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)
  
      # special_character = ['\xa2', '\xa3', '\xa4','\xa5']
      # self.separator_char = special_character[:len(separator)]
  
      self.dict = {}
      # for i, char in enumerate(self.separator_char + dict_character):
      for i, char in enumerate(dict_character):
          # NOTE: 0 is reserved for 'blank' token required by CTCLoss
          self.dict[char] = i + 1
  
      self.character = [
          "[blank]"
      ] + dict_character  # dummy '[blank]' token for CTCLoss (index 0)
      # self.character = ['[blank]']+ self.separator_char + 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)
      ]
  
      dict_list = {}
      for lang, dict_path in dict_pathlist.items():
          with open(dict_path, "rb") as input_file:
              word_count = pickle.load(input_file)
          dict_list[lang] = word_count
      self.dict_list = dict_list
  
imports: import torch
  import pickle
  import numpy
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)