Update app.py

app.py

@@ -20,10 +20,7 @@ def download_file(url, save_name):
 
 for i, url in enumerate(file_urls):
     if 'mp4' in file_urls[i]:
-        download_file(
-            file_urls[i],
-            f"video.mp4"
-        )
+        print('enter the image data')
     else:
         download_file(
             file_urls[i],
@@ -32,7 +29,6 @@ for i, url in enumerate(file_urls):
 
 model = YOLO('best.pt')
 path  = [['image_0.jpg'], ['image_1.jpg']]
-video_path = [['video.mp4']]
 
 def show_preds_image(image_path):
     image = cv2.imread(image_path)
@@ -63,43 +59,7 @@ interface_image = gr.Interface(
     examples=path,
     cache_examples=False,
 )
-
-def show_preds_video(video_path):
-    cap = cv2.VideoCapture(video_path)
-    while(cap.isOpened()):
-        ret, frame = cap.read()
-        if ret:
-            frame_copy = frame.copy()
-            outputs = model.predict(source=frame)
-            results = outputs[0].cpu().numpy()
-            for i, det in enumerate(results.boxes.xyxy):
-                cv2.rectangle(
-                    frame_copy,
-                    (int(det[0]), int(det[1])),
-                    (int(det[2]), int(det[3])),
-                    color=(0, 0, 255),
-                    thickness=2,
-                    lineType=cv2.LINE_AA
-                )
-            yield cv2.cvtColor(frame_copy, cv2.COLOR_BGR2RGB)
-
-inputs_video = [
-    gr.components.Video(type="filepath", label="Input Video"),
-
-]
-outputs_video = [
-    gr.components.Image(type="numpy", label="Output Image"),
-]
-interface_video = gr.Interface(
-    fn=show_preds_video,
-    inputs=inputs_video,
-    outputs=outputs_video,
-    title="Pothole detector",
-    examples=video_path,
-    cache_examples=False,
-)
-
 gr.TabbedInterface(
-    [interface_image, interface_video],
-    tab_names=['Image inference', 'Video inference']
+    [interface_image],
+    tab_names=['Image inference']
 ).queue().launch()