# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import sys import importlib __dir__ = os.path.dirname(__file__) import paddle sys.path.append(os.path.join(__dir__, '')) import cv2 import logging import numpy as np from pathlib import Path def _import_file(module_name, file_path, make_importable=False): spec = importlib.util.spec_from_file_location(module_name, file_path) module = importlib.util.module_from_spec(spec) spec.loader.exec_module(module) if make_importable: sys.modules[module_name] = module return module tools = _import_file('tools', os.path.join(__dir__, 'tools/__init__.py'), make_importable=True) ppocr = importlib.import_module('ppocr', 'paddleocr') ppstructure = importlib.import_module('ppstructure', 'paddleocr') from tools.infer import predict_system from ppocr.utils.logging import get_logger logger = get_logger() from ppocr.utils.utility import check_and_read, get_image_file_list from ppocr.utils.network import maybe_download, download_with_progressbar, is_link, confirm_model_dir_url from tools.infer.utility import draw_ocr, str2bool, check_gpu from ppstructure.utility import init_args, draw_structure_result from ppstructure.predict_system import StructureSystem, save_structure_res, to_excel __all__ = [ 'PaddleOCR', 'PPStructure', 'draw_ocr', 'draw_structure_result', 'save_structure_res', 'download_with_progressbar', 'to_excel' ] SUPPORT_DET_MODEL = ['DB'] VERSION = '2.6.1.0' SUPPORT_REC_MODEL = ['CRNN', 'SVTR_LCNet'] BASE_DIR = os.path.expanduser("~/.paddleocr/") DEFAULT_OCR_MODEL_VERSION = 'PP-OCRv3' SUPPORT_OCR_MODEL_VERSION = ['PP-OCR', 'PP-OCRv2', 'PP-OCRv3'] DEFAULT_STRUCTURE_MODEL_VERSION = 'PP-StructureV2' SUPPORT_STRUCTURE_MODEL_VERSION = ['PP-Structure', 'PP-StructureV2'] MODEL_URLS = { 'OCR': { 'PP-OCRv3': { 'det': { 'ch': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_infer.tar', }, 'en': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar', }, 'ml': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar' } }, 'rec': { 'tw': { 'url': 'https://huggingface.co/spaces/DeepLearning101/OCR101TW/resolve/main/20230804_latest-100_rec.tar', 'dict_path': './230802_v2_common_dict.txt' }, 'ch': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/ppocr_keys_v1.txt' }, 'en': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/en_dict.txt' }, 'korean': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/korean_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/korean_dict.txt' }, 'japan': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/japan_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/japan_dict.txt' }, 'chinese_cht': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/chinese_cht_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt' }, 'ta': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ta_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/ta_dict.txt' }, 'te': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/te_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/te_dict.txt' }, 'ka': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/ka_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/ka_dict.txt' }, 'latin': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/latin_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/latin_dict.txt' }, 'arabic': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/arabic_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/arabic_dict.txt' }, 'cyrillic': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/cyrillic_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/cyrillic_dict.txt' }, 'devanagari': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/devanagari_PP-OCRv3_rec_infer.tar', 'dict_path': './ppocr/utils/dict/devanagari_dict.txt' }, }, 'cls': { 'ch': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar', } }, }, 'PP-OCRv2': { 'det': { 'ch': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar', }, }, 'rec': { 'ch': { 'url': 'https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar', 'dict_path': './ppocr/utils/ppocr_keys_v1.txt' } }, 'cls': { 'ch': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar', } }, }, 'PP-OCR': { 'det': { 'ch': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar', }, 'en': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_ppocr_mobile_v2.0_det_infer.tar', }, 