code: def dataset_pr_info(thresh_num, pr_curve, count_face):
      _pr_curve = np.zeros((thresh_num, 2))
      for i in range(thresh_num):
          # _pr_curve[i, 0] = round(pr_curve[i, 1] / pr_curve[i, 0], 4)
          # _pr_curve[i, 1] = round(pr_curve[i, 1] / count_face, 4)
          _pr_curve[i, 0] = pr_curve[i, 1] / pr_curve[i, 0]
          _pr_curve[i, 1] = pr_curve[i, 1] / count_face
      return _pr_curve
  
imports: from __future__ import absolute_import
  import os
  import tqdm
  import pickle
  import datetime
  import argparse
  import numpy
  from scipy.io import loadmat
label_desc: Use image node_id 13 for calling a global function with example usage: dataset_pr_info(thresh_num, pr_curve, count_face) and returns: _pr_curve