class_docstr: Abstract class to postprocess the raw output of the model
  
  Args:
  ----
      box_thresh (float): minimal objectness score to consider a box
      bin_thresh (float): threshold to apply to segmentation raw heatmap
      assume straight_pages (bool): if True, fit straight boxes only
class_docstr_tok: ["Abstract","class","to","postprocess","the","raw","output","of","the","model","Args",":","--","--","box_thresh","(","float",")",":","minimal","objectness","score","to","consider","a","box","bin_thresh","(","float",")",":","threshold","to","apply","to","segmentation","raw","heatmap","assume","straight_pages","(","bool",")",":","if","True",",","fit","straight","boxes","only"]
code: def extra_repr(self) -> str:
      return (
          f"bin_thresh={self.bin_thresh}, box_thresh={self.box_thresh}"
      )
  
file_path: doctr/doctr/models/detection/core.py
imports: from typing import List
  import cv2
  import numpy
  from doctr.utils.repr import NestedObject
label_desc: Use image node_id 2 for calling the DetectionPostProcessor obj's underlying member method code with example usage: obj.extra_repr() and returns: str, self, str, self