200 lines
6.8 KiB
Python
200 lines
6.8 KiB
Python
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import numpy as np
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from ppocr.utils.logging import get_logger
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class DetLabelEncode(object):
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def __init__(self, **kwargs):
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pass
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def __call__(self, data):
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import json
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label = data['label']
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label = json.loads(label)
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nBox = len(label)
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boxes, txts, txt_tags = [], [], []
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for bno in range(0, nBox):
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box = label[bno]['points']
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txt = label[bno]['transcription']
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boxes.append(box)
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txts.append(txt)
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if txt in ['*', '###']:
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txt_tags.append(True)
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else:
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txt_tags.append(False)
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boxes = np.array(boxes, dtype=np.float32)
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txt_tags = np.array(txt_tags, dtype=np.bool)
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data['polys'] = boxes
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data['texts'] = txts
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data['ignore_tags'] = txt_tags
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return data
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def order_points_clockwise(self, pts):
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rect = np.zeros((4, 2), dtype="float32")
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s = pts.sum(axis=1)
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rect[0] = pts[np.argmin(s)]
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rect[2] = pts[np.argmax(s)]
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diff = np.diff(pts, axis=1)
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rect[1] = pts[np.argmin(diff)]
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rect[3] = pts[np.argmax(diff)]
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return rect
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class BaseRecLabelEncode(object):
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""" Convert between text-label and text-index """
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def __init__(self,
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max_text_length,
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character_dict_path=None,
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character_type='ch',
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use_space_char=False):
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support_character_type = ['ch', 'en', 'en_sensitive']
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assert character_type in support_character_type, "Only {} are supported now but get {}".format(
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support_character_type, self.character_str)
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self.max_text_len = max_text_length
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if character_type == "en":
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self.character_str = "0123456789abcdefghijklmnopqrstuvwxyz"
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dict_character = list(self.character_str)
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elif character_type == "ch":
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self.character_str = ""
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assert character_dict_path is not None, "character_dict_path should not be None when character_type is ch"
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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 += line
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if use_space_char:
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self.character_str += " "
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dict_character = list(self.character_str)
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elif character_type == "en_sensitive":
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# same with ASTER setting (use 94 char).
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import string
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self.character_str = string.printable[:-6]
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dict_character = list(self.character_str)
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self.character_type = character_type
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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 add_special_char(self, dict_character):
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return dict_character
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def encode(self, text):
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"""convert text-label into text-index.
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input:
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text: text labels of each image. [batch_size]
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output:
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text: concatenated text index for CTCLoss.
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[sum(text_lengths)] = [text_index_0 + text_index_1 + ... + text_index_(n - 1)]
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length: length of each text. [batch_size]
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"""
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if len(text) > self.max_text_len:
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return None
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if self.character_type == "en":
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text = text.lower()
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text_list = []
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for char in text:
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if char not in self.dict:
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# logger = get_logger()
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# logger.warning('{} is not in dict'.format(char))
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continue
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text_list.append(self.dict[char])
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if len(text_list) == 0:
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return None
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return text_list
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def get_ignored_tokens(self):
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return [0] # for ctc blank
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class CTCLabelEncode(BaseRecLabelEncode):
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""" Convert between text-label and text-index """
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def __init__(self,
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max_text_length,
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character_dict_path=None,
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character_type='ch',
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use_space_char=False,
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**kwargs):
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super(CTCLabelEncode,
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self).__init__(max_text_length, character_dict_path,
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character_type, use_space_char)
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def __call__(self, data):
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text = data['label']
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text = self.encode(text)
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if text is None:
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return None
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if len(text) > self.max_text_len:
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return None
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data['length'] = np.array(len(text))
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text = text + [0] * (self.max_text_len - len(text))
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data['label'] = np.array(text)
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return data
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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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class AttnLabelEncode(BaseRecLabelEncode):
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""" Convert between text-label and text-index """
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def __init__(self,
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max_text_length,
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character_dict_path=None,
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character_type='ch',
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use_space_char=False,
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**kwargs):
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super(AttnLabelEncode,
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self).__init__(max_text_length, character_dict_path,
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character_type, use_space_char)
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self.beg_str = "sos"
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self.end_str = "eos"
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def add_special_char(self, dict_character):
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dict_character = [self.beg_str, self.end_str] + dict_character
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return dict_character
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def __call__(self, text):
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text = self.encode(text)
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return text
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def get_ignored_tokens(self):
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beg_idx = self.get_beg_end_flag_idx("beg")
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end_idx = self.get_beg_end_flag_idx("end")
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return [beg_idx, end_idx]
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def get_beg_end_flag_idx(self, beg_or_end):
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if beg_or_end == "beg":
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idx = np.array(self.dict[self.beg_str])
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elif beg_or_end == "end":
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idx = np.array(self.dict[self.end_str])
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else:
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assert False, "Unsupport type %s in get_beg_end_flag_idx" \
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% beg_or_end
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return idx
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