Deploy CU1-X to Hugging Face Spaces

- Multi-model AI pipeline (RF-DETR, CLIP, OCR, BLIP)
- Unified API architecture
- Gradio web interface
- Full model weights included via Git LFS
- Ready for production deployment

.gitattributes

@@ -1,35 +1,21 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
+# Git LFS configuration for large files
+# Required for Hugging Face Spaces deployment
+# Model weights
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
 *.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
 *.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
 *.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
+# Pickle files (model serialization)
 *.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+# Other large model formats
+*.h5 filter=lfs diff=lfs merge=lfs -text
 *.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
+# Archives
+*.tar.gz filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+# Large data files
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text

API_USAGE.md

@@ -0,0 +1,233 @@
+# 🔌 API Usage Guide - Hugging Face Spaces
+
+Sur Hugging Face Spaces, **seul Gradio est exposé publiquement**. L'API FastAPI (port 8000) n'est pas accessible depuis l'extérieur.
+
+**Mais Gradio expose automatiquement une API REST native!** 🎉
+
+## 📡 Accéder à l'API depuis l'extérieur
+
+### Option 1: API Gradio Native (Recommandé)
+
+Gradio expose automatiquement une API REST à l'endpoint `/api/predict`.
+
+#### Python avec `gradio_client`:
+
+```python
+from gradio_client import Client
+
+# Remplacez par votre Space URL
+client = Client("AI-DrivenTesting/CU1-X")
+
+# Appeler l'API
+result = client.predict(
+    "screenshot.png",           # image (filepath or PIL Image)
+    0.35,                       # confidence_threshold (float)
+    2,                          # thickness (int)
+    True,                       # enable_clip (bool)
+    True,                       # enable_ocr (bool)
+    False,                      # enable_blip (bool)
+    False,                      # ocr_only (bool)
+    "Only image & button",      # blip_scope (str)
+    False,                      # preprocess (bool)
+    "RF-DETR Optimized (Recommended)",  # preprocess_mode (str)
+    "standard",                 # preprocess_preset (str)
+    api_name="/predict"
+)
+
+# Résultat: (annotated_image, summary, detections_json)
+annotated_image, summary, detections_json = result
+print(detections_json)
+```
+
+#### REST API (curl):
+
+```bash
+# Pour un Space public
+curl -X POST "https://AI-DrivenTesting-CU1-X.hf.space/api/predict" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "data": [
+      "screenshot.png",  # Base64 encoded image or URL
+      0.35,
+      2,
+      true,
+      true,
+      false,
+      false,
+      "Only image & button",
+      false,
+      "RF-DETR Optimized (Recommended)",
+      "standard"
+    ]
+  }'
+```
+
+**Note:** Pour les images, vous devez soit:
+- Utiliser une URL publique vers l'image
+- Encoder l'image en base64
+- Utiliser `gradio_client` qui gère ça automatiquement
+
+#### REST API avec Python `requests`:
+
+```python
+import requests
+import base64
+from PIL import Image
+import io
+
+# Encoder l'image en base64
+def image_to_base64(image_path):
+    with open(image_path, "rb") as f:
+        return base64.b64encode(f.read()).decode()
+
+# Appeler l'API
+url = "https://AI-DrivenTesting-CU1-X.hf.space/api/predict"
+image_b64 = image_to_base64("screenshot.png")
+
+response = requests.post(
+    url,
+    json={
+        "data": [
+            f"data:image/png;base64,{image_b64}",
+            0.35,
+            2,
+            True,
+            True,
+            False,
+            False,
+            "Only image & button",
+            False,
+            "RF-DETR Optimized (Recommended)",
+            "standard"
+        ]
+    },
+    timeout=120
+)
+
+result = response.json()
+print(result)
+```
+
+### Option 2: API FastAPI (Interne uniquement)
+
+L'API FastAPI sur le port 8000 **n'est PAS accessible depuis l'extérieur** du Space HF.
+
+Elle fonctionne uniquement:
+- ✅ En local (`python app.py`)
+- ✅ Entre les processus internes du Space
+- ❌ **PAS depuis l'extérieur du Space**
+
+## 🔑 Authentification
+
+### Spaces Publics
+- Aucune authentification requise
+- API accessible directement
+
+### Spaces Privés
+- Nécessite un token Hugging Face
+- Ajoutez le header: `Authorization: Bearer <HF_TOKEN>`
+
+```python
+from gradio_client import Client
+
+client = Client(
+    "AI-DrivenTesting/CU1-X",
+    hf_token="your_hf_token_here"  # Pour les Spaces privés
+)
+```
+
+## 📊 Paramètres de l'API
+
+| Paramètre | Type | Description | Valeur par défaut |
+|-----------|------|-------------|-------------------|
+| `image` | file/str | Image à analyser | - |
+| `confidence_threshold` | float | Seuil de confiance (0.1-0.9) | 0.35 |
+| `thickness` | int | Épaisseur des boîtes (1-6) | 2 |
+| `enable_clip` | bool | Activer classification CLIP | False |
+| `enable_ocr` | bool | Activer extraction OCR | True |
+| `enable_blip` | bool | Activer descriptions BLIP | False |
+| `ocr_only` | bool | Mode OCR seul (skip detection) | False |
+| `blip_scope` | str | Portée BLIP ("Only image & button" ou "All elements") | "Only image & button" |
+| `preprocess` | bool | Activer preprocessing | False |
+| `preprocess_mode` | str | Mode preprocessing | "RF-DETR Optimized (Recommended)" |
+| `preprocess_preset` | str | Preset preprocessing | "standard" |
+
+## 📝 Format de Réponse
+
+```json
+{
+  "annotated_image": "base64_encoded_image",
+  "summary": "Markdown summary text",
+  "detections_json": {
+    "success": true,
+    "detections": [...],
+    "total_detections": 10,
+    "image_size": {"width": 1080, "height": 1920},
+    "parameters": {...},
+    "type_distribution": {...}
+  }
+}
+```
+
+## 🚀 Exemples Complets
+
+### Exemple 1: Détection Simple
+
+```python
+from gradio_client import Client
+
+client = Client("AI-DrivenTesting/CU1-X")
+
+result = client.predict(
+    "screenshot.png",
+    0.35, 2, False, True, False, False, "Only image & button",
+    False, "RF-DETR Optimized (Recommended)", "standard",
+    api_name="/predict"
+)
+
+annotated_image, summary, detections = result
+print(f"Found {detections['total_detections']} elements")
+```
+
+### Exemple 2: Détection Complète avec CLIP
+
+```python
+result = client.predict(
+    "screenshot.png",
+    0.35, 2, True, True, False, False, "Only image & button",
+    False, "RF-DETR Optimized (Recommended)", "standard",
+    api_name="/predict"
+)
+```
+
+### Exemple 3: OCR Seulement
+
+```python
+result = client.predict(
+    "screenshot.png",
+    0.35, 2, False, True, False, True, "Only image & button",
+    False, "RF-DETR Optimized (Recommended)", "standard",
+    api_name="/predict"
+)
+```
+
+## ⚠️ Limitations HF Spaces
+
+1. **Timeout:** 60 secondes par défaut (peut être augmenté dans Settings)
+2. **Mémoire:** Limite selon le hardware choisi
+3. **CPU/GPU:** Performance dépend du hardware sélectionné
+4. **API FastAPI:** Non accessible depuis l'extérieur
+
+## 🔗 Liens Utiles
+
+- [Gradio Client Docs](https://www.gradio.app/guides/getting-started-with-the-python-client)
+- [HF Spaces API Docs](https://huggingface.co/docs/hub/spaces-sdks-gradio#api-tab)
+- [HF Authentication](https://huggingface.co/docs/hub/security-tokens)
+
+## 💡 Tips
+
+- Utilisez `gradio_client` pour une meilleure gestion des images
+- Pour les gros fichiers, utilisez des URLs publiques
+- Activez le preprocessing pour des résultats cohérents sur différents devices
+- Mode OCR-only est plus rapide si vous voulez juste le texte
+

