code: def get_cls_group_ofs(annotations, class_id):
      """Get `gt_group_of` of a certain class, which is used in Open Images.
  
      Args:
          annotations (list[dict]): Same as `eval_map()`.
          class_id (int): ID of a specific class.
  
      Returns:
          list[np.ndarray]: `gt_group_of` of a certain class.
      """
      gt_group_ofs = []
      for ann in annotations:
          gt_inds = ann["labels"] == class_id
          if ann.get("gt_is_group_ofs", None) is not None:
              gt_group_ofs.append(ann["gt_is_group_ofs"][gt_inds])
          else:
              gt_group_ofs.append(np.empty((0, 1), dtype=bool))
  
      return gt_group_ofs
  
file_path: mmdetection/mmdet/evaluation/functional/mean_ap.py
imports: from multiprocessing import Pool
  import numpy
  from mmengine.logging import print_log
  from mmengine.utils import is_str
  from terminaltables import AsciiTable
  from .bbox_overlaps import bbox_overlaps
  from .class_names import get_classes
label_desc: Use image node_id 6 for calling a global function with example usage: get_cls_group_ofs(annotations, class_id) and returns: gt_group_ofs