Update app.py

app.py

@@ -1,13 +1,16 @@
 import gradio as gr
 import cv2
-import requests
-import os
 from ultralytics import YOLO
 
 model = YOLO('best.pt')
-# video_path = 'Deployment\\test_videos\\test2.mp4'
-def show_preds(video_path):
+
+def show_preds(video_path, output_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:
@@ -23,24 +26,25 @@ def show_preds(video_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.components.Video(type='filepath', label='Input Video'),
+    gr.inputs.Video(type='file', label='Input Video'),
 ]
-outputs_video = [
-    gr.components.Image(type='numpy', label='Output Image'),
+output_video = [
+    gr.outputs.Video(type='file', label='Output Video'),
 ]
-interface_video = gr.Interface(
-    fn=show_preds,
-    inputs=input_video,
-    outputs=outputs_video,
+
+interface = gr.Interface(
+    show_preds,
+    inputs=input_video, # type: ignore
+    outputs=output_video, # type: ignore
     title='Pothole Detection',
-    #examples=video_path,
-    cache_examples=False,
+    description='Potholes Detection using YOLOv8',
 )
 
-gr.TabbedInterface(   
-    [interface_video],
-    tab_names=['Video Inference']
-).queue().launch()
+interface.queue().launch()