class_docstr: Implements a post processor for LinkNet model.
  
  Args:
  ----
      bin_thresh: threshold used to binzarized p_map at inference time
      box_thresh: minimal objectness score to consider a box
      assume_straight_pages: whether the inputs were expected to have horizontal text elements
class_docstr_tok: ["Implements","a","post","processor","for","LinkNet","model",".","Args",":","--","--","bin_thresh",":","threshold","used","to","binzarized","p_map","at","inference","time","box_thresh",":","minimal","objectness","score","to","consider","a","box","assume_straight_pages",":","whether","the","inputs","were","expected","to","have","horizontal","text","elements"]
code: def __init__(
      self,
      bin_thresh: float = 0.1,
      box_thresh: float = 0.1,
      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/linknet/base.py
imports: from typing import Dict, List, Tuple, Union
  import cv2
  import numpy
  import pyclipper
  from shapely.geometry import Polygon
  from doctr.models.core import BaseModel
  from ..core import DetectionPostProcessor
label_desc: Use image node_id 1 to create a new LinkNetPostProcessor object from inherited base classes: DetectionPostProcessor with example: obj = LinkNetPostProcessor(bin_thresh, box_thresh, assume_straight_pages)