class_docstr: Open Images Challenge dataset for detection.
  
  Args:
      ann_file (str): Open Images Challenge box annotation in txt format.
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.
      """
      label_list = []
      id_list = []
      index_mapping = {}
      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:
                  label_name = line[0]
                  label_id = int(line[2])
                  label_list.append(line[1])
                  id_list.append(label_id)
                  index_mapping[label_name] = label_id - 1
      indexes = np.argsort(id_list)
      classes_names = []
      for index in indexes:
          classes_names.append(label_list[index])
      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 OpenImagesChallengeDataset obj's underlying member method code with example usage: obj._parse_label_file(label_file) and returns: classes_names,  index_mapping