code: def load_txt_info(gt_file, img_info):
      """Collect the annotation information.
  
      The annotation format is as the following:
      x1,y1,x2,y2,x3,y3,x4,y4,text
  
      45.45,226.83,11.87,181.79,183.84,13.1,233.79,49.95,时尚袋袋
      345.98,311.18,345.98,347.21,462.26,347.21,462.26,311.18,73774
      462.26,292.34,461.44,299.71,502.39,299.71,502.39,292.34,73/74/737
  
      Args:
          gt_file (str): The path to ground-truth
          img_info (dict): The dict of the img and annotation information
  
      Returns:
          img_info (dict): The dict of the img and annotation information
      """
  
      anno_info = []
      with open(gt_file) as f:
          lines = f.readlines()
      for line in lines:
          points = line.split(",")[0:8]
          word = line.split(",")[8].rstrip("\n")
          if word == "###":
              continue
          bbox = [math.floor(float(pt)) for pt in points]
          anno = dict(bbox=bbox, word=word)
          anno_info.append(anno)
  
      img_info.update(anno_info=anno_info)
  
      return img_info
  
file_path: mmocr/tools/dataset_converters/textrecog/mtwi_converter.py
imports: import argparse
  import math
  import os
  import os.path
  import cv2
  import mmcv
  import mmengine
  from PIL import Image
  from mmocr.utils import crop_img, dump_ocr_data
label_desc: Use image node_id 4 for calling a global function with example usage: load_txt_info(gt_file, img_info) and returns: img_info