code: def default_evaluation_params():
      """
      default_evaluation_params: Default parameters to use for the validation and evaluation.
      """
      return {
          "IOU_CONSTRAINT": 0.5,
          "AREA_PRECISION_CONSTRAINT": 0.5,
          "GT_SAMPLE_NAME_2_ID": "gt_img_([0-9]+).txt",
          "DET_SAMPLE_NAME_2_ID": "res_img_([0-9]+).txt",
          "LTRB": False,  # LTRB:2points(left,top,right,bottom) or 4 points(x1,y1,x2,y2,x3,y3,x4,y4)
          "CRLF": False,  # Lines are delimited by Windows CRLF format
          "CONFIDENCES": False,  # Detections must include confidence value. AP will be calculated
          "PER_SAMPLE_RESULTS": True,  # Generate per sample results and produce data for visualization
      }
  
file_path: PaddleOCR/benchmark/PaddleOCR_DBNet/utils/cal_recall/script.py
imports: from collections import namedtuple
  from .None import rrc_evaluation_funcs
  import Polygon
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: default_evaluation_params() and returns: dict