DEPLOYMENT.md

@@ -0,0 +1,164 @@
+# 🚀 Guide de Déploiement Hugging Face Spaces
+
+## 📋 Scripts Disponibles
+
+### 1. `check_hf_space.sh` - Vérification Pré-Déploiement
+
+Vérifie que tout est prêt avant de déployer:
+
+```bash
+./check_hf_space.sh
+```
+
+**Vérifie:**
+- ✅ Python version (>= 3.12)
+- ✅ Fichiers requis (app.py, requirements.txt, etc.)
+- ✅ Répertoires requis (detection/, api/, ui/, rfdetr/)
+- ✅ model.pth présent et tracké par Git LFS
+- ✅ Configuration Git LFS
+- ✅ Métadonnées README.md (frontmatter YAML)
+- ✅ requirements.txt complet
+- ✅ Syntaxe Python valide
+- ✅ Configuration Git et remote HF
+- ✅ Connexion Hugging Face CLI
+
+### 2. `deploy_hf_space.sh` - Déploiement Automatique
+
+Déploie automatiquement vers Hugging Face Spaces:
+
+```bash
+./deploy_hf_space.sh
+```
+
+**Fait automatiquement:**
+- ✅ Configure Git LFS pour model.pth
+- ✅ Vérifie/configure le remote HF
+- ✅ Vérifie la connexion HF
+- ✅ Met à jour requirements.txt si nécessaire
+- ✅ Stage tous les fichiers
+- ✅ Commit avec message descriptif
+- ✅ Push vers HF Spaces
+- ✅ Affiche l'URL du Space
+
+## 🎯 Workflow Recommandé
+
+### Étape 1: Vérifier
+
+```bash
+./check_hf_space.sh
+```
+
+**Résultat attendu:**
+```
+✅ All checks passed! Ready to deploy! ✨
+```
+
+### Étape 2: Déployer
+
+```bash
+./deploy_hf_space.sh
+```
+
+Le script va:
+1. Vérifier Git LFS
+2. Configurer le remote si nécessaire
+3. Vérifier la connexion HF
+4. Commit et push
+5. Afficher l'URL du Space
+
+### Étape 3: Suivre le Build
+
+Le script affichera l'URL de votre Space:
+```
+https://huggingface.co/spaces/YOUR_USERNAME/CU1-X
+```
+
+Cliquez sur **"Logs"** pour voir le build en direct.
+
+## 📡 Accéder à l'API
+
+Une fois déployé, votre API est accessible via:
+
+### API Gradio Native
+
+```python
+from gradio_client import Client
+
+client = Client("AI-DrivenTesting/CU1-X")
+result = client.predict(
+    "screenshot.png",
+    0.35, 2, True, True, False, False, "Only image & button",
+    False, "RF-DETR Optimized (Recommended)", "standard",
+    api_name="/predict"
+)
+```
+
+**Voir:** `API_USAGE.md` pour plus de détails
+
+## 🔧 Dépannage
+
+### Erreur: "Git LFS not installed"
+
+```bash
+# macOS
+brew install git-lfs
+git lfs install
+
+# Linux
+sudo apt install git-lfs
+git lfs install
+```
+
+### Erreur: "Not logged in"
+
+```bash
+hf login
+# OU
+huggingface-cli login
+```
+
+### Erreur: "model.pth not tracked by LFS"
+
+```bash
+git lfs track "*.pth"
+git add .gitattributes model.pth
+git commit -m "Add model with LFS"
+```
+
+### Erreur: "No remote configured"
+
+Le script `deploy_hf_space.sh` vous demandera de configurer le remote automatiquement.
+
+Ou manuellement:
+```bash
+git remote add origin https://huggingface.co/spaces/YOUR_USERNAME/CU1-X
+```
+
+## 📊 Checklist Rapide
+
+Avant de déployer:
+
+- [ ] `./check_hf_space.sh` passe tous les tests
+- [ ] Git LFS installé et configuré
+- [ ] Connecté à Hugging Face (`hf login`)
+- [ ] model.pth présent (~510MB)
+- [ ] Remote HF configuré
+
+Pour déployer:
+
+```bash
+./deploy_hf_space.sh
+```
+
+## 🎉 Après le Déploiement
+
+Votre Space sera accessible à:
+- **Interface Web:** `https://huggingface.co/spaces/YOUR_USERNAME/CU1-X`
+- **API:** `https://YOUR_USERNAME-CU1-X.hf.space/api/predict`
+
+**Temps de build:** 5-10 minutes (première fois)
+
+---
+
+**Besoin d'aide?** Consultez `API_USAGE.md` pour utiliser l'API!
+

