595 lines
24 KiB
Python
595 lines
24 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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import os
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import sys
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import importlib
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__dir__ = os.path.dirname(__file__)
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import paddle
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sys.path.append(os.path.join(__dir__, ''))
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import cv2
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import logging
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import numpy as np
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from pathlib import Path
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tools = importlib.import_module('.', 'tools')
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ppocr = importlib.import_module('.', 'ppocr')
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ppstructure = importlib.import_module('.', 'ppstructure')
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from tools.infer import predict_system
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from ppocr.utils.logging import get_logger
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logger = get_logger()
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from ppocr.utils.utility import check_and_read_gif, get_image_file_list
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from ppocr.utils.network import maybe_download, download_with_progressbar, is_link, confirm_model_dir_url
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from tools.infer.utility import draw_ocr, str2bool, check_gpu
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from ppstructure.utility import init_args, draw_structure_result
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from ppstructure.predict_system import StructureSystem, save_structure_res
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__all__ = [
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'PaddleOCR', 'PPStructure', 'draw_ocr', 'draw_structure_result',
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'save_structure_res', 'download_with_progressbar'
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]
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SUPPORT_DET_MODEL = ['DB']
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VERSION = '2.5.0.3'
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SUPPORT_REC_MODEL = ['CRNN', 'SVTR_LCNet']
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BASE_DIR = os.path.expanduser("~/.paddleocr/")
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DEFAULT_OCR_MODEL_VERSION = 'PP-OCRv3'
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SUPPORT_OCR_MODEL_VERSION = ['PP-OCR', 'PP-OCRv2', 'PP-OCRv3']
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DEFAULT_STRUCTURE_MODEL_VERSION = 'PP-STRUCTURE'
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SUPPORT_STRUCTURE_MODEL_VERSION = ['PP-STRUCTURE']
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MODEL_URLS = {
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'OCR': {
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'PP-OCRv3': {
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'det': {
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'ch': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar',
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},
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'en': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar',
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},
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'ml': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar'
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}
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},
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'rec': {
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'ch': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
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},
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'en': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/en_dict.txt'
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},
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'korean': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/korean_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/korean_dict.txt'
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},
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'japan': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/japan_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/japan_dict.txt'
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},
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'chinese_cht': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/chinese_cht_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt'
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},
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'ta': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ta_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/ta_dict.txt'
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},
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'te': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/te_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/te_dict.txt'
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},
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'ka': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ka_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/ka_dict.txt'
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},
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'latin': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/latin_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/latin_dict.txt'
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},
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'arabic': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/arabic_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/arabic_dict.txt'
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},
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'cyrillic': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/cyrillic_dict.txt'
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},
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'devanagari': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/devanagari_PP-OCRv3_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/devanagari_dict.txt'
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},
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},
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'cls': {
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'ch': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar',
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}
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},
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},
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'PP-OCRv2': {
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'det': {
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'ch': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar',
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},
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},
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'rec': {
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'ch': {
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'url':
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'https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar',
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'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
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}
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}
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},
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'PP-OCR': {
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'det': {
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'ch': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar',
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},
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'en': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_ppocr_mobile_v2.0_det_infer.tar',
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},
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'structure': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar'
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}
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},
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'rec': {
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'ch': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
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},
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'en': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/en_dict.txt'
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},
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'french': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/french_dict.txt'
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},
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'german': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/german_dict.txt'
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},
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'korean': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/korean_dict.txt'
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},
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'japan': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/japan_dict.txt'
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},
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'chinese_cht': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt'
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},
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'ta': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/ta_dict.txt'
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},
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'te': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/te_dict.txt'
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},
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'ka': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/ka_dict.txt'
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},
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'latin': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/latin_dict.txt'
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},
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'arabic': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/arabic_dict.txt'
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},
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'cyrillic': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/cyrillic_dict.txt'
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},
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'devanagari': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar',
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'dict_path': './ppocr/utils/dict/devanagari_dict.txt'
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},
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'structure': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar',
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'dict_path': 'ppocr/utils/dict/table_dict.txt'
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}
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},
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'cls': {
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'ch': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar',
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}
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},
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}
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},
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'STRUCTURE': {
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'PP-STRUCTURE': {
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'table': {
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'en': {
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'url':
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'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar',
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'dict_path': 'ppocr/utils/dict/table_structure_dict.txt'
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}
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}
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}
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}
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}
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def parse_args(mMain=True):
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import argparse
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parser = init_args()
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parser.add_help = mMain
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parser.add_argument("--lang", type=str, default='ch')
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parser.add_argument("--det", type=str2bool, default=True)
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parser.add_argument("--rec", type=str2bool, default=True)
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parser.add_argument("--type", type=str, default='ocr')
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parser.add_argument(
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"--ocr_version",
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type=str,
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choices=SUPPORT_OCR_MODEL_VERSION,
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default='PP-OCRv3',
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help='OCR Model version, the current model support list is as follows: '
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'1. PP-OCRv3 Support Chinese and English detection and recognition model, and direction classifier model'
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'2. PP-OCRv2 Support Chinese detection and recognition model. '
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'3. PP-OCR support Chinese detection, recognition and direction classifier and multilingual recognition model.'