'structure': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar' } }, 'rec': { 'ch': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/ppocr_keys_v1.txt' }, 'en': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/en_number_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/en_dict.txt' }, 'french': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/french_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/french_dict.txt' }, 'german': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/german_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/german_dict.txt' }, 'korean': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/korean_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/korean_dict.txt' }, 'japan': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/japan_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/japan_dict.txt' }, 'chinese_cht': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/chinese_cht_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/chinese_cht_dict.txt' }, 'ta': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ta_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/ta_dict.txt' }, 'te': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/te_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/te_dict.txt' }, 'ka': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/ka_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/ka_dict.txt' }, 'latin': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/latin_ppocr_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/latin_dict.txt' }, 'arabic': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/arabic_ppocr_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/arabic_dict.txt' }, 'cyrillic': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/cyrillic_ppocr_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/cyrillic_dict.txt' }, 'devanagari': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/multilingual/devanagari_ppocr_mobile_v2.0_rec_infer.tar', 'dict_path': './ppocr/utils/dict/devanagari_dict.txt' }, 'structure': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar', 'dict_path': 'ppocr/utils/dict/table_dict.txt' } }, 'cls': { 'ch': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar', } }, } }, 'STRUCTURE': { 'PP-Structure': { 'table': { 'en': { 'url': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar', 'dict_path': 'ppocr/utils/dict/table_structure_dict.txt' } } }, 'PP-StructureV2': { 'kie': { 'en': { 'url': 'https://huggingface.co/spaces/CallMeMrFern/ocr/resolve/main/ppstructure/models/kie/ser_clinical.tar', 'dict_path': 'ppocr/utils/dict/kie/clinical_class_list.txt' }, 'tw': { 'url': 'https://huggingface.co/spaces/CallMeMrFern/ocr/ppstructure/models/kie/ser_clinical.tar', 'dict_path': 'ppocr/utils/dict/kie/clinical_class_list.txt' } } } } } def parse_args(mMain=True): import argparse parser = init_args() parser.add_help = mMain parser.add_argument("--lang", type=str, default='tw') parser.add_argument("--det", type=str2bool, default=True) parser.add_argument("--rec", type=str2bool, default=True) parser.add_argument("--type", type=str, default='ocr') parser.add_argument( "--ocr_version", type=str, choices=SUPPORT_OCR_MODEL_VERSION, default='PP-OCRv3', help='OCR Model version, the current model support list is as follows: ' '1. PP-OCRv3 Support Chinese and English detection and recognition model, and direction classifier model' '2. PP-OCRv2 Support Chinese detection and recognition model. ' '3. PP-OCR support Chinese detection, recognition and direction classifier and multilingual recognition model.' ) parser.add_argument( "--structure_version", type=str, choices=SUPPORT_STRUCTURE_MODEL_VERSION, default='PP-StructureV2', help='Model version, the current model support list is as follows:' ' 1. PP-Structure Support en table structure model.' ' 2. PP-StructureV2 Support ch and en table structure model.') for action in parser._actions: if action.dest in [ 'rec_char_dict_path', 'table_char_dict_path', 'layout_dict_path','kie_dict_path' ]: action.default = None if mMain: return parser.parse_args() else: inference_args_dict = {} for action in parser._actions: inference_args_dict[action.dest] = action.default return