QUICK_DEPLOY.md

@@ -0,0 +1,54 @@
+# ⚡ Déploiement Rapide - 2 Commandes
+
+## 🚀 Déployer en 2 Étapes
+
+### 1️⃣ Vérifier que tout est OK
+
+```bash
+./check_hf_space.sh
+```
+
+**Résultat attendu:** ✅ All checks passed!
+
+### 2️⃣ Déployer vers HF Spaces
+
+```bash
+./deploy_hf_space.sh
+```
+
+**C'est tout!** 🎉
+
+## 📡 Après le Déploiement
+
+Votre Space sera accessible à:
+- **Web UI:** https://huggingface.co/spaces/AI-DrivenTesting/CU1-X
+- **API:** https://AI-DrivenTesting-CU1-X.hf.space/api/predict
+
+## 🔌 Utiliser l'API
+
+```python
+from gradio_client import Client
+
+client = Client("AI-DrivenTesting/CU1-X")
+result = client.predict(
+    "screenshot.png",
+    0.35, 2, True, True, False, False, "Only image & button",
+    False, "RF-DETR Optimized (Recommended)", "standard",
+    api_name="/predict"
+)
+
+annotated_image, summary, detections = result
+print(detections)
+```
+
+**Voir:** `API_USAGE.md` pour plus d'exemples
+
+## ⏱️ Temps de Build
+
+- **Premier build:** 5-10 minutes
+- **Builds suivants:** 2-3 minutes
+
+---
+
+**C'est tout! Simple et rapide! 🚀**
+

README.md

@@ -1,12 +1,24 @@
 ---
-title: "CU1-X UI Element Detector"
-emoji: "🧠"
-colorFrom: "blue"
-colorTo: "purple"
-sdk: "gradio"
-sdk_version: "4.44.1"
-app_file: "app.py"
+title: CU1-X UI Element Detector
+emoji: 🧠
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 4.44.1
+app_file: app.py
 pinned: false
+python_version: 3.12
+models:
+  - Roboflow/RF-DETR
+  - openai/clip-vit-base-patch32
+  - Salesforce/blip-image-captioning-base
+tags:
+  - computer-vision
+  - object-detection
+  - ui-elements
+  - ocr
+  - transformers
+license: mit
 ---
 
 # CU-1 UI Element Detector
@@ -382,26 +394,44 @@ Detection performance depends on enabled features:
 
 ## 🤗 Deploying to Hugging Face Spaces
 
-### Quick Deploy
+### 🚀 Quick Deploy (2 Commands)
+
+**Option 1: Scripts Automatiques (Recommandé)**
+
+```bash
+# 1. Vérifier que tout est prêt
+./check_hf_space.sh
+
+# 2. Déployer automatiquement
+./deploy_hf_space.sh
+```
+
+**Option 2: Manuel**
 
 1. **Create a new Space** on Hugging Face
    - Choose "Gradio" as SDK
    - Select hardware (CPU or GPU)
 
-2. **Upload these files:**
+2. **Clone and push:**
    ```bash
-   app.py              # Unified entry point (API + UI)
-   app_api.py          # API server (launched by app.py)
-   requirements.txt    # Dependencies
-   detection/          # Detection modules
-   api/                # API endpoints
-   ui/                 # UI components
-   model.pth          # Model weights
-   README.md          # Documentation
+   git clone https://huggingface.co/spaces/YOUR_USERNAME/CU1-X
+   cd CU1-X
+   # Copy files from your project
+   git lfs install
+   git lfs track "*.pth"
+   git add .
+   git commit -m "Initial deployment"
+   git push origin main
    ```
 
