Prueba nuestras habitaciones de demostración
+          </h2>
+
+          {/* Filtros */}
+          <div className="flex flex-wrap gap-2 mb-8">
+            {categorias.map((cat) => (
+              <button
+                key={cat.id}
+                onClick={() => setCategoriaActiva(cat.id)}
+                className={`px-4 py-2 rounded-lg text-sm font-medium transition-all duration-200 border ${
+                  categoriaActiva === cat.id
+                    ? "bg-[#FACC15] border-[#FACC15] text-black shadow-sm"
+                    : "bg-white border-gray-300 text-gray-600 hover:bg-gray-50"
+                }`}
+              >
+                {cat.label} ({cat.count})
+              </button>
+            ))}
+          </div>
+
+          {/* Cuadrícula de Imágenes */}
+          <div className="grid grid-cols-1 sm:grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-6">
+            {habitacionesFiltradas.map((hab) => (
+              <div key={hab.id} className="group cursor-pointer">
+                <div className="relative aspect-[4/3] rounded-2xl overflow-hidden mb-3 bg-gray-100">
+                  <img
+                    src={hab.img}
+                    alt={hab.title}
+                    className="w-full h-full object-cover transition-transform duration-500 group-hover:scale-105"
+                  />
+                  <div className="absolute inset-0 bg-black/0 group-hover:bg-black/10 transition-colors duration-300" />
+                </div>
+                <h3 className="text-gray-700 font-medium text-sm px-1">
+                  {hab.title}
+                </h3>
+              </div>
+            ))}
+          </div>
+        </section>
+      </main>
+    </div>
+  );
+}
diff --git a/frontend/tsconfig.app.json b/frontend/tsconfig.app.json
index 5d560e388240dbdcea340d1adf54b9dc95f933d4..7f42e5f7cd2e79c7b5a25b753e56b1bcf94e1381 100644
--- a/frontend/tsconfig.app.json
+++ b/frontend/tsconfig.app.json
@@ -1,25 +1,25 @@
-{
-  "compilerOptions": {
-    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
-    "target": "es2023",
-    "lib": ["ES2023", "DOM"],
-    "module": "esnext",
-    "types": ["vite/client"],
-    "skipLibCheck": true,
-
-    /* Bundler mode */
-    "moduleResolution": "bundler",
-    "allowImportingTsExtensions": true,
-    "verbatimModuleSyntax": true,
-    "moduleDetection": "force",
-    "noEmit": true,
-    "jsx": "react-jsx",
-
-    /* Linting */
-    "noUnusedLocals": true,
-    "noUnusedParameters": true,
-    "erasableSyntaxOnly": true,
-    "noFallthroughCasesInSwitch": true
-  },
-  "include": ["src"]
-}
+{
+  "compilerOptions": {
+    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
+    "target": "es2023",
+    "lib": ["ES2023", "DOM"],
+    "module": "esnext",
+    "types": ["vite/client"],
+    "skipLibCheck": true,
+
+    /* Bundler mode */
+    "moduleResolution": "bundler",
+    "allowImportingTsExtensions": true,
+    "verbatimModuleSyntax": true,
+    "moduleDetection": "force",
+    "noEmit": true,
+    "jsx": "react-jsx",
+
+    /* Linting */
+    "noUnusedLocals": true,
+    "noUnusedParameters": true,
+    "erasableSyntaxOnly": true,
+    "noFallthroughCasesInSwitch": true
+  },
+  "include": ["src"]
+}
diff --git a/frontend/tsconfig.json b/frontend/tsconfig.json
index 38e8e3bf874144a573c37817f1e460b9e6dd8ada..1ffef600d959ec9e396d5a260bd3f5b927b2cef8 100644
--- a/frontend/tsconfig.json
+++ b/frontend/tsconfig.json
@@ -1,7 +1,7 @@
-{
-  "files": [],
-  "references": [
-    { "path": "./tsconfig.app.json" },
-    { "path": "./tsconfig.node.json" }
-  ]
-}
+{
+  "files": [],
+  "references": [
+    { "path": "./tsconfig.app.json" },
+    { "path": "./tsconfig.node.json" }