argparse.Namespace(**inference_args_dict) def parse_lang(lang): latin_lang = [ 'af', 'az', 'bs', 'cs', 'cy', 'da', 'de', 'es', 'et', 'fr', 'ga', 'hr', 'hu', 'id', 'is', 'it', 'ku', 'la', 'lt', 'lv', 'mi', 'ms', 'mt', 'nl', 'no', 'oc', 'pi', 'pl', 'pt', 'ro', 'rs_latin', 'sk', 'sl', 'sq', 'sv', 'sw', 'tl', 'tr', 'uz', 'vi', 'french', 'german' ] arabic_lang = ['ar', 'fa', 'ug', 'ur'] cyrillic_lang = [ 'ru', 'rs_cyrillic', 'be', 'bg', 'uk', 'mn', 'abq', 'ady', 'kbd', 'ava', 'dar', 'inh', 'che', 'lbe', 'lez', 'tab' ] devanagari_lang = [ 'hi', 'mr', 'ne', 'bh', 'mai', 'ang', 'bho', 'mah', 'sck', 'new', 'gom', 'sa', 'bgc' ] if lang in latin_lang: lang = "latin" elif lang in arabic_lang: lang = "arabic" elif lang in cyrillic_lang: lang = "cyrillic" elif lang in devanagari_lang: lang = "devanagari" assert lang in MODEL_URLS['OCR'][DEFAULT_OCR_MODEL_VERSION][ 'rec'], 'param lang must in {}, but got {}'.format( MODEL_URLS['OCR'][DEFAULT_OCR_MODEL_VERSION]['rec'].keys(), lang) if lang == "ch": det_lang = "ch" elif lang == 'tw': det_lang = 'ch' elif lang == 'structure': det_lang = 'structure' elif lang in ["en", "latin"]: det_lang = "en" else: det_lang = "ml" return lang, det_lang def get_model_config(type, version, model_type, lang): if type == 'OCR': DEFAULT_MODEL_VERSION = DEFAULT_OCR_MODEL_VERSION elif type == 'STRUCTURE': DEFAULT_MODEL_VERSION = DEFAULT_STRUCTURE_MODEL_VERSION else: raise NotImplementedError model_urls = MODEL_URLS[type] if version not in model_urls: version = DEFAULT_MODEL_VERSION if model_type not in model_urls[version]: if model_type in model_urls[DEFAULT_MODEL_VERSION]: version = DEFAULT_MODEL_VERSION else: logger.error('{} models is not support, we only support {}'.format( model_type, model_urls[DEFAULT_MODEL_VERSION].keys())) sys.exit(-1) if lang not in model_urls[version][model_type]: if lang in model_urls[DEFAULT_MODEL_VERSION][model_type]: version = DEFAULT_MODEL_VERSION else: logger.error( 'lang {} is not support, we only support {} for {} models'. format(lang, model_urls[DEFAULT_MODEL_VERSION][model_type].keys( ), model_type)) sys.exit(-1) return model_urls[version][model_type][lang] def img_decode(content: bytes): np_arr = np.frombuffer(content, dtype=np.uint8) return cv2.imdecode(np_arr, cv2.IMREAD_COLOR) def check_img(img): if isinstance(img, bytes): img = img_decode(img) if isinstance(img, str): # download net image if is_link(img): download_with_progressbar(img, 'tmp.jpg') img = 'tmp.jpg' image_file = img img, flag_gif, flag_pdf = check_and_read(image_file) if not flag_gif and not flag_pdf: with open(image_file, 'rb') as f: img = img_decode(f.read()) 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) return img class PaddleOCR(predict_system.TextSystem): def __init__(self, **kwargs): """ paddleocr package args: **kwargs: other params show in paddleocr --help """ params = parse_args(mMain=False) params.__dict__.update(**kwargs) assert params.ocr_version in SUPPORT_OCR_MODEL_VERSION, "ocr_version must in {}, but get {}".format( SUPPORT_OCR_MODEL_VERSION, params.ocr_version) params.use_gpu = check_gpu(params.use_gpu) if not params.show_log: logger.setLevel(logging.INFO) self.use_angle_cls = params.use_angle_cls 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']) cls_model_config = get_model_config('OCR', params.ocr_version, 'cls', 'ch') params.cls_model_dir, cls_url = confirm_model_dir_url( params.cls_model_dir, os.path.join(BASE_DIR, 'whl', 'cls'), cls_model_config['url']) if params.ocr_version == 'PP-OCRv3': params.rec_image_shape = "3, 48, 320" else: params.rec_image_shape = "3, 32, 320" # download model if using paddle infer if not params.use_onnx: maybe_download(params.det_model_dir, det_url) maybe_download(params.rec_model_dir, rec_url) maybe_download(params.cls_model_dir, cls_url) 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) self.page_num = params.page_num 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, bytes)) 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' ) img = check_img(img) # for infer pdf file if isinstance(img, list): if self.page_num > len(img) or self.page_num == 0: imgs=img else: imgs = img[:self.page_num] else: imgs = [img] if det and rec: ocr_res = [] for idx, img in enumerate(imgs): dt_boxes, rec_res, _ = self.