 3. **Space will auto-deploy** - First run takes 5-10 minutes (model download)
 
+### 📚 Documentation
+
+- **[QUICK_DEPLOY.md](QUICK_DEPLOY.md)** - Guide ultra-rapide (2 commandes)
+- **[DEPLOYMENT.md](DEPLOYMENT.md)** - Guide détaillé complet
+- **[API_USAGE.md](API_USAGE.md)** - Comment utiliser l'API depuis l'extérieur
+
 ### Unified Architecture
 
 **NEW:** `app.py` now uses the same unified API architecture everywhere:

README_DEPLOYMENT.md

@@ -0,0 +1,81 @@
+# 📦 Résumé - Fichiers de Déploiement HF Spaces
+
+## ✅ Fichiers Créés
+
+### 🚀 Scripts de Déploiement
+
+1. **`check_hf_space.sh`** - Script de vérification pré-déploiement
+   - Vérifie 10 points critiques
+   - Affiche warnings et erreurs
+   - Exit code 0 si OK, 1 si erreurs
+
+2. **`deploy_hf_space.sh`** - Script de déploiement automatique
+   - Configure Git LFS automatiquement
+   - Vérifie/configure remote HF
+   - Commit et push vers HF Spaces
+   - Affiche l'URL du Space
+
+### 📚 Documentation
+
+1. **`API_USAGE.md`** - Guide complet d'utilisation de l'API
+   - Comment utiliser l'API Gradio native
+   - Exemples Python et REST
+   - Paramètres et format de réponse
+
+2. **`DEPLOYMENT.md`** - Guide de déploiement détaillé
+   - Workflow étape par étape
+   - Dépannage
+   - Checklist
+
+3. **`QUICK_DEPLOY.md`** - Guide ultra-rapide
+   - 2 commandes pour déployer
+   - Exemple API rapide
+
+### 📝 Configuration
+
+1. **`requirements-full.txt`** - Toutes les dépendances
+2. **`requirements.txt`** - Copie de requirements-full.txt (pour HF)
+3. **`.gitattributes`** - Configuration Git LFS pour *.pth
+4. **`README.md`** - Mis à jour avec métadonnées HF Spaces
+
+### 💡 Exemples
+
+1. **`examples/api_example.py`** - Exemple Python d'utilisation de l'API
+
+## 🎯 Utilisation
+
+### Vérifier avant déploiement:
+```bash
+./check_hf_space.sh
+```
+
+### Déployer:
+```bash
+./deploy_hf_space.sh
+```
+
+## 📊 État Actuel
+
+✅ **Tout est prêt!**
+
+- ✅ Tous les fichiers requis présents
+- ✅ model.pth tracké par Git LFS
+- ✅ Git LFS configuré
+- ✅ README.md avec métadonnées HF
+- ✅ requirements.txt complet
+- ✅ Remote HF configuré
+- ✅ Connecté à Hugging Face
+
+**Prochaine étape:** `./deploy_hf_space.sh`
+
+## 🔗 URLs Importantes
+
+Une fois déployé:
+- **Space:** https://huggingface.co/spaces/AI-DrivenTesting/CU1-X
+- **API:** https://AI-DrivenTesting-CU1-X.hf.space/api/predict
+- **Logs:** https://huggingface.co/spaces/AI-DrivenTesting/CU1-X/logs
+
+---
+
+**Tout est prêt pour le déploiement! 🚀**
+

app.py

@@ -141,11 +141,13 @@ def main():
         print(f"\n🎨 Starting Gradio UI on http://localhost:{UI_PORT}...\n")
         
         # Launch Gradio with automatic port fallback
+        # API is automatically exposed at /api/predict for HF Spaces
         try:
             demo.queue().launch(
                 server_name=UI_HOST,
                 server_port=UI_PORT,
-                share=False
+                share=False,
+                api_name="predict"  # Explicitly expose API endpoint
             )
         except OSError as e:
             if "Cannot find empty port" in str(e):

