docstr: Decoding algorithm of the individual CTCDecoder. This abstract function is reimplemented
  by the DefaultCTCDecoder and the FuzzyCTCDecoder.
  
  Parameters
  ----------
  probabilities : array_like
      Prediction probabilities of the neural net to decode or shape (length x character probability).
      The blank index must be 0.
  
  Returns
  -------
      a Prediction object
docstr_tok: ["Decoding","algorithm","of","the","individual","CTCDecoder",".","This","abstract","function","is","reimplemented","by","the","DefaultCTCDecoder","and","the","FuzzyCTCDecoder",".","Parameters","--","--","--","--","--","probabilities",":","array_like","Prediction","probabilities","of","the","neural","net","to","decode","or","shape","(","length","x","character","probability",")",".","The","blank","index","must","be","0",".","Returns","--","--","--","-","a","Prediction","object"]
code: def decode(self, probabilities):
      """
      Decoding algorithm of the individual CTCDecoder. This abstract function is reimplemented
      by the DefaultCTCDecoder and the FuzzyCTCDecoder.
  
      Parameters
      ----------
      probabilities : array_like
          Prediction probabilities of the neural net to decode or shape (length x character probability).
          The blank index must be 0.
  
      Returns
      -------
          a Prediction object
      """
      return Prediction()
  
file_path: calamari/calamari_ocr/ocr/model/ctcdecoder/ctc_decoder.py
imports: from abc import ABC, abstractmethod
  from dataclasses import field, dataclass
  from typing import List
  import numpy
  from paiargparse import pai_dataclass
  from tfaip.util.enum import StrEnum
  from calamari_ocr.ocr.predict.params import Prediction, PredictionPosition, PredictionCharacter
label_desc: Use image node_id 2 for calling the CTCDecoder obj's underlying member method code with example usage: obj.decode(probabilities) and returns: Prediction