fix: resolve libgl1 build error and update dependencies for HuggingFace deployment

ASSETS.md

@@ -55,6 +55,18 @@
 
 ---
 
+## Claude Code Quick Start
+
+```powershell
+# Start Claude Code with CCR (Gemini backend)
+$env:Path = "C:\Users\jonat_cau4\AppData\Local\nvm\v22.21.1;C:\Users\jonat_cau4\AppData\Roaming\npm;" + $env:Path
+$env:CLAUDE_BASE_URL = "http://127.0.0.1:3456"
+cd "C:\Users\jonat_cau4\.gemini\antigravity\scratch\background removal tool"
+claude
+```
+
+---
+
 ## Related Projects
 
 | Project | Relationship |

Dockerfile

@@ -9,11 +9,7 @@ ENV MPLCONFIGDIR=/app/cache
 ENV HOME=/home/user
 
 # Install system dependencies
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    libgl1-mesa-glx \
-    libglib2.0-0 \
-    && rm -rf /var/lib/apt/lists/*
+RUN apt-get update && apt-get install -y     build-essential     libgl1     libglib2.0-0     && rm -rf /var/lib/apt/lists/*
 
 # Set up a new user named "user" with UID 1000
 RUN useradd -m -u 1000 user

README.md

@@ -1,68 +1,23 @@
-# CutoutAI - Background Remover
+---
+title: CutoutAI Background Remover
+emoji: 🖼️
+colorFrom: blue
+colorTo: purple
+sdk: docker
+app_port: 7860
+pinned: false
+---
 
-An enhanced, flawless background removal tool built on BiRefNet for perfect t-shirt mockup preparation.
+# CutoutAI Background Removal Service
 
-## Features
+This space hosts a custom API for removing backgrounds from images using BiRefNet.
 
-- **Flawless Removal**: No patchy faces, artifacts, or edge issues
-- **Multi-Element Capture**: Captures bubbles, decorations, and all design elements
-- **API Ready**: Webhook, HTTP API, terminal commands
-- **Cloud Hosted**: Designed for n8n, Make, and cloud automation
-- **Mockup Quality**: Optimized for Printify t-shirt mockups
+## API Usage
 
-## Quick Start
+**Endpoint:** `/remove-background`
 
-```python
-from cutoutai import remove_background
+**Method:** `POST`
 
-# Basic usage
-result = remove_background("design.png")
-result.save("design_cutout.png")
+**Body:** `multipart/form-data` with an `image` file.
 
-# With enhanced settings for complex designs
-result = remove_background(
-    "design.png",
-    capture_all_elements=True,  # Get bubbles, small elements
-    edge_refinement=True,       # Smooth edges
-    matting_mode="general"      # or "portrait" for faces
-)
-```
-
-## API Endpoints
-
-| Endpoint | Method | Description |
-|----------|--------|-------------|
-| `/api/v1/remove` | POST | Remove background from image |
-| `/api/v1/batch` | POST | Process multiple images |
-| `/api/v1/health` | GET | Health check |
-| `/webhook` | POST | n8n/Make webhook endpoint |
-
-## Workflow Integration
-
-### n8n Webhook
-```
-POST https://your-host/webhook
-Content-Type: multipart/form-data
-
-image: <file>
-options: {"capture_all_elements": true}
-```
-
-### CLI
-```bash
-cutoutai process design.png --output cutout.png
-cutoutai batch ./designs/ --output ./cutouts/
-```
-
-## Quality Settings
-
-| Setting | Description | Use Case |
-|---------|-------------|----------|
-| `capture_all_elements` | Detect and preserve small elements (bubbles, decorations) | Complex designs |
-| `edge_refinement` | Smooth and feather edges | All mockups |
-| `matting_mode` | `general`, `portrait`, or `heavy` | Match content type |
-| `output_resolution` | Preserve or scale output | Printify requirements |
-
-## License
-
-MIT License - Built on BiRefNet
+**Response:** Returns the image PNG with transparent background.

api.py

@@ -12,6 +12,7 @@ import io
 import base64
 import time
 import logging
+import httpx
 from typing import Optional, Literal, Union
 from pathlib import Path
 from contextlib import asynccontextmanager
@@ -307,12 +308,13 @@ async def webhook_handler(
                 # Handle potential header in base64
                 if "," in image_base64:
                     image_base64 = image_base64.split(",")[1]
+                # Clean whitespace
+                image_base64 = "".join(image_base64.split())
                 img_data = base64.b64decode(image_base64)
                 logger.info("Using base64 image data")
             except Exception as e:
                 return JSONResponse({"success": False, "error": f"Invalid base64 data: {e}"}, status_code=400)
         elif image_url:
-            import httpx
             logger.info(f"Fetching image from URL: {image_url}")
             async with httpx.AsyncClient(timeout=30.0, follow_redirects=True) as client:
                 try:
@@ -341,21 +343,31 @@ async def webhook_handler(
             edge_radius=edge_radius,
             threshold=threshold,
             soft_threshold=soft_threshold,
+            return_mask=return_mask,
             output_format="base64"
         )
 
         processing_time = time.time() - start_time
 
-        response_data = {
-            "success": True,
-            "image_base64": result,
-            "model_used": model,
-            "processing_time_seconds": round(processing_time, 2)
-        }
+        if isinstance(result, dict):
+            response_data = {
+                "success": True,
+                "image_base64": result["result"],
+                "mask_base64": result["mask"],
+                "model_used": model,
+                "threshold_used": round(result.get("threshold_used", 0), 4),
+                "processing_time_seconds": round(processing_time, 2)
+            }
+        else:
+            response_data = {
+                "success": True,
+                "image_base64": result,
+                "model_used": model,
+                "processing_time_seconds": round(processing_time, 2)
+            }
 
         # If callback URL provided, send result there too
         if callback_url:
-            import httpx
             logger.info(f"Sending callback to: {callback_url}")
             async with httpx.AsyncClient(timeout=10.0) as client:
                 try:

requirements.txt

@@ -6,6 +6,7 @@ torchvision>=0.15.0
 transformers>=4.35.0
 timm>=0.9.0
 kornia>=0.7.0
+einops>=0.7.0
 
 # Image processing
 Pillow>=10.0.0