fix mail final

app.py

@@ -36,63 +36,21 @@ except ImportError as e:
     print(f"⚠️ Detectron2 not available: {e}")
     DETECTRON2_AVAILABLE = False
 
-def check_model_files():
-    """Check availability of model files locally and remotely"""
-    model_status = {}
-    
-    print("\n🔍 Checking model files...")
-    
-    # Check damage detection model (Detectron2)
-    if os.path.exists(DEFAULT_DAMAGE_MODEL_PATH):
-        file_size = os.path.getsize(DEFAULT_DAMAGE_MODEL_PATH) / (1024 * 1024)  # Size in MB
-        print(f"✅ Damage Model: Available ({file_size:.2f} MB) at {DEFAULT_DAMAGE_MODEL_PATH}")
-        model_status['damage_model'] = {'available': True, 'size': file_size, 'path': DEFAULT_DAMAGE_MODEL_PATH}
-    else:
-        print(f"❌ Damage Model: Not found at {DEFAULT_DAMAGE_MODEL_PATH}")
-        model_status['damage_model'] = {'available': False, 'path': DEFAULT_DAMAGE_MODEL_PATH}
-    
-    # Check deepfake detection model (ViT) - Local first
-    local_deepfake_path = None
-    if os.path.exists(DEFAULT_DEEPFAKE_MODEL_PATH):
-        file_size = os.path.getsize(DEFAULT_DEEPFAKE_MODEL_PATH) / (1024 * 1024)  # Size in MB
-        print(f"✅ Deepfake Model: Available locally ({file_size:.2f} MB) at {DEFAULT_DEEPFAKE_MODEL_PATH}")
-        local_deepfake_path = DEFAULT_DEEPFAKE_MODEL_PATH
-        model_status['deepfake_model'] = {'available': True, 'size': file_size, 'path': local_deepfake_path, 'source': 'local'}
-    else:
-        print(f"⚠️ Deepfake Model: Not found locally at {DEFAULT_DEEPFAKE_MODEL_PATH}")
-        model_status['deepfake_model'] = {'available': False, 'path': DEFAULT_DEEPFAKE_MODEL_PATH, 'source': 'local'}
-    
-    return model_status, local_deepfake_path
-
-# Check local models first
-model_status, local_deepfake_model_path = check_model_files()
-
-# Try to download deepfake model from Hugging Face if not available locally
+# Try to download model from Hugging Face
 huggingface_model_path = None
-if not local_deepfake_model_path:
-    try:
-        print("🔄 Attempting to download deepfake model from Hugging Face...")
-        from huggingface_hub import hf_hub_download
-        huggingface_model_path = hf_hub_download(
-            repo_id="Askhedi/Car_damage_fraud_detector",
-            filename="vit_deepfake_final.pth",
-            token=os.getenv('HF_TOKEN')
-        )
-        print(f"✅ Deepfake model downloaded from Hugging Face: {huggingface_model_path}")
-        # Update model status
-        if huggingface_model_path and os.path.exists(huggingface_model_path):
-            file_size = os.path.getsize(huggingface_model_path) / (1024 * 1024)
-            model_status['deepfake_model'] = {'available': True, 'size': file_size, 'path': huggingface_model_path, 'source': 'huggingface'}
-    except Exception as e:
-        print(f"⚠️ Could not download model from Hugging Face: {e}")
-        print("🔄 Will use demo mode with simulated results")
-        huggingface_model_path = None
-else:
-    print("✅ Using local deepfake model")
-    huggingface_model_path = local_deepfake_model_path
-
-# Make model_status global for access in functions
-globals()['model_status'] = model_status
+try:
+    from huggingface_hub import hf_hub_download
+    # Try to download from your repository
+    huggingface_model_path = hf_hub_download(
+        repo_id="Askhedi/Car_damage_fraud_detector",
+        filename="vit_deepfake_final.pth",
+        token=os.getenv('HF_TOKEN')
+    )
+    print(f"✅ Model downloaded from Hugging Face: {huggingface_model_path}")
+except Exception as e:
+    print(f"⚠️ Could not download model from Hugging Face: {e}")
+    print("🔄 Will use demo mode with simulated results")
+    huggingface_model_path = None
 
