class_docstr: Implementation of `CrowdDet <https://arxiv.org/abs/2003.09163>`_
  
  Args:
      backbone (:obj:`ConfigDict` or dict): The backbone config.
      rpn_head (:obj:`ConfigDict` or dict): The rpn config.
      roi_head (:obj:`ConfigDict` or dict): The roi config.
      train_cfg (:obj:`ConfigDict` or dict, optional): The training config
          of FCOS. Defaults to None.
      test_cfg (:obj:`ConfigDict` or dict, optional): The testing config
          of FCOS. Defaults to None.
      neck (:obj:`ConfigDict` or dict): The neck config.
      data_preprocessor (:obj:`ConfigDict` or dict, optional): Config of
          :class:`DetDataPreprocessor` to process the input data.
          Defaults to None.
      init_cfg (:obj:`ConfigDict` or list[:obj:`ConfigDict`] or dict or
          list[dict], optional): Initialization config dict.
          Defaults to None.
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code: def __init__(
      self,
      backbone: ConfigType,
      rpn_head: ConfigType,
      roi_head: ConfigType,
      train_cfg: ConfigType,
      test_cfg: ConfigType,
      neck: OptConfigType = None,
      data_preprocessor: OptConfigType = None,
      init_cfg: OptMultiConfig = None,
  ) -> None:
      super().__init__(
          backbone=backbone,
          neck=neck,
          rpn_head=rpn_head,
          roi_head=roi_head,
          train_cfg=train_cfg,
          test_cfg=test_cfg,
          init_cfg=init_cfg,
          data_preprocessor=data_preprocessor,
      )
  
imports: from mmdet.registry import MODELS
  from mmdet.utils import ConfigType, OptConfigType, OptMultiConfig
  from .two_stage import TwoStageDetector
label_desc: Use image node_id 1 to create a new CrowdDet object from inherited base classes: TwoStageDetector with example: obj = CrowdDet(backbone, rpn_head, roi_head, train_cfg, test_cfg, neck, data_preprocessor, init_cfg)