check_hf_space.sh

@@ -0,0 +1,286 @@
+#!/bin/bash
+# Script de vérification pour Hugging Face Spaces
+# Vérifie que tout est prêt pour le déploiement
+
+set -e
+
+# Colors
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+NC='\033[0m'
+
+print_info() { echo -e "${BLUE}ℹ️  $1${NC}"; }
+print_success() { echo -e "${GREEN}✅ $1${NC}"; }
+print_warning() { echo -e "${YELLOW}⚠️  $1${NC}"; }
+print_error() { echo -e "${RED}❌ $1${NC}"; }
+
+FAILURES=0
+WARNINGS=0
+
+echo ""
+print_info "🔍 Hugging Face Spaces Pre-Deployment Check"
+echo "================================================"
+echo ""
+
+# Test 1: Python version
+print_info "Test 1: Python version..."
+PYTHON_VERSION=$(python --version 2>&1 | awk '{print $2}')
+PYTHON_MAJOR=$(echo $PYTHON_VERSION | cut -d. -f1)
+PYTHON_MINOR=$(echo $PYTHON_VERSION | cut -d. -f2)
+
+if [ "$PYTHON_MAJOR" -ge 3 ] && [ "$PYTHON_MINOR" -ge 12 ]; then
+    print_success "Python $PYTHON_VERSION (>= 3.12)"
+else
+    print_warning "Python $PYTHON_VERSION (recommended: >= 3.12)"
+    WARNINGS=$((WARNINGS + 1))
+fi
+echo ""
+
+# Test 2: Required files
+print_info "Test 2: Required files..."
+REQUIRED_FILES=(
+    "app.py"
+    "app_api.py"
+    "app_ui.py"
+    "requirements.txt"
+    "README.md"
+    ".gitattributes"
+)
+
+for file in "${REQUIRED_FILES[@]}"; do
+    if [ -f "$file" ]; then
+        print_success "$file exists"
+    else
+        print_error "$file NOT FOUND"
+        FAILURES=$((FAILURES + 1))
+    fi
+done
+echo ""
+
+# Test 3: Required directories
+print_info "Test 3: Required directories..."
+REQUIRED_DIRS=(
+    "detection"
+    "api"
+    "ui"
+    "rfdetr"
+)
+
+for dir in "${REQUIRED_DIRS[@]}"; do
+    if [ -d "$dir" ]; then
+        print_success "$dir/ exists"
+    else
+        print_error "$dir/ NOT FOUND"
+        FAILURES=$((FAILURES + 1))
+    fi
+done
+echo ""
+
+# Test 4: model.pth
+print_info "Test 4: Model weights (model.pth)..."
+if [ -f "model.pth" ]; then
+    SIZE=$(du -h model.pth | cut -f1)
+    SIZE_BYTES=$(stat -f%z model.pth 2>/dev/null || stat -c%s model.pth)
+    
+    if [ $SIZE_BYTES -gt 100000000 ]; then  # > 100MB
+        print_success "model.pth exists ($SIZE)"
+        
+        # Check Git LFS
+        if git lfs ls-files | grep -q "model.pth"; then
+            print_success "model.pth tracked by Git LFS"
+        else
+            print_warning "model.pth NOT tracked by Git LFS (will fail on push)"
+            WARNINGS=$((WARNINGS + 1))
+        fi
+    else
+        print_warning "model.pth size: $SIZE (seems small, verify it's correct)"
+        WARNINGS=$((WARNINGS + 1))
+    fi
+else
+    print_error "model.pth NOT FOUND"
+    FAILURES=$((FAILURES + 1))
+fi
+echo ""
+
+# Test 5: Git LFS
+print_info "Test 5: Git LFS configuration..."
+if command -v git-lfs &> /dev/null; then
+    print_success "Git LFS installed"
+    
+    if git lfs env &> /dev/null; then
+        print_success "Git LFS initialized"
+    else
+        print_warning "Git LFS not initialized"
+        WARNINGS=$((WARNINGS + 1))
+    fi
+    
+    if grep -q "*.pth.*lfs" .gitattributes 2>/dev/null; then
+        print_success ".gitattributes tracks *.pth"
+    else
+        print_error ".gitattributes doesn't track *.pth"
+        FAILURES=$((FAILURES + 1))
+    fi
+else
+    print_error "Git LFS not installed!"
+    print_info "   Install: brew install git-lfs (macOS) or sudo apt install git-lfs (Linux)"
+    FAILURES=$((FAILURES + 1))
+fi
+echo ""
+
+# Test 6: README.md frontmatter
+print_info "Test 6: README.md frontmatter (HF Spaces metadata)..."
+if [ -f "README.md" ]; then
+    if head -n 1 README.md | grep -q "^---$"; then
+        print_success "README.md has YAML frontmatter"
+        
+        # Check key fields
+        if grep -q "^sdk: gradio" README.md; then
+            print_success "sdk: gradio found"
+        else
+            print_warning "sdk: gradio not found"
+            WARNINGS=$((WARNINGS + 1))
+        fi
+        
+        if grep -q "^app_file: app.py" README.md; then
+            print_success "app_file: app.py found"
+        else
+            print_warning "app_file: app.py not found"
+            WARNINGS=$((WARNINGS + 1))
+        fi
+        
+        if grep -q "^python_version:" README.md; then
