class_docstr: Convert between text-label and text-index 
class_docstr_tok: ["Convert","between","text-label","and","text-index"]
code: def __init__(self, character, separator_list={}, dict_pathlist={}):
      # character (str): set of the possible characters.
      dict_character = list(character)
  
      self.dict = {}
      for i, char in enumerate(dict_character):
          self.dict[char] = i + 1
  
      self.character = [
          "[blank]"
      ] + dict_character  # dummy '[blank]' token for CTCLoss (index 0)
  
      self.separator_list = separator_list
      separator_char = []
      for lang, sep in separator_list.items():
          separator_char += sep
      self.ignore_idx = [0] + [
          i + 1 for i, item in enumerate(separator_char)
      ]
  
      ####### latin dict
      if len(separator_list) == 0:
          dict_list = []
          for lang, dict_path in dict_pathlist.items():
              try:
                  with open(
                      dict_path, "r", encoding="utf-8-sig"
                  ) as input_file:
                      word_count = input_file.read().splitlines()
                  dict_list += word_count
              except:
                  pass
      else:
          dict_list = {}
          for lang, dict_path in dict_pathlist.items():
              with open(
                  dict_path, "r", encoding="utf-8-sig"
              ) as input_file:
                  word_count = input_file.read().splitlines()
              dict_list[lang] = word_count
  
      self.dict_list = dict_list
  
imports: from __future__ import print_function
  import torch
  import pickle
  import numpy
  import math
  import cv2
  from PIL import Image, JpegImagePlugin
  from scipy import ndimage
  import hashlib
  import sys, os
  from zipfile import ZipFile
  from .imgproc import loadImage
label_desc: Use image node_id 1 to create a new CTCLabelConverter object from inherited base classes: object with example: obj = CTCLabelConverter(character, separator_list, dict_pathlist)