Update app

app.py

@@ -1389,4 +1389,4 @@ if __name__ == "__main__":
 			outputs=[demo_choice, video_input, global_speaker, num_avg_frames, apply_preprocess, result_text, output_video]
 		)
 	# Launch the interface
-	demo.launch(allowed_paths=["."], server_name="0.0.0.0", server_port=7860, share=True)
+	demo.launch(allowed_paths=["."], share=True)

preprocess/inference_preprocess.py

@@ -48,7 +48,7 @@ def bb_intersection_over_union(boxA, boxB):
 	return iou
 
 def track_shot(opt, scenefaces):
-    print("Tracking video...")
+	print("Tracking video...")
 	iouThres = 0.5  # Minimum IOU between consecutive face detections
 	tracks = []
 
@@ -104,7 +104,7 @@ def read_video(o, start_idx):
 		return video_stream
 
 def crop_video(opt, track, cropfile, tight_scale=1):
-    print("Cropping video...")
+	print("Cropping video...")
 	fourcc = cv2.VideoWriter_fourcc(*'XVID')
 	vOut = cv2.VideoWriter(cropfile + '.avi', fourcc, opt.frame_rate, (480, 270))
 
@@ -169,7 +169,7 @@ def inference_video(opt, padding=0):
 
 	dets = []
 	fidx = 0
-    print("Detecting people in the video using YOLO...")
+	print("Detecting people in the video using YOLO...")
 	while True:
 		success, image = vidObj.read()
 		if not success:
@@ -203,7 +203,7 @@ def inference_video(opt, padding=0):
 	return dets
 
 def scene_detect(opt):
-    print("Detecting scenes in the video...")
+	print("Detecting scenes in the video...")
 	video_manager = VideoManager([os.path.join(opt.avi_dir, 'video.avi')])
 	stats_manager = StatsManager()
 	scene_manager = SceneManager(stats_manager)