Update app.py

app.py

@@ -23,6 +23,9 @@ def process_video(video):
     new_width, new_height = 640, 480  # Resize to 640x480 resolution
     frame_width, frame_height = new_width, new_height
 
+    # List to store processed frames for Gradio output
+    processed_frames = []
+
     while True:
         # Read a frame from the video
         ret, frame = input_video.read()
@@ -43,23 +46,19 @@ def process_video(video):
             # Convert the annotated frame to RGB format for displaying
             annotated_frame_rgb = cv2.cvtColor(annotated_frame, cv2.COLOR_BGR2RGB)
 
-            # Display the frame with detections
-            cv2.imshow("Detected Frame", annotated_frame_rgb)
-
-            # Wait for a key press (optional: press 'q' to quit early)
-            if cv2.waitKey(1) & 0xFF == ord('q'):
-                break
+            # Append the annotated frame to the list for Gradio
+            processed_frames.append(annotated_frame_rgb)
 
     # Release resources
     input_video.release()
-    cv2.destroyAllWindows()
 
-    return "Video processing complete!"
+    # Return the processed frames for Gradio to display as a video
+    return processed_frames
 
 # Create a Gradio interface for video upload
 iface = gr.Interface(fn=process_video, 
                      inputs=gr.Video(label="Upload Video"),  # Updated line
-                     outputs=gr.Textbox(label="Processing Status"),  # Output text showing processing status
+                     outputs=gr.Video(label="Processed Video"),  # This will display the output video directly
                      title="YOLOv8 Object Detection - Real-Time Display",
                      description="Upload a video for object detection using YOLOv8. The frames with detections will be shown in real-time.")