code: def __load_data(
      self, img_path: str, label: np.ndarray
  ) -> Tuple[torch.Tensor, torch.Tensor]:
      img = cv.imread(img_path)
      img_h, img_w = img.shape[:2]
      img = prepare_image(
          img[:, :, :3], [self.__net_width, self.__net_height]
      )
      lab = self.__process_label(label, img_w, img_h)
      return img.squeeze(), lab
  
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 6 for calling the LoadImagesAndLabels obj's underlying member method code with example usage: obj.__load_data(img_path, label) and returns: img,  lab