Update app.py

app.py

@@ -3,14 +3,9 @@ import cv2
 from ultralytics import YOLO
 
 model = YOLO('best.pt')
-
-def show_preds(video_path, output_path):
+# video_path = 'Deployment\\test_videos\\test2.mp4'
+def show_preds(video_path):
     cap = cv2.VideoCapture(video_path)
-    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-    fps = cap.get(cv2.CAP_PROP_FPS)
-    fourcc = cv2.VideoWriter_fourcc(*'h264')
-    writer = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
     while True:
         ret, frame = cap.read()
         if ret:
@@ -26,25 +21,24 @@ def show_preds(video_path, output_path):
                     thickness=2,
                     lineType=cv2.LINE_AA
                 )
-            writer.write(frame_copy)
             yield cv2.cvtColor(frame_copy, cv2.COLOR_BGR2RGB)
-        else:
-            break
-    writer.release()
 
 input_video = [
-    gr.inputs.Video(type='file', label='Input Video'),
+    gr.components.Video(type='filepath', label='Input Video'),
 ]
-output_video = [
-    gr.outputs.Video(type='file', label='Output Video'),
+outputs_video = [
+    gr.components.Image(type='numpy', label='Output Image'),
 ]
-
-interface = gr.Interface(
-    show_preds,
+interface_video = gr.Interface(
+    fn=show_preds,
     inputs=input_video, # type: ignore
-    outputs=output_video, # type: ignore
+    outputs=outputs_video, # type: ignore
     title='Pothole Detection',
-    description='Potholes Detection using YOLOv8',
+    #examples=video_path,
+    cache_examples=False,
 )
 
-interface.queue().launch()
+gr.TabbedInterface(   
+    [interface_video],
+    tab_names=['Video Inference']
+).queue().launch()