class_docstr: Bbox head used in Double-Head R-CNN
  
  .. code-block:: none
  
                                        /-> cls
                    /-> shared convs ->
                                        \-> reg
      roi features
                                        /-> cls
                    \-> shared fc    ->
                                        \-> reg
code: def __init__(
      self,
      num_convs=0,
      num_fcs=0,
      conv_out_channels=1024,
      fc_out_channels=1024,
      conv_cfg=None,
      norm_cfg=dict(type="BN"),
      **kwargs,
  ):
      kwargs.setdefault("with_avg_pool", True)
      super(DoubleConvFCBBoxHead, self).__init__(**kwargs)
      assert self.with_avg_pool
      assert num_convs > 0
      assert num_fcs > 0
      self.num_convs = num_convs
      self.num_fcs = num_fcs
      self.conv_out_channels = conv_out_channels
      self.fc_out_channels = fc_out_channels
      self.conv_cfg = conv_cfg
      self.norm_cfg = norm_cfg
  
      # increase the channel of input features
      self.res_block = BasicResBlock(
          self.in_channels, self.conv_out_channels
      )
  
      # add conv heads
      self.conv_branch = self._add_conv_branch()
      # add fc heads
      self.fc_branch = self._add_fc_branch()
  
      out_dim_reg = (
          4 if self.reg_class_agnostic else 4 * self.num_classes
      )
      self.fc_reg = nn.Linear(self.conv_out_channels, out_dim_reg)
  
      self.fc_cls = nn.Linear(
          self.fc_out_channels, self.num_classes + 1
      )
      self.relu = nn.ReLU(inplace=True)
  
file_path: insightface/detection/scrfd/mmdet/models/roi_heads/bbox_heads/double_bbox_head.py
imports: import torch.nn
  from mmcv.cnn import ConvModule, normal_init, xavier_init
  from mmdet.models.backbones.resnet import Bottleneck
  from mmdet.models.builder import HEADS
  from .bbox_head import BBoxHead
label_desc: Use image node_id 1 to create a new DoubleConvFCBBoxHead object from inherited base classes: BBoxHead with example: obj = DoubleConvFCBBoxHead(num_convs, num_fcs, conv_out_channels, fc_out_channels, conv_cfg, norm_cfg)