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