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import re |
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import numpy as np |
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class BaseRecLabelDecode(object): |
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"""Convert between text-label and text-index.""" |
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def __init__(self, character_dict_path=None, use_space_char=False): |
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self.beg_str = 'sos' |
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self.end_str = 'eos' |
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self.reverse = False |
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self.character_str = [] |
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if character_dict_path is None: |
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self.character_str = '0123456789abcdefghijklmnopqrstuvwxyz' |
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dict_character = list(self.character_str) |
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else: |
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with open(character_dict_path, 'rb') as fin: |
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lines = fin.readlines() |
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for line in lines: |
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line = line.decode('utf-8').strip('\n').strip('\r\n') |
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self.character_str.append(line) |
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if use_space_char: |
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self.character_str.append(' ') |
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dict_character = list(self.character_str) |
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if 'arabic' in character_dict_path: |
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self.reverse = True |
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dict_character = self.add_special_char(dict_character) |
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self.dict = {} |
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for i, char in enumerate(dict_character): |
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self.dict[char] = i |
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self.character = dict_character |
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def pred_reverse(self, pred): |
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pred_re = [] |
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c_current = '' |
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for c in pred: |
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if not bool(re.search('[a-zA-Z0-9 :*./%+-]', c)): |
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if c_current != '': |
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pred_re.append(c_current) |
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pred_re.append(c) |
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c_current = '' |
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else: |
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c_current += c |
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if c_current != '': |
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pred_re.append(c_current) |
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return ''.join(pred_re[::-1]) |
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def add_special_char(self, dict_character): |
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return dict_character |
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def decode(self, text_index, text_prob=None, is_remove_duplicate=False): |
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"""convert text-index into text-label.""" |
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result_list = [] |
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ignored_tokens = self.get_ignored_tokens() |
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batch_size = len(text_index) |
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for batch_idx in range(batch_size): |
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selection = np.ones(len(text_index[batch_idx]), dtype=bool) |
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if is_remove_duplicate: |
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selection[1:] = text_index[batch_idx][1:] != text_index[ |
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batch_idx][:-1] |
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for ignored_token in ignored_tokens: |
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selection &= text_index[batch_idx] != ignored_token |
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char_list = [ |
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self.character[text_id] |
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for text_id in text_index[batch_idx][selection] |
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] |
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if text_prob is not None: |
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conf_list = text_prob[batch_idx][selection] |
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else: |
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conf_list = [1] * len(selection) |
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if len(conf_list) == 0: |
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conf_list = [0] |
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text = ''.join(char_list) |
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if self.reverse: |
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text = self.pred_reverse(text) |
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result_list.append((text, np.mean(conf_list).tolist())) |
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return result_list |
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def get_ignored_tokens(self): |
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return [0] |
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def get_character_num(self): |
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return len(self.character) |
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class CTCLabelDecode(BaseRecLabelDecode): |
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"""Convert between text-label and text-index.""" |
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def __init__(self, |
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character_dict_path=None, |
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use_space_char=False, |
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**kwargs): |
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super(CTCLabelDecode, self).__init__(character_dict_path, |
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use_space_char) |
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def __call__(self, preds, batch=None, **kwargs): |
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if kwargs.get('torch_tensor', True): |
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preds = preds.detach().cpu().numpy() |
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preds_idx = preds.argmax(axis=2) |
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preds_prob = preds.max(axis=2) |
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text = self.decode(preds_idx, preds_prob, is_remove_duplicate=True) |
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if batch is None: |
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return text |
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label = self.decode(batch[1]) |
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return text, label |
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def add_special_char(self, dict_character): |
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dict_character = ['blank'] + dict_character |
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return dict_character |
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