code: def convert_annotations(root_path, split):
      """Convert original annotations to mmocr format.
  
      The annotation format of this dataset is as the following:
          word_1.png, "flying"
          word_2.png, "today"
          word_3.png, "means"
      See the format of converted annotation in mmocr.utils.dump_ocr_data.
  
      Args:
          root_path (str): The root path of the dataset
          split (str): The split of dataset. Namely: Train or Test
      """
      assert isinstance(root_path, str)
      assert isinstance(split, str)
  
      img_info = []
      with open(
          osp.join(
              root_path,
              "annotations",
              f"Challenge1_{split}_Task3_GT.txt",
          ),
          encoding='"utf-8-sig',
      ) as f:
          annos = f.readlines()
      for anno in annos:
          # text may contain comma ','
          dst_img_name, word = anno.split(', "')
          word = word.replace('"\n', "")
  
          img_info.append(
              {"file_name": dst_img_name, "anno_info": [{"text": word}]}
          )
  
      return img_info
  
imports: import argparse
  import os.path
  from mmocr.utils import dump_ocr_data
label_desc: Use image node_id 1 for calling a global function with example usage: convert_annotations(root_path, split) and returns: img_info