V1.1

app.py

@@ -581,60 +581,8 @@ def create_gradio_interface():
         gr.Markdown("## Examples")
         gr.Markdown("Note: Examples will use the default models if you don't specify custom paths.")
             
-    return app        gr.Markdown("# Car Damage Detection & Deepfake Verification")
-        gr.Markdown("Upload an image to detect car damage and check if it's a deepfake")
-        
-        with gr.Tab("Basic Interface"):
-            with gr.Row():
-                with gr.Column(scale=1):
-                    input_image = gr.Image(type="numpy", label="Input Image")
-                    
-                    # Simple controls
-                    skip_damage = gr.Checkbox(label="Skip Damage Detection", value=False)
-                    damage_threshold = gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.05, 
-                                               label="Damage Detection Threshold")
-                    deepfake_threshold = gr.Slider(minimum=0.1, maximum=1.0, value=0.5, step=0.05,
-                                                 label="Deepfake Detection Threshold")
-                    device = gr.Dropdown(choices=["auto", "cuda", "cpu", "mps"], value="auto", 
-                                        label="Computation Device")
-                    
-                    process_btn = gr.Button("Process Image", variant="primary")
-                    
-                with gr.Column(scale=1):
-                    output_image = gr.Image(type="numpy", label="Result")
-                    output_text = gr.Textbox(label="Detection Results", lines=10)
-            
-        with gr.Tab("Advanced Settings"):
-            with gr.Row():
-                with gr.Column():
-                    damage_model_path = gr.Textbox(label="Damage Model Path", 
-                                                 placeholder="Path to damage detection model (.pth)")
-                    deepfake_model_path = gr.Textbox(label="Deepfake Model Path", 
-                                                   placeholder="Path to deepfake detection model (.pth)")
-                    deepfake_cfg_path = gr.Textbox(label="Deepfake Config Path", 
-                                                 placeholder="Path to deepfake model config (.yaml)")
-        
-        # Connect the process function
-        process_btn.click(
-            fn=process_image,
-            inputs=[
-                input_image, 
-                damage_model_path,
-                deepfake_model_path,
-                deepfake_cfg_path,
-                damage_threshold,
-                deepfake_threshold,
-                skip_damage,
-                device
-            ],
-            outputs=[output_image, output_text]
-        )
-        
-        # Examples
-        gr.Markdown("## Examples")
-        gr.Markdown("Note: Examples will only work if you have the appropriate models installed.")
-            
-    return app
+    return app      
+
 
     # Create and launch the app