Update app.py

app.py

@@ -19,9 +19,17 @@ def process_frame(frame):
 def convert_video_to_dumpscare(video, sensitivity):
     # Initialize the output
     output_frames = []
-
+    
     # Read the video
     cap = cv2.VideoCapture(video)
+    fps = cap.get(cv2.CAP_PROP_FPS)
+    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    
+    # Define the codec and create a VideoWriter object
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    out = cv2.VideoWriter('output_dumpscare.mp4', fourcc, fps, (width, height))
+
     while cap.isOpened():
         ret, frame = cap.read()
         if not ret:
@@ -29,10 +37,17 @@ def convert_video_to_dumpscare(video, sensitivity):
         
         # Process each frame
         prediction = process_frame(frame)
-        output_frames.append(prediction)
+        
+        # Here you can modify the frame based on prediction if needed
+        output_frames.append(frame)  # For now, just appending the original frame
+        
+        # Write the frame to the output video
+        out.write(frame)
 
     cap.release()
-    return output_frames
+    out.release()
+    
+    return 'output_dumpscare.mp4'  # Return the path to the saved video
 
 def gradio_interface(video, sensitivity):
     result = convert_video_to_dumpscare(video, sensitivity)
@@ -42,10 +57,10 @@ def gradio_interface(video, sensitivity):
 iface = gr.Interface(
     fn=gradio_interface,
     inputs=[
-        gr.Video(label="Import Video"),  # Ensure video input
-        gr.Slider(label="Sensitivity", minimum=0, maximum=100, step=1, value=50)  # Use 'value' instead of 'default'
+        gr.Video(label="Import Video"),
+        gr.Slider(label="Sensitivity", minimum=0, maximum=100, step=1, value=50)
     ],
-    outputs="text"  # Change this according to your desired output format
+    outputs=gr.File(label="Output Video")  # Output will be a video file
 )
 
 # Launch the app