__call__(img, cls) tmp_res = [[box.tolist(), res] for box, res in zip(dt_boxes, rec_res)] ocr_res.append(tmp_res) return ocr_res elif det and not rec: ocr_res = [] for idx, img in enumerate(imgs): dt_boxes, elapse = self.text_detector(img) tmp_res = [box.tolist() for box in dt_boxes] ocr_res.append(tmp_res) return ocr_res else: ocr_res = [] cls_res = [] for idx, img in enumerate(imgs): if not isinstance(img, list): img = [img] if self.use_angle_cls and cls: img, cls_res_tmp, elapse = self.text_classifier(img) if not rec: cls_res.append(cls_res_tmp) rec_res, elapse = self.text_recognizer(img) ocr_res.append(rec_res) if not rec: return cls_res return ocr_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) params.mode = 'kie' if not params.show_log: logger.setLevel(logging.INFO) lang, det_lang = parse_lang(params.lang) if lang == 'ch': table_lang = 'ch' else: table_lang = 'en' if params.structure_version == 'PP-Structure': params.merge_no_span_structure = False # 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', table_lang) # 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']) # print(params.structure_version) # layout_model_config = get_model_config( # 'STRUCTURE', params.structure_version, 'layout', lang) # params.layout_model_dir, layout_url = confirm_model_dir_url( # params.layout_model_dir, # os.path.join(BASE_DIR, 'whl', 'layout'), layout_model_config['url']) ser_model_config = get_model_config( 'STRUCTURE', params.structure_version, 'kie', table_lang) params.ser_model_dir, ser_url = confirm_model_dir_url( params.ser_model_dir, os.path.join(BASE_DIR, 'whl', 'kie'), ser_model_config['url']) print(params.ser_model_dir) # 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) # maybe_download(params.layout_model_dir, layout_url) maybe_download(params.ser_model_dir, ser_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']) # if params.layout_dict_path is None: # params.layout_dict_path = str( # Path(__file__).parent / layout_model_config['dict_path']) if params.ser_dict_path is None: params.ser_dict_path = str( Path(__file__).parent / ser_model_config['dict_path']) logger.debug(params) print(params) super().__init__(params) def __call__(self, img, return_ocr_result_in_table=False, img_idx=0): img = check_img(img) res, res2 = super().__call__( img, return_ocr_result_in_table, img_idx=img_idx) return res, res2 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 idx in range(len(result)): res = result[idx] for line in res: logger.info(line) elif args.type == 'structure': img, flag_gif, flag_pdf = check_and_read(img_path) if not flag_gif and not flag_pdf: img = cv2.imread(img_path) if args.recovery and args.use_pdf2docx_api and flag_pdf: from pdf2docx.converter import Converter docx_file = os.path.join(args.output, '{}.docx'.format(img_name)) cv = Converter(img_path) cv.convert(docx_file) cv.close() logger.info('docx save to {}'.format(docx_file)) continue if not flag_pdf: if img is None: logger.error("error in loading image:{}".format(img_path)) continue img_paths = [[img_path, img]] else: img_paths = [] for index, pdf_img in enumerate(img): os.makedirs( os.path.join(args.output, img_name), exist_ok=True) pdf_img_path = os.path.join( args.output, img_name, img_name + '_' + str(index) + '.jpg') cv2.imwrite(pdf_img_path, pdf_img) img_paths.append([pdf_img_path, pdf_img]) all_res = [] for index, (new_img_path, img) in enumerate(img_paths): logger.info('processing {}/{} page:'.format(index + 1, len(img_paths))) new_img_name = os.path.basename(new_img_path).split('.')[0] result = engine(new_img_path, img_idx=index) save_structure_res(result, args.output, img_name, index) if args.recovery and result != []: from copy import deepcopy from ppstructure.recovery.recovery_to_doc import sorted_layout_boxes h, w, _ = img.shape result_cp = deepcopy(result) result_sorted = sorted_layout_boxes(result_cp, w) all_res += result_sorted if args.recovery and all_res != []: try: from ppstructure.recovery.recovery_to_doc import convert_info_docx convert_info_docx(img, all_res, args.output, img_name) except Exception as ex: logger.error( "error in layout recovery image:{}, err msg: {}".format( img_name, ex)) continue for item in all_res: item.pop('img') item.pop('res') logger.info(item) logger.info('result save to {}'.format(args.output))