+            print_success "python_version specified"
+        else
+            print_warning "python_version not specified"
+            WARNINGS=$((WARNINGS + 1))
+        fi
+    else
+        print_error "README.md missing YAML frontmatter"
+        FAILURES=$((FAILURES + 1))
+    fi
+else
+    print_error "README.md not found"
+    FAILURES=$((FAILURES + 1))
+fi
+echo ""
+
+# Test 7: requirements.txt
+print_info "Test 7: requirements.txt..."
+if [ -f "requirements.txt" ]; then
+    if [ -s "requirements.txt" ]; then
+        LINE_COUNT=$(wc -l < requirements.txt)
+        if [ $LINE_COUNT -gt 5 ]; then
+            print_success "requirements.txt looks complete ($LINE_COUNT lines)"
+        else
+            print_warning "requirements.txt seems minimal ($LINE_COUNT lines)"
+            WARNINGS=$((WARNINGS + 1))
+        fi
+        
+        # Check for critical dependencies
+        if grep -q "gradio" requirements.txt; then
+            print_success "gradio found in requirements.txt"
+        else
+            print_error "gradio NOT found in requirements.txt"
+            FAILURES=$((FAILURES + 1))
+        fi
+        
+        if grep -q "torch" requirements.txt; then
+            print_success "torch found in requirements.txt"
+        else
+            print_warning "torch not found (may be needed)"
+            WARNINGS=$((WARNINGS + 1))
+        fi
+    else
+        print_error "requirements.txt is empty"
+        FAILURES=$((FAILURES + 1))
+    fi
+else
+    print_error "requirements.txt not found"
+    FAILURES=$((FAILURES + 1))
+fi
+echo ""
+
+# Test 8: Python syntax
+print_info "Test 8: Python syntax validation..."
+for pyfile in app.py app_api.py app_ui.py; do
+    if [ -f "$pyfile" ]; then
+        if python -m py_compile "$pyfile" 2>/dev/null; then
+            print_success "$pyfile syntax valid"
+        else
+            print_error "$pyfile has syntax errors"
+            FAILURES=$((FAILURES + 1))
+        fi
+    fi
+done
+echo ""
+
+# Test 9: Git repository
+print_info "Test 9: Git repository..."
+if [ -d ".git" ]; then
+    print_success "Git repository initialized"
+    
+    # Check remote
+    if git remote -v | grep -q "huggingface.co"; then
+        REMOTE_URL=$(git remote get-url origin 2>/dev/null || echo "unknown")
+        print_success "HF Space remote configured: $REMOTE_URL"
+    else
+        print_warning "No Hugging Face remote configured"
+        WARNINGS=$((WARNINGS + 1))
+    fi
+    
+    # Check for uncommitted changes
+    if [ -n "$(git status --porcelain)" ]; then
+        print_warning "Uncommitted changes detected"
+        WARNINGS=$((WARNINGS + 1))
+    else
+        print_success "All changes committed"
+    fi
+else
+    print_warning "Not a git repository (will need git init)"
+    WARNINGS=$((WARNINGS + 1))
+fi
+echo ""
+
+# Test 10: Hugging Face CLI
+print_info "Test 10: Hugging Face CLI..."
+if command -v huggingface-cli &> /dev/null || command -v hf &> /dev/null; then
+    print_success "Hugging Face CLI installed"
+    
+    # Check login
+    if huggingface-cli whoami &> /dev/null 2>&1 || hf auth whoami &> /dev/null 2>&1; then
+        USERNAME=$(huggingface-cli whoami 2>/dev/null || hf auth whoami 2>/dev/null | head -n1)
+        print_success "Logged in as: $USERNAME"
+    else
+        print_warning "Not logged in to Hugging Face"
+        print_info "   Run: huggingface-cli login or hf login"
+        WARNINGS=$((WARNINGS + 1))
+    fi
+else
+    print_warning "Hugging Face CLI not installed"
+    print_info "   Install: pip install huggingface-hub"
+    WARNINGS=$((WARNINGS + 1))
+fi
+echo ""
+
+# Summary
+echo "================================================"
+if [ $FAILURES -eq 0 ] && [ $WARNINGS -eq 0 ]; then
+    print_success "All checks passed! Ready to deploy! ✨"
+    echo ""
+    print_info "Next step: Run ./deploy_hf_space.sh"
+    exit 0
+elif [ $FAILURES -eq 0 ]; then
+    print_warning "$WARNINGS warning(s) found"
+    echo ""
+    print_info "You can proceed, but consider fixing warnings"
+    print_info "Next step: Run ./deploy_hf_space.sh"
+    exit 0
+else
+    print_error "$FAILURES critical error(s) and $WARNINGS warning(s)"
+    echo ""
+    print_info "Please fix the errors before deploying"
+    exit 1
+fi
+

