code: def load_prescription_cleval_gt(dataFolder):
      total_img_path = []
      total_gt_path = []
      for root, directories, files in os.walk(dataFolder):
          for file in files:
              if ".jpg" in file:
                  img_path = os.path.join(root, file)
                  total_img_path.append(img_path)
              if "_cl.txt" in file:
                  gt_path = os.path.join(root, file)
                  total_gt_path.append(gt_path)
  
      total_imgs_parsing_bboxes = []
      for img_path, gt_path in zip(
          sorted(total_img_path), sorted(total_gt_path)
      ):
          # check file
  
          assert (
              img_path.split(".jpg")[0]
              == gt_path.split("_label_cl.txt")[0]
          )
  
          lines = open(gt_path, encoding="utf-8").readlines()
          word_bboxes = []
  
          for line in lines:
              box_info_dict = {
                  "points": None,
                  "text": None,
                  "ignore": None,
              }
              box_info = (
                  line.strip()
                  .encode("utf-8")
                  .decode("utf-8-sig")
                  .split(",")
              )
  
              box_points = [int(box_info[i]) for i in range(8)]
              box_info_dict["points"] = np.array(box_points)
  
              word_bboxes.append(box_info_dict)
          total_imgs_parsing_bboxes.append(word_bboxes)
  
      return total_imgs_parsing_bboxes, sorted(total_img_path)
  
imports: import os
  import re
  import itertools
  import cv2
  import time
  import numpy
  import torch
  from torch.autograd import Variable
  from utils.craft_utils import getDetBoxes, adjustResultCoordinates
  from data import imgproc
  from data.dataset import SynthTextDataSet
  import math
  import xml.etree.ElementTree
label_desc: Use image node_id 5 for calling a global function with example usage: load_prescription_cleval_gt(dataFolder) and returns: total_imgs_parsing_bboxes,  sorted