if success:
        result = model.track(frame, persist=True, conf=0.5, iou=0.5)

        # Check if any objects were detected
        if result[0].boxes.cls.numel() > 0:
            # Get the boxes and track IDs
            cls = result[0].boxes.cls.int().cpu().item()
            boxes = result[0].boxes.xywh.cpu()
            track_ids = result[0].boxes.id.int().cpu().tolist()
            name = result[0].names[cls]

            # Visualize the results on the frame
            annotated_frame = result[0].plot()

            # Plot the tracks
            for box, track_id in zip(boxes, track_ids):
                x, y, w, h = box
                track = track_history[track_id]
                track.append((float(x), float(y)))  # x, y center point
                if len(track) > 30:
                    track.pop(0)

                # Draw the tracking lines
                points = np.array(track).astype(np.int32).reshape((-1, 1, 2))
                print("cls number ", cls, "class name", name)
                cv2.polylines(annotated_frame, [points], isClosed=False, color=(230, 230, 230), thickness=10)

            # Display the annotated frame
            cv2.imshow("YOLOv8 Tracking .... ", annotated_frame)
        else:
            # If no objects are detected, just display the frame
            cv2.imshow("YOLOv8 Tracking .... ", frame)

        # Break the loop if 'q' is pressed
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    else:
        break

cap = cv2.VideoCapture(0)  # webcam device : 0

# Store the track history
track_history = defaultdict(lambda: [])

webcam_play_run(cap=cap, model=model, track_history=track_history)