deploy_hf_space.sh

@@ -0,0 +1,210 @@
+#!/bin/bash
+# Script de déploiement pour Hugging Face Spaces
+# Build et push le Space vers Hugging Face
+
+set -e
+
+# Colors
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+NC='\033[0m'
+
+print_info() { echo -e "${BLUE}ℹ️  $1${NC}"; }
+print_success() { echo -e "${GREEN}✅ $1${NC}"; }
+print_warning() { echo -e "${YELLOW}⚠️  $1${NC}"; }
+print_error() { echo -e "${RED}❌ $1${NC}"; }
+
+echo ""
+print_info "🚀 Deploying CU1-X to Hugging Face Spaces"
+echo "================================================"
+echo ""
+
+# Check if we're in a git repo
+if [ ! -d ".git" ]; then
+    print_error "Not a git repository!"
+    print_info "Initializing git repository..."
+    git init
+    print_success "Git repository initialized"
+fi
+
+# Check Git LFS
+print_info "Configuring Git LFS..."
+if ! command -v git-lfs &> /dev/null; then
+    print_error "Git LFS not installed!"
+    print_info "Install with: brew install git-lfs (macOS) or sudo apt install git-lfs (Linux)"
+    exit 1
+fi
+
+git lfs install > /dev/null 2>&1 || true
+
+# Ensure model.pth is tracked
+if [ -f "model.pth" ]; then
+    if ! git lfs ls-files | grep -q "model.pth"; then
+        print_info "Adding model.pth to Git LFS..."
+        git lfs track "*.pth"
+        git add .gitattributes
+        print_success "model.pth configured for Git LFS"
+    else
+        print_success "model.pth already tracked by Git LFS"
+    fi
+else
+    print_error "model.pth not found!"
+    exit 1
+fi
+
+# Check HF remote
+print_info "Checking Hugging Face remote..."
+if git remote | grep -q "origin"; then
+    REMOTE_URL=$(git remote get-url origin 2>/dev/null || echo "")
+    if echo "$REMOTE_URL" | grep -q "huggingface.co"; then
+        print_success "HF Space remote configured: $REMOTE_URL"
+        SPACE_URL=$(echo "$REMOTE_URL" | sed -E 's|.*spaces/([^/]+)/([^/]+).*|\1/\2|')
+        print_info "Space URL: https://huggingface.co/spaces/$SPACE_URL"
+    else
+        print_warning "Remote exists but doesn't look like HF Space"
+        print_info "Current remote: $REMOTE_URL"
+    fi
+else
+    print_warning "No remote configured"
+    print_info "You'll need to add a remote:"
+    print_info "  git remote add origin https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME"
+    read -p "Do you want to configure it now? (y/n) " -n 1 -r
+    echo
+    if [[ $REPLY =~ ^[Yy]$ ]]; then
+        read -p "Enter your HF username: " HF_USERNAME
+        read -p "Enter your Space name: " SPACE_NAME
+        git remote add origin "https://huggingface.co/spaces/$HF_USERNAME/$SPACE_NAME"
+        print_success "Remote configured"
+        SPACE_URL="$HF_USERNAME/$SPACE_NAME"
+    else
+        print_error "Cannot deploy without remote"
+        exit 1
+    fi
+fi
+
+# Check login
+print_info "Checking Hugging Face login..."
+if command -v hf &> /dev/null; then
+    if hf auth whoami &> /dev/null 2>&1; then
+        USERNAME=$(hf auth whoami 2>/dev/null | head -n1)
+        print_success "Logged in as: $USERNAME"
+    else
+        print_warning "Not logged in"
+        print_info "Logging in..."
+        hf login
+    fi
+elif command -v huggingface-cli &> /dev/null; then
+    if huggingface-cli whoami &> /dev/null 2>&1; then
+        USERNAME=$(huggingface-cli whoami 2>/dev/null | head -n1)
+        print_success "Logged in as: $USERNAME"
+    else
+        print_warning "Not logged in"
+        print_info "Logging in..."
+        huggingface-cli login
+    fi
+else
+    print_error "Hugging Face CLI not found!"
+    print_info "Install: pip install huggingface-hub"
+    exit 1
+fi
+
+# Ensure requirements.txt is complete
+print_info "Checking requirements.txt..."
+if [ -f "requirements-full.txt" ] && [ -f "requirements.txt" ]; then
+    FULL_LINES=$(wc -l < requirements-full.txt)
+    CURRENT_LINES=$(wc -l < requirements.txt)
+    
+    if [ $CURRENT_LINES -lt $FULL_LINES ]; then
+        print_warning "requirements.txt seems incomplete"
+        read -p "Use requirements-full.txt? (y/n) " -n 1 -r
+        echo
+        if [[ $REPLY =~ ^[Yy]$ ]]; then
+            cp requirements-full.txt requirements.txt
+            print_success "Updated requirements.txt from requirements-full.txt"
+        fi
+    fi
+fi
+
+# Stage all files
+print_info "Staging files..."
+git add .
+print_success "Files staged"
+
+# Check if there are changes
+if [ -z "$(git status --porcelain)" ]; then
+    print_warning "No changes to commit"
+    print_info "Everything is already up to date"
+else
+    # Show what will be committed
+    print_info "Changes to commit:"
+    git status --short
+    
+    # Commit
+    print_info "Creating commit..."
+    COMMIT_MSG="Deploy CU1-X to Hugging Face Spaces
+
+- Multi-model AI pipeline (RF-DETR, CLIP, OCR, BLIP)
+- Unified API architecture
+- Gradio web interface
+- Full model weights included via Git LFS
+- Ready for production deployment"
+    
+    git commit -m "$COMMIT_MSG" || {
+        print_error "Commit failed"
+        exit 1
+    }
+    print_success "Changes committed"
+fi
+
+# Push to Hugging Face
+print_info "Pushing to Hugging Face Spaces..."
+print_warning "This may take several minutes (model.pth is 510MB)..."
+echo ""
+
+BRANCH=$(git branch --show-current 2>/dev/null || echo "main")
+
+if git push -u origin "$BRANCH" 2>&1 | tee /tmp/hf_push.log; then
+    print_success "Push completed successfully!"
+    echo ""
+    echo "================================================"
+    print_success "🎉 Deployment Successful!"
+    echo "================================================"
+    echo ""
+    
+    if [ -n "$SPACE_URL" ]; then
+        print_info "Your Space is deploying at:"
+        echo "   https://huggingface.co/spaces/$SPACE_URL"
+        echo ""
+        print_info "Build progress:"
+        echo "   https://huggingface.co/spaces/$SPACE_URL/logs"
+        echo ""
+        print_info "Once deployed, your app will be at:"
+        echo "   https://huggingface.co/spaces/$SPACE_URL"
+        echo ""
+        print_info "API endpoint:"
+        echo "   https://$SPACE_URL.hf.space/api/predict"
+        echo ""
+    fi
+    
+    print_warning "First build may take 5-10 minutes"
+    print_info "HF Spaces will automatically:"
+    print_info "  - Install dependencies from requirements.txt"
+    print_info "  - Download models (CLIP, BLIP, EasyOCR)"
+    print_info "  - Start app.py"
+    print_info "  - Expose Gradio interface and API"
+    echo ""
+    print_success "All done! 🎉"
+else
+    print_error "Push failed!"
+    echo ""
+    print_info "Common issues:"
+    print_info "1. Authentication failed: Run 'hf login' or 'huggingface-cli login'"
+    print_info "2. Git LFS error: Ensure Git LFS is installed and model.pth is tracked"
+    print_info "3. Network error: Check your internet connection"
+    echo ""
+    print_info "Check the error above for details"
+    exit 1
+fi
+

