code: def __load_raw_label(self, label_path: str):
      if os.path.isfile(label_path):
          with warnings.catch_warnings():
              l = np.loadtxt(label_path).reshape(-1, 5)
              assert (
                  l >= 0
              ).all(), "bounding box values should be positive and in range 0 - 1"
              assert (
                  l[:, 1:] <= 1
              ).all(), (
                  "bounding box values should be in the range 0 - 1"
              )
      else:
          l = np.zeros((0, 5), dtype=np.float32)
      return l
  
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 7 for calling the LoadImagesAndLabels obj's underlying member method code with example usage: obj.__load_raw_label(label_path) and returns: l