class_docstr: Open Images dataset for detection.
  
  Args:
      ann_file (str): Annotation file path.
      label_file (str): File path of the label description file that
          maps the classes names in MID format to their short
          descriptions.
      meta_file (str): File path to get image metas.
      hierarchy_file (str): The file path of the class hierarchy.
      image_level_ann_file (str): Human-verified image level annotation,
          which is used in evaluation.
      backend_args (dict, optional): Arguments to instantiate the
          corresponding backend. Defaults to None.
docstr: Get classes name and index mapping from cls-label-description file.
  
  Args:
      label_file (str): File path of the label description file that
          maps the classes names in MID format to their short
          descriptions.
  
  Returns:
      tuple: Class name of OpenImages.
docstr_tok: ["Get","classes","name","and","index","mapping","from","cls-label-description","file",".","Args",":","label_file","(","str",")",":","File","path","of","the","label","description","file","that","maps","the","classes","names","in","MID","format","to","their","short","descriptions",".","Returns",":","tuple",":","Class","name","of","OpenImages","."]
code: def _parse_label_file(self, label_file: str) -> tuple:
      """Get classes name and index mapping from cls-label-description file.
  
      Args:
          label_file (str): File path of the label description file that
              maps the classes names in MID format to their short
              descriptions.
  
      Returns:
          tuple: Class name of OpenImages.
      """
  
      index_list = []
      classes_names = []
      with get_local_path(
          label_file, backend_args=self.backend_args
      ) as local_path:
          with open(local_path, "r") as f:
              reader = csv.reader(f)
              for line in reader:
                  # self.cat2label[line[0]] = line[1]
                  classes_names.append(line[1])
                  index_list.append(line[0])
      index_mapping = {index: i for i, index in enumerate(index_list)}
      return classes_names, index_mapping
  
imports: import csv
  import os.path
  from collections import defaultdict
  from typing import Dict, List, Optional
  import numpy
  from mmengine.fileio import get_local_path, load
  from mmengine.utils import is_abs
  from mmdet.registry import DATASETS
  from .base_det_dataset import BaseDetDataset
label_desc: Use image node_id 3 for calling the OpenImagesDataset obj's underlying member method code with example usage: obj._parse_label_file(label_file) and returns: classes_names,  index_mapping