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.
code: def __init__(
      self,
      label_file: str,
      meta_file: str,
      hierarchy_file: str,
      image_level_ann_file: Optional[str] = None,
      **kwargs,
  ) -> None:
      self.label_file = label_file
      self.meta_file = meta_file
      self.hierarchy_file = hierarchy_file
      self.image_level_ann_file = image_level_ann_file
      super().__init__(**kwargs)
  
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 1 to create a new OpenImagesDataset object from inherited base classes: BaseDetDataset with example: obj = OpenImagesDataset(label_file, meta_file, hierarchy_file, image_level_ann_file)