class_docstr: Implements a post processor for DBNet adapted from the implementation of `xuannianz
  <https://github.com/xuannianz/DifferentiableBinarization>`_.
  
  Args:
  ----
      unclip ratio: ratio used to unshrink polygons
      min_size_box: minimal length (pix) to keep a box
      max_candidates: maximum boxes to consider in a single page
      box_thresh: minimal objectness score to consider a box
      bin_thresh: threshold used to binzarized p_map at inference time
class_docstr_tok: ["Implements","a","post","processor","for","DBNet","adapted","from","the","implementation","of","`","xuannianz","<","https",":","\/\/github.com\/xuannianz\/DifferentiableBinarization",">","`","_",".","Args",":","--","--","unclip","ratio",":","ratio","used","to","unshrink","polygons","min_size_box",":","minimal","length","(","pix",")","to","keep","a","box","max_candidates",":","maximum","boxes","to","consider","in","a","single","page","box_thresh",":","minimal","objectness","score","to","consider","a","box","bin_thresh",":","threshold","used","to","binzarized","p_map","at","inference","time"]
code: def __init__(
      self,
      box_thresh: float = 0.1,
      bin_thresh: float = 0.3,
      assume_straight_pages: bool = True,
  ) -> None:
      super().__init__(box_thresh, bin_thresh, assume_straight_pages)
      self.unclip_ratio = 1.5
  
file_path: doctr/doctr/models/detection/differentiable_binarization/base.py
imports: from typing import Dict, List, Tuple, Union
  import cv2
  import numpy
  import pyclipper
  from shapely.geometry import Polygon
  from ..core import DetectionPostProcessor
label_desc: Use image node_id 1 to create a new DBPostProcessor object from inherited base classes: DetectionPostProcessor with example: obj = DBPostProcessor(box_thresh, bin_thresh, assume_straight_pages)