code: def add_ResNet_roi_conv5_head_for_masks(
      model, blob_in, dim_in, spatial_scale
  ):
      """Add a ResNet "conv5" / "stage5" head for predicting masks."""
      model.RoIFeatureTransform(
          blob_in,
          blob_out="_[mask]_pool5",
          blob_rois="mask_rois",
          method=cfg.MRCNN.ROI_XFORM_METHOD,
          resolution=cfg.MRCNN.ROI_XFORM_RESOLUTION,
          sampling_ratio=cfg.MRCNN.ROI_XFORM_SAMPLING_RATIO,
          spatial_scale=spatial_scale,
      )
  
      dilation = cfg.MRCNN.DILATION
      stride_init = int(
          cfg.MRCNN.ROI_XFORM_RESOLUTION / 7
      )  # by default: 2
  
      s, dim_in = ResNet.add_stage(
          model,
          "_[mask]_res5",
          "_[mask]_pool5",
          3,
          dim_in,
          2048,
          512,
          dilation,
          stride_init=stride_init,
      )
  
      return s, 2048
  
file_path: dense-pose/detectron/modeling/mask_rcnn_heads.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from detectron.core.config import cfg
  from detectron.utils.c2 import const_fill
  from detectron.utils.c2 import gauss_fill
  from detectron.utils.net import get_group_gn
  import detectron.modeling.ResNet
  import detectron.utils.blob
label_desc: Use image node_id 10 for calling a global function with example usage: add_ResNet_roi_conv5_head_for_masks(model, blob_in, dim_in, spatial_scale) and returns: s,  int