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import copy
import random
import numpy as np
from openrec.preprocess.ctc_label_encode import BaseRecLabelEncode
class IGTRLabelEncode(BaseRecLabelEncode):
"""Convert between text-label and text-index."""
def __init__(self,
max_text_length,
character_dict_path=None,
use_space_char=False,
k=1,
ch=False,
prompt_error=False,
**kwargs):
super(IGTRLabelEncode,
self).__init__(max_text_length, character_dict_path,
use_space_char)
self.ignore_index = self.dict['<pad>']
self.k = k
self.prompt_error = prompt_error
self.ch = ch
rare_file = kwargs.get('rare_file', None)
siml_file = kwargs.get('siml_file', None)
siml_char_dict = {}
siml_char_list = [0 for _ in range(self.num_character)]
if siml_file is not None:
with open(siml_file, 'r') as f:
for lin in f.readlines():
lin_s = lin.strip().split('\t')
char_siml = lin_s[0]
if char_siml in self.dict:
siml_list = []
siml_prob = []
for i in range(1, len(lin_s), 2):
c = lin_s[i]
prob = int(lin_s[i + 1])
if c in self.dict and prob >= 1:
siml_list.append(self.dict[c])
siml_prob.append(prob)
siml_prob = np.array(siml_prob,
dtype=np.float32) / sum(siml_prob)
siml_char_dict[self.dict[char_siml]] = [
siml_list, siml_prob.tolist()
]
siml_char_list[self.dict[char_siml]] = 1
self.siml_char_dict = siml_char_dict
self.siml_char_list = siml_char_list
rare_char_list = [0 for _ in range(self.num_character)]
if rare_file is not None:
with open(rare_file, 'r') as f:
for lin in f.readlines():
lin_s = lin.strip().split('\t')
# print(lin_s)
char_rare = lin_s[0]
num_appear = int(lin_s[1])
if char_rare in self.dict and num_appear < 1000:
rare_char_list[self.dict[char_rare]] = 1
self.rare_char_list = rare_char_list # [self.dict[char] for char in rare_char_list]
def __call__(self, data):
text = data['label'] # coffee
encoder_result = self.encode(text)
if encoder_result is None:
return None
text, text_char_num, ques_list_s, prompt_list_s = encoder_result
if len(text) > self.max_text_len:
return None
data['length'] = np.array(len(text))
text = [self.dict['<s>']] + text + [self.dict['</s>']]
text = text + [self.dict['<pad>']
] * (self.max_text_len + 2 - len(text))
data['label'] = np.array(text) # 6
ques_len_list = []
ques2_len_list = []
prompt_len_list = []
prompt_pos_idx_list = []
prompt_char_idx_list = []
ques_pos_idx_list = []
ques1_answer_list = []
ques2_char_idx_list = []
ques2_answer_list = []
ques4_char_num_list = []
train_step = 0
for prompt_list, ques_list in zip(prompt_list_s, ques_list_s):
prompt_len = len(prompt_list) + 1
prompt_len_list.append(prompt_len)
prompt_list = np.array(
[[0, self.dict['<s>'], 0]] + prompt_list +
[[self.max_text_len + 2, self.dict['<pad>'], 0]] *
(self.max_text_len - len(prompt_list)))
prompt_pos_idx_list.append(prompt_list[:, 0])
prompt_char_idx_list.append(prompt_list[:, 1])
ques_len = len(ques_list)
ques_len_list.append(ques_len)
ques_list = np.array(
ques_list + [[self.max_text_len + 2, self.dict['<pad>'], 0]] *
(self.max_text_len + 1 - ques_len))
ques_pos_idx_list.append(ques_list[:, 0])
