Add robust logging and checks to ensure output video is valid and not empty

app.py

@@ -183,7 +183,6 @@ def process_video_movenet(video_path):
         width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
         height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
         total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
-        
         print(f"[DEBUG] Video properties - FPS: {fps}, Width: {width}, Height: {height}, Total Frames: {total_frames}")
         
         # Initialize MoveNet model on GPU if available
@@ -216,17 +215,18 @@ def process_video_movenet(video_path):
             ret, frame = cap.read()
             if not ret:
                 break
-                
             frame_count += 1
             if frame_count % 10 != 0:  # Process every 10th frame
                 continue
-                
             try:
+                # Ensure frame size matches VideoWriter
+                if frame.shape[1] != width or frame.shape[0] != height:
+                    print(f"[WARNING] Frame size {frame.shape[1]}x{frame.shape[0]} does not match VideoWriter size {width}x{height}. Resizing.")
+                    frame = cv2.resize(frame, (width, height))
                 # Resize and pad the image to keep aspect ratio
                 img = frame.copy()
                 img = tf.image.resize_with_pad(tf.expand_dims(img, axis=0), 192, 192)
                 img = tf.cast(img, dtype=tf.int32)
-                
                 # Run inference on GPU if available
                 if gpus:
                     with tf.device('/GPU:0'):
@@ -236,31 +236,31 @@ def process_video_movenet(video_path):
                     with tf.device('/CPU:0'):
                         results = movenet(img)
                         keypoints = results['output_0'].numpy()
-                
                 # Process keypoints and draw on frame
                 y, x, c = frame.shape
                 shaped = np.squeeze(keypoints)
-                
                 for kp in range(17):
                     ky, kx, kp_conf = shaped[kp]
                     if kp_conf > 0.3:
                         cx, cy = int(kx * x), int(ky * y)
                         cv2.circle(frame, (cx, cy), 6, (0, 255, 0), -1)
-                
                 out.write(frame)
                 processed_frames += 1
-                
+                print(f"[DEBUG] Wrote frame {frame_count} to output video.")
             except Exception as e:
                 print(f"[ERROR] Error processing frame {frame_count}: {str(e)}")
                 continue
-        
         cap.release()
         out.release()
-        
         print(f"[DEBUG] Processed {processed_frames} frames out of {total_frames} total frames")
-        # Return the correct URL for the output video
+        # Check output file size
+        if not os.path.exists(output_path):
+            raise ValueError(f"Output video file was not created: {output_path}")
+        file_size = os.path.getsize(output_path)
+        print(f"[DEBUG] Output video file size: {file_size} bytes")
+        if processed_frames == 0 or file_size < 1000:
+            raise ValueError(f"Output video file is empty or too small: {output_path}")
         return url_for('serve_video', filename=output_filename, _external=False)
-        
     except Exception as e:
         print(f"[ERROR] Error in process_video_movenet: {str(e)}")
         traceback.print_exc()