Update app.py

app.py

@@ -23,11 +23,6 @@ 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 = []
-
-    frame_counter = 0  # Counter to limit the number of frames for processing
-
     while True:
         # Read a frame from the video
         ret, frame = input_video.read()
@@ -48,26 +43,18 @@ def process_video(video):
             # Convert the annotated frame to RGB format for displaying
             annotated_frame_rgb = cv2.cvtColor(annotated_frame, cv2.COLOR_BGR2RGB)
 
-            # Append the annotated frame to the list for Gradio
-            processed_frames.append(annotated_frame_rgb)
-
-        # Limit the number of frames processed (to speed up processing)
-        frame_counter += 1
-        if frame_counter > 100:  # Process only 100 frames, adjust as necessary
-            break
+            # Yield the frame immediately
+            yield annotated_frame_rgb
 
     # Release resources
     input_video.release()
 
-    # Return the processed frames as a list of NumPy arrays (Gradio expects this format)
-    return processed_frames  # Ensure this is a list of frames
-
 # Create a Gradio interface for video upload
 iface = gr.Interface(fn=process_video, 
                      inputs=gr.Video(label="Upload Video"),  # Updated line
-                     outputs=gr.Video(label="Processed Video"),  # This will display the output video directly
+                     outputs=gr.Image(label="Processed Frame", type="numpy"),  # Show processed frame immediately
                      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.")
+                     description="Upload a video for object detection using YOLOv8. The frames with detections will be shown in real-time as they are processed.")
 
 # Launch the interface
 iface.launch()