+  ]
+}
diff --git a/frontend/tsconfig.node.json b/frontend/tsconfig.node.json
index 09fe7a71655904cabc441ada690d27b78c496861..d3c52ea64c6cd6bad118474410f5322f48e257a6 100644
--- a/frontend/tsconfig.node.json
+++ b/frontend/tsconfig.node.json
@@ -1,24 +1,24 @@
-{
-  "compilerOptions": {
-    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo",
-    "target": "es2023",
-    "lib": ["ES2023"],
-    "module": "esnext",
-    "types": ["node"],
-    "skipLibCheck": true,
-
-    /* Bundler mode */
-    "moduleResolution": "bundler",
-    "allowImportingTsExtensions": true,
-    "verbatimModuleSyntax": true,
-    "moduleDetection": "force",
-    "noEmit": true,
-
-    /* Linting */
-    "noUnusedLocals": true,
-    "noUnusedParameters": true,
-    "erasableSyntaxOnly": true,
-    "noFallthroughCasesInSwitch": true
-  },
-  "include": ["vite.config.ts"]
-}
+{
+  "compilerOptions": {
+    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo",
+    "target": "es2023",
+    "lib": ["ES2023"],
+    "module": "esnext",
+    "types": ["node"],
+    "skipLibCheck": true,
+
+    /* Bundler mode */
+    "moduleResolution": "bundler",
+    "allowImportingTsExtensions": true,
+    "verbatimModuleSyntax": true,
+    "moduleDetection": "force",
+    "noEmit": true,
+
+    /* Linting */
+    "noUnusedLocals": true,
+    "noUnusedParameters": true,
+    "erasableSyntaxOnly": true,
+    "noFallthroughCasesInSwitch": true
+  },
+  "include": ["vite.config.ts"]
+}
diff --git a/frontend/vite.config.ts b/frontend/vite.config.ts
index c7f5bb15fbd62f66d2f4d82b1ce034f38d0d8d49..cd3f07eee86edf54d5e0568605591ec7704f9c07 100644
--- a/frontend/vite.config.ts
+++ b/frontend/vite.config.ts
@@ -1,30 +1,30 @@
-import { defineConfig, loadEnv } from "vite";
-import react from "@vitejs/plugin-react";
-import { readFileSync } from "fs";
-import { dirname, join } from "path";
-import { fileURLToPath } from "url";
-
-// https://vite.dev/config/
-export default defineConfig(({ mode }) => {
-  const env = loadEnv(mode, process.cwd(), "");
-  const pkgPath = join(dirname(fileURLToPath(import.meta.url)), "package.json");
-  const pkg = JSON.parse(readFileSync(pkgPath, "utf8"));
-  const appVersion = env.VITE_APP_VERSION || pkg.version || "0.0.0";
-
-  return {
-    base: env.VITE_APP_BASE || "/",
-    define: {
-      "import.meta.env.VITE_APP_VERSION": JSON.stringify(appVersion),
-    },
-    plugins: [react()],
-    server: {
-      proxy: {
-        "/api": "http://localhost:8000",
-        "/seg": "http://localhost:8000",
-        "/uploads": "http://localhost:8000",
-        "/preview": "http://localhost:8000",
-        "/widget.js": "http://localhost:8000",
-      },
-    },
-  };
-});
+import { defineConfig, loadEnv } from "vite";
+import react from "@vitejs/plugin-react";
+import { readFileSync } from "fs";
+import { dirname, join } from "path";
+import { fileURLToPath } from "url";
+
+// https://vite.dev/config/
+export default defineConfig(({ mode }) => {
+  const env = loadEnv(mode, process.cwd(), "");
+  const pkgPath = join(dirname(fileURLToPath(import.meta.url)), "package.json");
+  const pkg = JSON.parse(readFileSync(pkgPath, "utf8"));
+  const appVersion = env.VITE_APP_VERSION || pkg.version || "0.0.0";
+
+  return {
+    base: env.VITE_APP_BASE || "/",
+    define: {
+      "import.meta.env.VITE_APP_VERSION": JSON.stringify(appVersion),
+    },
+    plugins: [react()],
+    server: {
+      proxy: {
+        "/api": "http://localhost:8000",
+        "/seg": "http://localhost:8000",
+        "/uploads": "http://localhost:8000",
+        "/preview": "http://localhost:8000",
+        "/widget.js": "http://localhost:8000",
+      },
+    },
+  };
+});