# what is the first and third char?
# Is the first character 't'? and Is the third character 'f'?
# How many 'c', 's' and 'f' are there in the text image?
ques1_answer_list.append(ques_list[:, 1])
ques2_char_idx = copy.deepcopy(ques_list[:ques_len, :2])
new_ques2_char_idx = []
ques2_answer = []
for q_2, ques2_idx in enumerate(ques2_char_idx.tolist()):
if (train_step == 2 or train_step == 3) and q_2 == ques_len - 1:
new_ques2_char_idx.append(ques2_idx)
ques2_answer.append(1)
continue
if ques2_idx[1] != self.dict['<pad>'] and random.random() > 0.5:
select_idx = random.randint(0, self.num_character - 3)
new_ques2_char_idx.append([ques2_idx[0], select_idx])
if select_idx == ques2_idx[1]:
ques2_answer.append(1)
else:
ques2_answer.append(0)
if self.siml_char_list[
ques2_idx[1]] == 1 and random.random() > 0.5:
select_idx_sim_list = random.sample(
self.siml_char_dict[ques2_idx[1]][0],
min(3, len(self.siml_char_dict[ques2_idx[1]][0])),
)
for select_idx in select_idx_sim_list:
new_ques2_char_idx.append(
[ques2_idx[0], select_idx])
if select_idx == ques2_idx[1]:
ques2_answer.append(1)
else:
ques2_answer.append(0)
else:
new_ques2_char_idx.append(ques2_idx)
ques2_answer.append(1)
ques2_len_list.append(len(new_ques2_char_idx))
ques2_char_idx_new = np.array(
new_ques2_char_idx +
[[self.max_text_len + 2, self.dict['<pad>']]] *
(self.max_text_len * 4 + 1 - len(new_ques2_char_idx)))
ques2_answer = np.array(
ques2_answer + [0] *
(self.max_text_len * 4 + 1 - len(ques2_answer)))
ques2_char_idx_list.append(ques2_char_idx_new)
ques2_answer_list.append(ques2_answer)
ques4_char_num_list.append(ques_list[:, 2])
train_step += 1
data['ques_len_list'] = np.array(ques_len_list, dtype=np.int64)
data['ques2_len_list'] = np.array(ques2_len_list, dtype=np.int64)
data['prompt_len_list'] = np.array(prompt_len_list, dtype=np.int64)
data['prompt_pos_idx_list'] = np.array(prompt_pos_idx_list,
dtype=np.int64)
data['prompt_char_idx_list'] = np.array(prompt_char_idx_list,
dtype=np.int64)
data['ques_pos_idx_list'] = np.array(ques_pos_idx_list, dtype=np.int64)
data['ques1_answer_list'] = np.array(ques1_answer_list, dtype=np.int64)
data['ques2_char_idx_list'] = np.array(ques2_char_idx_list,
dtype=np.int64)
data['ques2_answer_list'] = np.array(ques2_answer_list,
dtype=np.float32)
data['ques3_answer'] = np.array(
text_char_num,
dtype=np.int64) # np.array([1, 0, 2]) # answer 1, 0, 2
data['ques4_char_num_list'] = np.array(ques4_char_num_list)
return data
def add_special_char(self, dict_character):
dict_character = ['</s>'] + dict_character + ['<s>'] + ['<pad>']
self.num_character = len(dict_character)
return dict_character
def encode(self, text):
"""convert text-label into text-index.
input:
text: text labels of each image. [batch_size]
output:
text: concatenated text index for CTCLoss.
[sum(text_lengths)] = [text_index_0 + text_index_1 + ... + text_index_(n - 1)]
length: length of each text. [batch_size]
"""
if len(text) == 0:
return None
if self.lower:
text = text.lower()
char_num = [0 for _ in range(self.num_character - 2)]
char_num[0] = 1
text_list = []
qa_text = []
pos_i = 0
rare_char_qa = []
unrare_char_qa = []
for char in text:
if char not in self.dict:
continue
char_id = self.dict[char]
text_list.append(char_id)
qa_text.append([pos_i + 1, char_id, char_num[char_id]])
if self.rare_char_list[char_id] == 1:
rare_char_qa.append([pos_i + 1, char_id, char_num[char_id]])
else:
unrare_char_qa.append([pos_i + 1, char_id, char_num[char_id]])
char_num[char_id] += 1
pos_i += 1
if self.ch:
char_num_ch = []
char_num_ch_none = []
rare_char_num_ch_none = []
for i, num in enumerate(char_num):
if self.rare_char_list[i] == 1:
