code: def ctc_decoder_for_image(
      gather_info_list,
      logits_map,
      Lexicon_Table,
      pts_num=6,
      point_gather_mode=None,
  ):
      """
      CTC decoder using multiple processes.
      """
      decoder_str = []
      decoder_xys = []
      for gather_info in gather_info_list:
          if len(gather_info) < pts_num:
              continue
          dst_str, xys_list = instance_ctc_greedy_decoder(
              gather_info,
              logits_map,
              pts_num=pts_num,
              point_gather_mode=point_gather_mode,
          )
          dst_str_readable = "".join(
              [Lexicon_Table[idx] for idx in dst_str]
          )
          if len(dst_str_readable) < 2:
              continue
          decoder_str.append(dst_str_readable)
          decoder_xys.append(xys_list)
      return decoder_str, decoder_xys
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import cv2
  import math
  import numpy
  from itertools import groupby
  from skimage.morphology._skeletonize import thin
label_desc: Use image node_id 8 for calling a global function with example usage: ctc_decoder_for_image(gather_info_list, logits_map, Lexicon_Table, pts_num, point_gather_mode) and returns: decoder_str,  decoder_xys