class_docstr: Implementation of `Cascade R-CNN: Delving into High Quality Object
  Detection <https://arxiv.org/abs/1906.09756>`_
class_docstr_tok: ["Implementation","of","`","Cascade","R-CNN",":","Delving","into","High","Quality","Object","Detection","<","https",":","\/\/arxiv.org\/abs\/1906.09756",">","`","_"]
code: def __init__(
      self,
      backbone: ConfigType,
      neck: OptConfigType = None,
      rpn_head: OptConfigType = None,
      roi_head: OptConfigType = None,
      train_cfg: OptConfigType = None,
      test_cfg: 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,
          data_preprocessor=data_preprocessor,
          init_cfg=init_cfg,
      )
  
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 CascadeRCNN object from inherited base classes: TwoStageDetector with example: obj = CascadeRCNN(backbone, neck, rpn_head, roi_head, train_cfg, test_cfg, data_preprocessor, init_cfg)