Update app.py

app.py

@@ -58,24 +58,39 @@ interface_image = gr.Interface(
 
 
 # For video processing, it's best to process and then show the output video.
-# This is a simplified placeholder for video processing, indicating where to include the video processing logic.
 def show_preds_video(video_path):
-    # Placeholder for video processing function
-    # Process the video here and save the output, then return the path to the processed video
-    processed_video_path = "processed_video.mp4"  # Example output path
-    return processed_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 det in 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)
+        else:
+            break
+    cap.release()
+    
+inputs_video = gr.components.Video(label="Input Video")
+outputs_video = gr.components.Image(label="Output Image", type="numpy")
 
-
-# Define the Gradio interface for video input
 interface_video = gr.Interface(
     fn=show_preds_video,
-    inputs=gr.components.Video(label="Input Video"), 
-    outputs=gr.components.Video(type="numpy", label="Processed Video"),
-    title="Pothole Detector - Video",
+    inputs=inputs_video,
+    outputs=outputs_video,
+    title="Pothole Detector",
     examples=example_vids,
     cache_examples=False,
 )
-
 # Combine the interfaces into a tabbed interface
 gr.TabbedInterface(
     [interface_image, interface_video], tab_names=["Image Inference", "Video Inference"]