 # Define model paths
 DEFAULT_DAMAGE_MODEL_PATH = "./output/model_final.pth"
@@ -766,7 +724,6 @@ def load_vit_deepfake_model(model_path, device):
 
 def process_image(input_image, damage_threshold, deepfake_threshold, skip_damage, device_str, usage_count, recipient_email):
     """Main processing function with Mailjet email integration"""
-    global model_status  # Access global model status
     
     # Handle usage count
     if usage_count is None:
@@ -822,37 +779,20 @@ def process_image(input_image, damage_threshold, deepfake_threshold, skip_damage
     progress_info.append(f"🖥️ Using device: {device}")
     
     # Initialize models
-    damage_detector = None
+    deepfake_model_path = huggingface_model_path or DEFAULT_DEEPFAKE_MODEL_PATH
     deepfake_model = None
     demo_mode = False
     
-    # Setup damage detector if available and not skipped
-    if not skip_damage and model_status['damage_model']['available'] and DETECTRON2_AVAILABLE:
-        progress_info.append("🤖 Loading damage detection model...")
-        damage_detector, _ = setup_damage_detector(model_status['damage_model']['path'], float(damage_threshold))
-        if damage_detector:
-            progress_info.append("✅ Damage detection model loaded successfully")
-        else:
-            progress_info.append("❌ Failed to load damage detection model")
-    elif skip_damage:
-        progress_info.append("⚠️ Damage detection skipped (user setting)")
-    else:
-        if not DETECTRON2_AVAILABLE:
-            progress_info.append("⚠️ Detectron2 not available - skipping damage detection")
-        else:
-            progress_info.append("❌ Damage detection model not found")
-    
-    # Setup deepfake detector
-    if model_status['deepfake_model']['available']:
-        progress_info.append(f"🤖 Loading deepfake model from {model_status['deepfake_model']['source']}...")
-        deepfake_model = load_vit_deepfake_model(model_status['deepfake_model']['path'], device)
+    if deepfake_model_path and os.path.exists(deepfake_model_path):
+        progress_info.append("🤖 Loading AI model...")
+        deepfake_model = load_vit_deepfake_model(deepfake_model_path, device)
         if deepfake_model:
-            progress_info.append("✅ Deepfake detection model loaded successfully")
+            progress_info.append("✅ AI model loaded successfully")
         else:
-            progress_info.append("❌ Failed to load deepfake model - using demo mode")
+            progress_info.append("❌ Failed to load AI model - using demo mode")
             demo_mode = True
     else:
-        progress_info.append("⚠️ Deepfake model not found - using demo mode")
+        progress_info.append("⚠️ AI model not found - using demo mode")
         demo_mode = True
     
     # Analyze the image
@@ -971,9 +911,6 @@ def process_image(input_image, damage_threshold, deepfake_threshold, skip_damage
 
 def create_gradio_interface():
     """Create Gradio interface with Mailjet integration"""
-    # Make model_status accessible to the interface
-    global model_status
-    
     theme = gr.themes.Soft(primary_hue="blue", secondary_hue="orange")
     
     with gr.Blocks(title="Car Damage Fraud Detector - Mailjet Edition", theme=theme) as app:
@@ -991,26 +928,12 @@ def create_gradio_interface():
         """)
         