examples/api_example.py

@@ -0,0 +1,94 @@
+"""
+Example: Using CU1-X API from Hugging Face Space
+
+This example shows how to call the CU1-X API deployed on Hugging Face Spaces.
+"""
+
+from gradio_client import Client
+import json
+
+# Configuration
+SPACE_URL = "AI-DrivenTesting/CU1-X"  # Remplacez par votre Space URL
+
+def detect_ui_elements(image_path: str):
+    """
+    Détecte les éléments UI dans une image via l'API HF Space
+    
+    Args:
+        image_path: Chemin vers l'image à analyser
+        
+    Returns:
+        Tuple (annotated_image, summary, detections_json)
+    """
+    # Créer le client Gradio
+    client = Client(SPACE_URL)
+    
+    # Appeler l'API
+    result = client.predict(
+        image_path,                          # image
+        0.35,                                # confidence_threshold
+        2,                                   # thickness
+        True,                                # enable_clip (classification)
+        True,                                # enable_ocr (extraction texte)
+        False,                               # enable_blip (descriptions)
+        False,                               # ocr_only
+        "Only image & button",              # blip_scope
+        False,                               # preprocess
+        "RF-DETR Optimized (Recommended)",  # preprocess_mode
+        "standard",                          # preprocess_preset
+        api_name="/predict"
+    )
+    
+    # Déballer les résultats
+    annotated_image, summary, detections_json = result
+    
+    return annotated_image, summary, detections_json
+
+
+def main():
+    """Exemple d'utilisation"""
+    
+    print("🚀 CU1-X API Example")
+    print("=" * 50)
+    
+    # Chemin vers votre image de test
+    test_image = "screenshot.png"  # Remplacez par votre image
+    
+    try:
+        print(f"\n📤 Uploading image: {test_image}")
+        print("⏳ Processing... (this may take 30-60 seconds)")
+        
+        # Appeler l'API
+        annotated_image, summary, detections = detect_ui_elements(test_image)
+        
+        # Afficher les résultats
+        print("\n✅ Detection completed!")
+        print("\n📊 Summary:")
+        print(summary)
+        
+        print("\n🔍 Detections:")
+        if isinstance(detections, str):
+            detections = json.loads(detections)
+        
+        print(f"   Total: {detections.get('total_detections', 0)} elements")
+        
+        if 'type_distribution' in detections:
+            print("\n📈 Type Distribution:")
+            for elem_type, count in detections['type_distribution'].items():
+                print(f"   {elem_type}: {count}")
+        
+        print("\n💾 Saving annotated image...")
+        # annotated_image est un fichier temporaire, vous pouvez le copier
+        print(f"   Annotated image saved at: {annotated_image}")
+        
+    except Exception as e:
+        print(f"\n❌ Error: {e}")
+        print("\nTroubleshooting:")
+        print("1. Vérifiez que votre Space est déployé et en ligne")
+        print("2. Vérifiez que SPACE_URL est correct")
+        print("3. Assurez-vous d'avoir installé: pip install gradio_client")
+
+
+if __name__ == "__main__":
+    main()
+

requirements-full.txt

@@ -0,0 +1,40 @@
+# Full requirements for CU1-X UI Element Detector
+# Use this file for deployment to Hugging Face Spaces or production
+
+# Core dependencies
+gradio[oauth]==4.44.1
+
+# Deep Learning frameworks
+torch==2.4.1
+torchvision==0.19.1
+
+# Computer Vision & Image Processing
+opencv-python-headless==4.10.0.84
+pillow==10.4.0
+numpy==1.26.4
+supervision==0.23.0
+
+# OCR & Text Recognition
+easyocr==1.7.1
+
+# Transformers & AI Models
+transformers==4.44.2
+
+# RF-DETR Detection Model
+rfdetr==1.0.4
+
+# API Framework
+fastapi==0.115.0
+uvicorn[standard]==0.30.6
+
+# HTTP Clients
+requests==2.32.3
+aiohttp==3.10.5
+
+# Testing
+pytest==8.3.3
+
+# Utilities
+python-multipart==0.0.9  # For FastAPI file uploads
+python-dotenv==1.0.1     # For environment variables
+

requirements.txt

@@ -1 +1,40 @@
-gradio[oauth]==4.44.1
+# Full requirements for CU1-X UI Element Detector
+# Use this file for deployment to Hugging Face Spaces or production
+
+# Core dependencies
+gradio[oauth]==4.44.1
+
+# Deep Learning frameworks
+torch==2.4.1
+torchvision==0.19.1
+
+# Computer Vision & Image Processing
+opencv-python-headless==4.10.0.84
+pillow==10.4.0
+numpy==1.26.4
+supervision==0.23.0
+
+# OCR & Text Recognition
+easyocr==1.7.1
+
+# Transformers & AI Models
+transformers==4.44.2
+
+# RF-DETR Detection Model
+rfdetr==1.0.4
+
+# API Framework
+fastapi==0.115.0
+uvicorn[standard]==0.30.6
+
+# HTTP Clients
+requests==2.32.3
+aiohttp==3.10.5
+
+# Testing
+pytest==8.3.3
+
+# Utilities
+python-multipart==0.0.9  # For FastAPI file uploads
+python-dotenv==1.0.1     # For environment variables
+