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)
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parser.add_argument(
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"--structure_version",
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type=str,
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choices=SUPPORT_STRUCTURE_MODEL_VERSION,
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default='PP-STRUCTURE',
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help='Model version, the current model support list is as follows:'
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' 1. STRUCTURE Support en table structure model.')
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for action in parser._actions:
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if action.dest in ['rec_char_dict_path', 'table_char_dict_path']:
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action.default = None
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if mMain:
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return parser.parse_args()
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else:
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inference_args_dict = {}
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for action in parser._actions:
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inference_args_dict[action.dest] = action.default
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return argparse.Namespace(**inference_args_dict)
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def parse_lang(lang):
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latin_lang = [
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'af', 'az', 'bs', 'cs', 'cy', 'da', 'de', 'es', 'et', 'fr', 'ga', 'hr',
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'hu', 'id', 'is', 'it', 'ku', 'la', 'lt', 'lv', 'mi', 'ms', 'mt', 'nl',
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'no', 'oc', 'pi', 'pl', 'pt', 'ro', 'rs_latin', 'sk', 'sl', 'sq', 'sv',
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'sw', 'tl', 'tr', 'uz', 'vi', 'french', 'german'
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]
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arabic_lang = ['ar', 'fa', 'ug', 'ur']
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cyrillic_lang = [
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'ru', 'rs_cyrillic', 'be', 'bg', 'uk', 'mn', 'abq', 'ady', 'kbd', 'ava',
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'dar', 'inh', 'che', 'lbe', 'lez', 'tab'
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]
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devanagari_lang = [
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'hi', 'mr', 'ne', 'bh', 'mai', 'ang', 'bho', 'mah', 'sck', 'new', 'gom',
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'sa', 'bgc'
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]
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if lang in latin_lang:
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lang = "latin"
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elif lang in arabic_lang:
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lang = "arabic"
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elif lang in cyrillic_lang:
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lang = "cyrillic"
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elif lang in devanagari_lang:
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lang = "devanagari"
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assert lang in MODEL_URLS['OCR'][DEFAULT_OCR_MODEL_VERSION][
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'rec'], 'param lang must in {}, but got {}'.format(
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MODEL_URLS['OCR'][DEFAULT_OCR_MODEL_VERSION]['rec'].keys(), lang)
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if lang == "ch":
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det_lang = "ch"
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elif lang == 'structure':
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det_lang = 'structure'
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elif lang in ["en", "latin"]:
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det_lang = "en"
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else:
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det_lang = "ml"
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return lang, det_lang
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def get_model_config(type, version, model_type, lang):
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if type == 'OCR':
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DEFAULT_MODEL_VERSION = DEFAULT_OCR_MODEL_VERSION
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elif type == 'STRUCTURE':
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DEFAULT_MODEL_VERSION = DEFAULT_STRUCTURE_MODEL_VERSION
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else:
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raise NotImplementedError
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model_urls = MODEL_URLS[type]
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if version not in model_urls:
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version = DEFAULT_MODEL_VERSION
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if model_type not in model_urls[version]:
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if model_type in model_urls[DEFAULT_MODEL_VERSION]:
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version = DEFAULT_MODEL_VERSION
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else:
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logger.error('{} models is not support, we only support {}'.format(
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model_type, model_urls[DEFAULT_MODEL_VERSION].keys()))
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sys.exit(-1)
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if lang not in model_urls[version][model_type]:
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if lang in model_urls[DEFAULT_MODEL_VERSION][model_type]:
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version = DEFAULT_MODEL_VERSION
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else:
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logger.error(
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'lang {} is not support, we only support {} for {} models'.