         # Model and Mailjet status
-        damage_status = "✅ Available" if model_status['damage_model']['available'] else "❌ Not found"
-        deepfake_status = "✅ Available" if model_status['deepfake_model']['available'] else "🧪 Demo mode"
-        detectron2_status = "✅ Available" if DETECTRON2_AVAILABLE else "❌ Not installed"
-        
-        if model_status['deepfake_model']['available']:
-            deepfake_source = f"({model_status['deepfake_model']['source']})"
-            deepfake_status += f" {deepfake_source}"
-        
-        mailjet_status = "✅ Configured" if (MAILJET_CONFIG['API_KEY'] and MAILJET_CONFIG['SECRET_KEY']) else "⚠️ Not configured"
+        model_status = "✅ AI Model Ready" if huggingface_model_path and os.path.exists(huggingface_model_path) else "🧪 Demo Mode (simulated results)"
         
-        gr.Markdown(f"""
-        **📊 System Status:**
-        - **Detectron2:** {detectron2_status}
-        - **Damage Model:** {damage_status}
-        - **Deepfake Model:** {deepfake_status}  
-        - **Mailjet API:** {mailjet_status}
-        """)
-        
-        if not model_status['deepfake_model']['available']:
-            gr.Markdown("⚠️ **Demo Mode Active**: Simulated results will be generated for demonstration purposes.")
+        if MAILJET_CONFIG['API_KEY'] and MAILJET_CONFIG['SECRET_KEY']:
+            gr.Markdown(f"**✅ Mailjet API configured** | **{model_status}**")
+        else:
+            gr.Markdown(f"**⚠️ Mailjet API not configured** | **{model_status}**")
         
         usage_counter = gr.State(0)
 
@@ -1070,81 +993,6 @@ def create_gradio_interface():
                         )
                         download_info = gr.Markdown("**Complete analysis package will appear here after processing...**")
 
-        with gr.Tab("🔧 System Status"):
-            gr.Markdown("## 📊 Model and System Status")
-            
-            def create_model_status():
-                status_info = []
-                
-                # Detectron2 status
-                if DETECTRON2_AVAILABLE:
-                    status_info.append("✅ **Detectron2**: Available for damage detection")
-                else:
-                    status_info.append("❌ **Detectron2**: Not installed (pip install detectron2)")
-                
-                # Damage model status
-                if model_status['damage_model']['available']:
-                    size_mb = model_status['damage_model']['size']
-                    path = model_status['damage_model']['path']
-                    status_info.append(f"✅ **Damage Model**: Available ({size_mb:.2f} MB)")
-                    status_info.append(f"   📁 Path: `{path}`")
-                else:
-                    path = model_status['damage_model']['path']
-                    status_info.append(f"❌ **Damage Model**: Not found")
-                    status_info.append(f"   📁 Expected path: `{path}`")
-                
-                # Deepfake model status
-                if model_status['deepfake_model']['available']:
-                    size_mb = model_status['deepfake_model']['size']
-                    path = model_status['deepfake_model']['path']
-                    source = model_status['deepfake_model']['source']
-                    status_info.append(f"✅ **Deepfake Model**: Available ({size_mb:.2f} MB) - {source}")
-                    status_info.append(f"   📁 Path: `{path}`")
-                else:
-                    path = model_status['deepfake_model']['path']
-                    status_info.append(f"🧪 **Deepfake Model**: Using demo mode")
-                    status_info.append(f"   📁 Expected local path: `{path}`")
-                    status_info.append(f"   🌐 Remote: Hugging Face repository not accessible")
-                
-                # Mailjet status
-                if MAILJET_CONFIG['API_KEY'] and MAILJET_CONFIG['SECRET_KEY']:
-                    status_info.append(f"✅ **Mailjet API**: Configured")
-                    status_info.append(f"   📧 From: {MAILJET_CONFIG['FROM_NAME']} <{MAILJET_CONFIG['FROM_EMAIL']}>")
-                    status_info.append(f"   🔑 API Key: {MAILJET_CONFIG['API_KEY'][:8]}...{MAILJET_CONFIG['API_KEY'][-4:]}")
-                else:
-                    status_info.append(f"⚠️ **Mailjet API**: Not configured")
-                    status_info.append(f"   📧 Email delivery unavailable")
-                
-                return "\n".join(status_info)
-            
-            gr.Markdown(create_model_status())
-            
-            gr.Markdown("""
-            ## 🔧 Setup Instructions
-            
-            ### For Damage Detection (Optional):
-            1. **Install Detectron2**: `pip install detectron2`
-            2. **Place model file** at: `./output/model_final.pth`
-            
-            ### For AI Deepfake Detection:
-            1. **Option 1 - Local**: Place model at `./output/vit_deepfake_final.pth`
-            2. **Option 2 - Hugging Face**: Configure `HF_TOKEN` environment variable
-            
-            ### For Email Delivery:
-            1. **Get Mailjet credentials** from https://www.mailjet.com/
-            2. **Set environment variables**:
-               ```
-               MAILJET_API_KEY=your_api_key
-               MAILJET_SECRET_KEY=your_secret_key
-               FROM_EMAIL=your-email@domain.com
-               ```
-            
-            ## 📦 File Locations Expected:
-            - **Damage Model**: `./output/model_final.pth`
-            - **Deepfake Model**: `./output/vit_deepfake_final.pth`
-            - **Config**: Environment variables for Mailjet
-            """)
-
         with gr.Tab("📧 Mailjet Setup"):
             gr.Markdown("""
             ## 🔧 Mailjet Configuration
@@ -1320,35 +1168,13 @@ def create_gradio_interface():
 
