state buttons

app.py

@@ -159,16 +159,16 @@ def run_video_inference(
         confidence_threshold: Confidence threshold for filtering predictions
     
     Returns:
-        Tuple of (output_video_path, metrics_text)
+        Tuple of (output_video_path, metrics_text, start_btn_state, stop_btn_state)
     """
     global streaming
     streaming = True
     
     if video_path is None:
-        return None, "⚠️ Please upload a video first."
+        return None, "⚠️ Please upload a video first.", gr.update(interactive=True), gr.update(interactive=False)
     
     if model_name is None or model_name == "No models available":
-        return None, "⚠️ No model selected or available."
+        return None, "⚠️ No model selected or available.", gr.update(interactive=True), gr.update(interactive=False)
     
     try:
         # Load model
@@ -178,7 +178,7 @@ def run_video_inference(
         cap = cv2.VideoCapture(video_path)
         
         if not cap.isOpened():
-            return None, "⚠️ Error: Could not open video file."
+            return None, "⚠️ Error: Could not open video file.", gr.update(interactive=True), gr.update(interactive=False)
         
         # Get video properties
         video_codec = cv2.VideoWriter_fourcc(*"mp4v")
@@ -188,7 +188,7 @@ def run_video_inference(
         # Read first frame to get dimensions
         ret, frame = cap.read()
         if not ret or frame is None:
-            return None, "⚠️ Error: Could not read video frames."
+            return None, "⚠️ Error: Could not read video frames.", gr.update(interactive=True), gr.update(interactive=False)
         
         # Process first frame to get output dimensions
         result = model(frame)
@@ -241,20 +241,28 @@ def run_video_inference(
         
         # Verify final file exists before returning
         if os.path.exists(output_video_name) and os.path.getsize(output_video_name) > 0:
-            return output_video_name, final_metrics
+            return output_video_name, final_metrics, gr.update(interactive=True), gr.update(interactive=False)
         else:
-            return None, final_metrics + "\n⚠️ Final video file not available."
+            return None, final_metrics + "\n⚠️ Final video file not available.", gr.update(interactive=True), gr.update(interactive=False)
         
     except Exception as e:
         error_msg = f"Error during video inference: {str(e)}"
-        return None, error_msg
+        return None, error_msg, gr.update(interactive=True), gr.update(interactive=False)
 
 
 def stop_video_inference():
     """Stop video processing."""
     global streaming
     streaming = False
-    return "⏹️ Video processing stopped."
+    return "⏹️ Video processing stopped.", gr.update(interactive=True), gr.update(interactive=False)
+
+
+def enable_video_buttons(video):
+    """Enable start button when video is uploaded."""
+    if video is not None:
+        return gr.update(interactive=True), gr.update(interactive=False)
+    else:
+        return gr.update(interactive=False), gr.update(interactive=False)
 
 
 def format_results(result, confidence_threshold: float) -> str:
@@ -423,8 +431,8 @@ def create_gradio_interface():
                         )
                         
                         with gr.Row():
-                            video_start_btn = gr.Button("▶️ Start Processing", variant="primary")
-                            video_stop_btn = gr.Button("⏹️ Stop", variant="stop")
+                            video_start_btn = gr.Button("▶️ Start Processing", variant="primary", interactive=False)
+                            video_stop_btn = gr.Button("⏹️ Stop", variant="stop", interactive=False)
                     
                     with gr.Column(scale=1):
                         output_video = gr.Video(
@@ -440,17 +448,31 @@ def create_gradio_interface():
                             max_lines=15
                         )
                 
-                # Connect video buttons
+                # Enable start button when video is uploaded
+                input_video.change(
+                    fn=enable_video_buttons,
+                    inputs=[input_video],
+                    outputs=[video_start_btn, video_stop_btn]
+                )
+                
+                # Connect video buttons - when clicked, start is disabled and stop is enabled
+                def start_processing_wrapper(video, model, conf):
+                    # First disable start and enable stop
+                    yield None, "🔄 Starting video processing...", gr.update(interactive=False), gr.update(interactive=True)
+                    # Then run the actual processing
+                    result = run_video_inference(video, model, conf)
+                    yield result
+                
                 video_start_btn.click(
-                    fn=run_video_inference,
+                    fn=start_processing_wrapper,
                     inputs=[input_video, video_model_dropdown, video_confidence_slider],
-                    outputs=[output_video, video_metrics_output]
+                    outputs=[output_video, video_metrics_output, video_start_btn, video_stop_btn]
                 )
                 
                 video_stop_btn.click(
                     fn=stop_video_inference,
                     inputs=None,
-                    outputs=video_metrics_output
+                    outputs=[video_metrics_output, video_start_btn, video_stop_btn]
                 )
                 
                 # Video Examples section