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format(lang, model_urls[DEFAULT_MODEL_VERSION][model_type].keys(
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), model_type))
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sys.exit(-1)
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return model_urls[version][model_type][lang]
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class PaddleOCR(predict_system.TextSystem):
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def __init__(self, **kwargs):
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"""
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paddleocr package
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args:
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**kwargs: other params show in paddleocr --help
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"""
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params = parse_args(mMain=False)
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params.__dict__.update(**kwargs)
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assert params.ocr_version in SUPPORT_OCR_MODEL_VERSION, "ocr_version must in {}, but get {}".format(
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SUPPORT_OCR_MODEL_VERSION, params.ocr_version)
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params.use_gpu = check_gpu(params.use_gpu)
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if not params.show_log:
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logger.setLevel(logging.INFO)
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self.use_angle_cls = params.use_angle_cls
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lang, det_lang = parse_lang(params.lang)
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# init model dir
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det_model_config = get_model_config('OCR', params.ocr_version, 'det',
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det_lang)
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params.det_model_dir, det_url = confirm_model_dir_url(
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params.det_model_dir,
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os.path.join(BASE_DIR, 'whl', 'det', det_lang),
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det_model_config['url'])
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rec_model_config = get_model_config('OCR', params.ocr_version, 'rec',
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lang)
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params.rec_model_dir, rec_url = confirm_model_dir_url(
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params.rec_model_dir,
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os.path.join(BASE_DIR, 'whl', 'rec', lang), rec_model_config['url'])
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cls_model_config = get_model_config('OCR', params.ocr_version, 'cls',
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'ch')
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params.cls_model_dir, cls_url = confirm_model_dir_url(
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params.cls_model_dir,
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os.path.join(BASE_DIR, 'whl', 'cls'), cls_model_config['url'])
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if params.ocr_version == 'PP-OCRv3':
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params.rec_image_shape = "3, 48, 320"
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else:
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params.rec_image_shape = "3, 32, 320"
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# download model
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maybe_download(params.det_model_dir, det_url)
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maybe_download(params.rec_model_dir, rec_url)
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maybe_download(params.cls_model_dir, cls_url)
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if params.det_algorithm not in SUPPORT_DET_MODEL:
|
||
logger.error('det_algorithm must in {}'.format(SUPPORT_DET_MODEL))
|
||
sys.exit(0)
|
||
if params.rec_algorithm not in SUPPORT_REC_MODEL:
|
||
logger.error('rec_algorithm must in {}'.format(SUPPORT_REC_MODEL))
|
||
sys.exit(0)
|
||
|
||
if params.rec_char_dict_path is None:
|
||
params.rec_char_dict_path = str(
|
||
Path(__file__).parent / rec_model_config['dict_path'])
|
||
|
||
logger.debug(params)
|
||
# init det_model and rec_model
|
||
super().__init__(params)
|
||
|
||
def ocr(self, img, det=True, rec=True, cls=True):
|
||
"""
|
||
ocr with paddleocr
|
||
args：
|
||
img: img for ocr, support ndarray, img_path and list or ndarray
|
||
det: use text detection or not. If false, only rec will be exec. Default is True
|
||
rec: use text recognition or not. If false, only det will be exec. Default is True
|
||
cls: use angle classifier or not. Default is True. If true, the text with rotation of 180 degrees can be recognized. If no text is rotated by 180 degrees, use cls=False to get better performance. Text with rotation of 90 or 270 degrees can be recognized even if cls=False.
|
||
"""
|
||
assert isinstance(img, (np.ndarray, list, str))
|
||
