code: def load_txt_info(gt_file, img_info):
      """Collect the annotation information.
  
      The annotation format is as the following:
      left, top, right, bottom, "transcription"
  
      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:
              xmin, ymin, xmax, ymax = line.split(",")[0:4]
              x = max(0, int(xmin))
              y = max(0, int(ymin))
              w = int(xmax) - x
              h = int(ymax) - y
              bbox = [x, y, w, h]
              segmentation = [x, y, x + w, y, x + w, y + h, x, y + h]
  
              anno = dict(
                  iscrowd=0,
                  category_id=1,
                  bbox=bbox,
                  area=w * h,
                  segmentation=[segmentation],
              )
              anno_info.append(anno)
      img_info.update(anno_info=anno_info)
  
      return img_info
  
file_path: mmocr/tools/dataset_converters/textdet/ic11_converter.py
imports: import argparse
  import os
  import os.path
  import mmcv
  import mmengine
  from PIL import Image
  from mmocr.utils import dump_ocr_data
label_desc: Use image node_id 5 for calling a global function with example usage: load_txt_info(gt_file, img_info) and returns: img_info