code: def __img_path2label_path(self, path: str) -> str:
      im, lb = (
          os.sep + "images" + os.sep,
          os.sep + "annotations" + os.sep,
      )
      return lb.join(path.rsplit(im, 1)).rsplit(".", 1)[0] + ".txt"
  
imports: import os
  import warnings
  from typing import Tuple, List
  import cv2
  import numpy
  import torch
  from torch.utils.data import Dataset
  from torchvision import transforms
  from ....yolov3.utils import prepare_image
label_desc: Use image node_id 3 for calling the LoadImagesAndLabels obj's underlying member method code with example usage: obj.__img_path2label_path(path) and returns: unknown