rare_char_num_ch_none.append([i, num])
if num > 0:
char_num_ch.append([i, num])
else:
char_num_ch_none.append([i, 0])
none_char_index = random.sample(
char_num_ch_none,
min(37 - len(char_num_ch), len(char_num_ch_none)))
if len(rare_char_num_ch_none) > 0:
none_rare_char_index = random.sample(
rare_char_num_ch_none,
min(40 - len(char_num_ch) - len(none_char_index),
len(rare_char_num_ch_none)),
)
char_num_ch = char_num_ch + none_char_index + none_rare_char_index
else:
char_num_ch = char_num_ch + none_char_index
char_num_ch.sort(key=lambda x: x[0])
char_num = char_num_ch
len_ = len(text_list)
if len_ == 0:
return None
ques_list = [
qa_text + [[pos_i + 1, self.dict['</s>'], 0]],
[[pos_i + 1, self.dict['</s>'], 0]],
]
prompt_list = [qa_text[len_:], qa_text]
if len_ == 1:
ques_list.append([[self.max_text_len + 1, self.dict['</s>'], 0]])
prompt_list.append(
[[self.max_text_len + 2, self.dict['<pad>'], 0]] * 4 + qa_text)
for _ in range(1, self.k):
ques_list.append(
[[self.max_text_len + 2, self.dict['<pad>'], 0]])
prompt_list.append(qa_text[1:])
else:
next_id = random.sample(range(1, len_ + 1), 2)
for slice_id in next_id:
b_i = slice_id - 5 if slice_id - 5 > 0 else 0
if slice_id == len_:
ques_list.append(
[[self.max_text_len + 1, self.dict['</s>'], 0]])
else:
ques_list.append(
qa_text[slice_id:] +
[[self.max_text_len + 1, qa_text[slice_id][1], 0]])
prompt_list.append(
[[self.max_text_len + 2, self.dict['<pad>'], 0]] *
(5 - slice_id + b_i) + qa_text[b_i:slice_id])
shuffle_id1 = random.sample(range(1, len_),
2) if len_ > 2 else [1, 0]
for slice_id in shuffle_id1:
if slice_id == 0:
ques_list.append(
[[self.max_text_len + 2, self.dict['<pad>'], 0]])
prompt_list.append(qa_text[:0])
else:
ques_list.append(qa_text[slice_id:] +
[[pos_i + 1, self.dict['</s>'], 0]])
prompt_list.append(qa_text[:slice_id])
if len_ > 2:
shuffle_id2 = random.sample(
range(1, len_),
self.k - 4 if len_ - 1 > self.k - 4 else len_ - 1)
if self.k - 4 != len(shuffle_id2):
shuffle_id2 += random.sample(range(1, len_),
self.k - 4 - len(shuffle_id2))
rare_slice_id = len(rare_char_qa)
unrare_slice_id = len(unrare_char_qa)
for slice_id in shuffle_id2:
random.shuffle(qa_text)
if len(rare_char_qa) > 0 and random.random() < 0.5:
ques_list.append(rare_char_qa[:rare_slice_id] +
unrare_char_qa[unrare_slice_id:] +
[[pos_i + 1, self.dict['</s>'], 0]])
if len(unrare_char_qa[:unrare_slice_id]) > 0:
prompt_list1 = random.sample(
unrare_char_qa[:unrare_slice_id],
random.randint(
1, len(unrare_char_qa[:unrare_slice_id]))
if len(unrare_char_qa[:unrare_slice_id]) > 1
else 1,
)
else:
prompt_list1 = []
if len(rare_char_qa[rare_slice_id:]) > 0:
prompt_list2 = random.sample(
rare_char_qa[rare_slice_id:],
random.randint(
1,
len(rare_char_qa[rare_slice_id:])
if len(rare_char_qa[rare_slice_id:]) > 1
else 1,
),
)
else:
prompt_list2 = []
prompt_list.append(prompt_list1 + prompt_list2)
random.shuffle(rare_char_qa)
random.shuffle(unrare_char_qa)
rare_slice_id = random.randint(
1,
len(rare_char_qa)) if len(rare_char_qa) > 1 else 1
unrare_slice_id = random.randint(
1, len(unrare_char_qa)
) if len(unrare_char_qa) > 1 else 1
else:
ques_list.append(qa_text[slice_id:] +
[[pos_i + 1, self.dict['</s>'], 0]])
prompt_list.append(qa_text[:slice_id])
else:
ques_list.append(qa_text[1:] +
[[pos_i + 1, self.dict['</s>'], 0]])
prompt_list.append(qa_text[:1])
ques_list.append(qa_text[:1] +
[[pos_i + 1, self.dict['</s>'], 0]])
prompt_list.append(qa_text[1:])
ques_list += [[[self.max_text_len + 2, self.dict['<pad>'], 0]]
] * (self.k - 6)
prompt_list += [qa_text[:0]] * (self.k - 6)
return text_list, char_num, ques_list, prompt_list
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