if isinstance(img, list) and det == True:
|
||
logger.error('When input a list of images, det must be false')
|
||
exit(0)
|
||
if cls == True and self.use_angle_cls == False:
|
||
logger.warning(
|
||
'Since the angle classifier is not initialized, the angle classifier will not be uesd during the forward process'
|
||
)
|
||
|
||
if isinstance(img, str):
|
||
# download net image
|
||
if img.startswith('http'):
|
||
download_with_progressbar(img, 'tmp.jpg')
|
||
img = 'tmp.jpg'
|
||
image_file = img
|
||
img, flag = check_and_read_gif(image_file)
|
||
if not flag:
|
||
with open(image_file, 'rb') as f:
|
||
np_arr = np.frombuffer(f.read(), dtype=np.uint8)
|
||
img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
|
||
if img is None:
|
||
logger.error("error in loading image:{}".format(image_file))
|
||
return None
|
||
if isinstance(img, np.ndarray) and len(img.shape) == 2:
|
||
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
|
||
if det and rec:
|
||
dt_boxes, rec_res = self.__call__(img, cls)
|
||
return [[box.tolist(), res] for box, res in zip(dt_boxes, rec_res)]
|
||
elif det and not rec:
|
||
dt_boxes, elapse = self.text_detector(img)
|
||
if dt_boxes is None:
|
||
return None
|
||
return [box.tolist() for box in dt_boxes]
|
||
else:
|
||
if not isinstance(img, list):
|
||
img = [img]
|
||
if self.use_angle_cls and cls:
|
||
img, cls_res, elapse = self.text_classifier(img)
|
||
if not rec:
|
||
return cls_res
|
||
rec_res, elapse = self.text_recognizer(img)
|
||
return rec_res
|
||
|
||
|
||
class PPStructure(StructureSystem):
|
||
def __init__(self, **kwargs):
|
||
params = parse_args(mMain=False)
|
||
params.__dict__.update(**kwargs)
|
||
assert params.structure_version in SUPPORT_STRUCTURE_MODEL_VERSION, "structure_version must in {}, but get {}".format(
|
||
SUPPORT_STRUCTURE_MODEL_VERSION, params.structure_version)
|
||
params.use_gpu = check_gpu(params.use_gpu)
|
||
|
||
if not params.show_log:
|
||
logger.setLevel(logging.INFO)
|
||
lang, det_lang = parse_lang(params.lang)
|
||
|
||
# init model dir
|
||
det_model_config = get_model_config('OCR', params.ocr_version, 'det',
|
||
det_lang)
|
||
params.det_model_dir, det_url = confirm_model_dir_url(
|
||
params.det_model_dir,
|
||
os.path.join(BASE_DIR, 'whl', 'det', det_lang),
|
||
det_model_config['url'])
|
||
rec_model_config = get_model_config('OCR', params.ocr_version, 'rec',
|
||
lang)
|
||
params.rec_model_dir, rec_url = confirm_model_dir_url(
|
||
params.rec_model_dir,
|
||
os.path.join(BASE_DIR, 'whl', 'rec', lang), rec_model_config['url'])
|
||
table_model_config = get_model_config(
|
||
'STRUCTURE', params.structure_version, 'table', 'en')
|
||
params.table_model_dir, table_url = confirm_model_dir_url(
|
||
params.table_model_dir,
|
||
os.path.join(BASE_DIR, 'whl', 'table'), table_model_config['url'])
|
||
# download model
|
||
maybe_download(params.det_model_dir, det_url)
|
||
maybe_download(params.rec_model_dir, rec_url)
|
||
maybe_download(params.table_model_dir, table_url)
|
||
|
||
if params.rec_char_dict_path is None:
|
||
params.rec_char_dict_path = str(
|
||
Path(__file__).parent / rec_model_config['dict_path'])
|
||
if params.table_char_dict_path is None:
|
||
params.table_char_dict_path = str(
|
||
Path(__file__).parent / table_model_config['dict_path'])
|
||
|
||
logger.debug(params)
|
||
super().__init__(params)
|
||
|
||
def __call__(self, img, return_ocr_result_in_table=False):
|
||
if isinstance(img, str):
|
||
# download net image
|
||
if img.startswith('http'):
|
||
download_with_progressbar(img, 'tmp.jpg')
|
||
img = 'tmp.jpg'
|
||
image_file = img
|
||
img, flag = check_and_read_gif(image_file)
|
||
if not flag:
|
||
with open(image_file, 'rb') as f:
|
||
np_arr = np.frombuffer(f.read(), dtype=np.uint8)
|
||
img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
|
||
if img is None:
|
||
logger.error("error in loading image:{}".format(image_file))
|
||
return None
|
||
if isinstance(img, np.ndarray) and len(img.shape) == 2:
|
||
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
|
||
|
||
res = super().__call__(img, return_ocr_result_in_table)
|
||
return res
|
||
|
||
|
||
def main():
|
||
# for cmd
|
||
args = parse_args(mMain=True)
|
||
image_dir = args.image_dir
|
||
if is_link(image_dir):
|
||
download_with_progressbar(image_dir, 'tmp.jpg')
|
||
image_file_list = ['tmp.jpg']
|
||
else:
|
||
image_file_list = get_image_file_list(args.image_dir)
|
||
if len(image_file_list) == 0:
|
||
logger.error('no images find in {}'.format(args.image_dir))
|
||
return
|
||
if args.type == 'ocr':
|
||
engine = PaddleOCR(**(args.__dict__))
|
||
elif args.type == 'structure':
|
||
engine = PPStructure(**(args.__dict__))
|
||
else:
|
||
raise NotImplementedError
|
||
|
||
for img_path in image_file_list:
|
||
img_name = os.path.basename(img_path).split('.')[0]
|
||
logger.info('{}{}{}'.format('*' * 10, img_path, '*' * 10))
|
||
if args.type == 'ocr':
|
||
result = engine.ocr(img_path,
|
||
det=args.det,
|
||
rec=args.rec,
|
||
cls=args.use_angle_cls)
|
||
if result is not None:
|
||
for line in result:
|
||
logger.info(line)
|
||
elif args.type == 'structure':
|
||
result = engine(img_path)
|
||
save_structure_res(result, args.output, img_name)
|
||
|
||
for item in result:
|
||
item.pop('img')
|
||
logger.info(item)
|