class_docstr: Two-stage text spotter.
  
  Args:
      backbone (dict, optional): Config dict for text spotter backbone.
          Defaults to None.
      neck (dict, optional): Config dict for text spotter neck. Defaults to
          None.
      det_head (dict, optional): Config dict for text spotter head. Defaults
          to None.
      roi_head (dict, optional): Config dict for text spotter roi head.
          Defaults to None.
      data_preprocessor (dict, optional): Config dict for text spotter data
          preprocessor. Defaults to None.
      init_cfg (dict, optional): Initialization config dict. Defaults to
          None.
docstr: bool: whether the detector has a RoI head
docstr_tok: ["bool",":","whether","the","detector","has","a","RoI","head"]
code: def with_roi_head(self):
      """bool: whether the detector has a RoI head"""
      return hasattr(self, "roi_head") and self.roi_head is not None
  
file_path: mmocr/projects/ABCNet/abcnet/model/two_stage_text_spotting.py
imports: from typing import Dict
  import torch
  from mmocr.models.textdet.detectors.base import BaseTextDetector
  from mmocr.registry import MODELS
  from mmocr.utils import OptConfigType, OptDetSampleList, OptMultiConfig
label_desc: Use image node_id 3 for calling the TwoStageTextSpotter obj's underlying member method code with example usage: obj.with_roi_head() and returns: unknown