width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
   height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
   webcam_data = (width, height)

   zone = sv.PolygonZone(polygon=polygon, frame_resolution_wh=webcam_data)
   box_annotator = sv.BoxAnnotator(thickness=4, text_thickness=4, text_scale=2)
   zone_annotator = sv.PolygonZoneAnnotator(zone=zone, color=sv.Color.green(), thickness=6, text_thickness=6,
                                           text_scale=4)

   while True:

       ret, frame = cap.read()

       if not ret:
           break
  
       results = model(frame)
      
       for result in results:
           frame = result.orig_img

           detections = sv.Detections.from_yolov8(result)

           labels = [
               f"{tracker_id} {model.names[class_id]} {confidence:0.2f}"
               for _, confidence, class_id, tracker_id
               in detections
           ]

           frame = box_annotator.annotate(
               scene=frame,
               detections=detections,
               labels=labels
           )

           zone.trigger(detections=detections)
           zone_annotator.annotate(scene=frame)
           print("END webcam cycle "+str(webcam_id) +"\n")

           cv2.imshow(f"yolov8-{webcam_id}", frame)

       if cv2.waitKey(1) & 0xFF == 27:
           break

   cap.release()
   cv2.destroyAllWindows()

   webcam_id_1 = 0
   webcam_id_2 = 1

   cap2 = cv2.VideoCapture(1)# cv2.CAP_DSHOW
   cap = cv2.VideoCapture(0)# cv2.CAP_DSHOW

   thread2 = Thread(target=webcam_inference, args=(webcam_id_2, model, cap2))
   thread1 = Thread(target=webcam_inference, args=(webcam_id_1, model, cap))

   thread2.start()
   thread1.start()
  
   thread1.join()
   thread2.join()