code: def __init__(
      self,
      *,
      mult_proposal_score: bool = False,
      with_image_labels: bool = False,
      add_image_box: bool = False,
      image_box_size: float = 1.0,
      ws_num_props: int = 128,
      add_feature_to_prop: bool = False,
      mask_weight: float = 1.0,
      one_class_per_proposal: bool = False,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.mult_proposal_score = mult_proposal_score
      self.with_image_labels = with_image_labels
      self.add_image_box = add_image_box
      self.image_box_size = image_box_size
      self.ws_num_props = ws_num_props
      self.add_feature_to_prop = add_feature_to_prop
      self.mask_weight = mask_weight
      self.one_class_per_proposal = one_class_per_proposal
  
imports: from typing import List, Sequence, Tuple
  import torch
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.models.roi_heads import CascadeRoIHead
  from mmdet.models.task_modules.samplers import SamplingResult
  from mmdet.models.test_time_augs import merge_aug_masks
  from mmdet.models.utils import empty_instances, unpack_gt_instances
  from mmdet.registry import MODELS
  from mmdet.structures import SampleList
  from mmdet.structures.bbox import bbox2roi, get_box_tensor
  from mmdet.utils import ConfigType, InstanceList, MultiConfig
label_desc: Use image node_id 1 to create a new DeticRoIHead object from inherited base classes: CascadeRoIHead with example: obj = DeticRoIHead()