 if __name__ == "__main__":
     print("🚀 Starting Car Damage Fraud Detector - Mailjet Edition...")
+    print(f"✅ HuggingFace model: {'Available' if huggingface_model_path else 'Not available'}")
     
-    # Display comprehensive system status
-    print("\n📊 SYSTEM STATUS SUMMARY:")
-    print("=" * 50)
-    
-    # Detectron2 status
-    detectron2_status = "✅ Available" if DETECTRON2_AVAILABLE else "❌ Not installed"
-    print(f"🔧 Detectron2: {detectron2_status}")
-    
-    # Models status
-    if model_status['damage_model']['available']:
-        size_mb = model_status['damage_model']['size']
-        print(f"🎯 Damage Model: ✅ Available ({size_mb:.2f} MB)")
-    else:
-        print(f"🎯 Damage Model: ❌ Not found at {DEFAULT_DAMAGE_MODEL_PATH}")
-    
-    if model_status['deepfake_model']['available']:
-        size_mb = model_status['deepfake_model']['size']
-        source = model_status['deepfake_model']['source']
-        print(f"🤖 Deepfake Model: ✅ Available ({size_mb:.2f} MB) - {source}")
-    else:
-        print(f"🤖 Deepfake Model: 🧪 Demo mode (model not available)")
-    
-    # Mailjet status  
+    # Test Mailjet configuration
     if MAILJET_CONFIG['API_KEY'] and MAILJET_CONFIG['SECRET_KEY']:
-        print(f"📧 Mailjet API: ✅ Configured")
+        print("📧 Mailjet API: ✅ Configured")
         print(f"📧 From: {MAILJET_CONFIG['FROM_NAME']} <{MAILJET_CONFIG['FROM_EMAIL']}>")
-        
-        # Test Mailjet connection
+        # Test connection at startup
         if test_mailjet_connection():
             print("📧 Mailjet: ✅ Connection test successful")
         else:
@@ -1356,16 +1182,6 @@ if __name__ == "__main__":
     else:
         print("📧 Mailjet API: ❌ Not configured")
     
-    print("=" * 50)
-    
-    # Display operational mode
-    if model_status['deepfake_model']['available']:
-        print("🎯 OPERATIONAL MODE: Full AI Analysis")
-    else:
-        print("🧪 OPERATIONAL MODE: Demo Mode (simulated results)")
-    
-    print("🌐 Starting Gradio interface...")
-    
     app = create_gradio_interface()
     app.launch(
         share=False,