149 lines
6.0 KiB
Python
149 lines
6.0 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 logging
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import os
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import sys
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__dir__ = os.path.dirname(__file__)
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sys.path.append(__dir__)
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sys.path.append(os.path.join(__dir__, '..'))
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import cv2
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import numpy as np
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from pathlib import Path
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from ppocr.utils.logging import get_logger
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from test1.predict_system import OCRSystem, save_res
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from test1.table.predict_table import to_excel
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from test1.utility import init_args, draw_result
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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, confirm_model_dir_url, is_link
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__all__ = ['PaddleStructure', 'draw_result', 'save_res']
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VERSION = '2.1'
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BASE_DIR = os.path.expanduser("~/.paddlestructure/")
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model_urls = {
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'det': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar',
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'rec': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar',
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'table': 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar'
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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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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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class PaddleStructure(OCRSystem):
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def __init__(self, **kwargs):
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params = parse_args(mMain=False)
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params.__dict__.update(**kwargs)
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if not params.show_log:
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logger.setLevel(logging.INFO)
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params.use_angle_cls = False
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# init model dir
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params.det_model_dir, det_url = confirm_model_dir_url(params.det_model_dir,
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os.path.join(BASE_DIR, VERSION, 'det'),
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model_urls['det'])
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params.rec_model_dir, rec_url = confirm_model_dir_url(params.rec_model_dir,
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os.path.join(BASE_DIR, VERSION, 'rec'),
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model_urls['rec'])
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params.table_model_dir, table_url = confirm_model_dir_url(params.table_model_dir,
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os.path.join(BASE_DIR, VERSION, 'table'),
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model_urls['table'])
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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.table_model_dir, table_url)
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if params.rec_char_dict_path is None:
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params.rec_char_type = 'EN'
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if os.path.exists(str(Path(__file__).parent / 'ppocr/utils/dict/table_dict.txt')):
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params.rec_char_dict_path = str(Path(__file__).parent / 'ppocr/utils/dict/table_dict.txt')
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else:
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params.rec_char_dict_path = str(Path(__file__).parent.parent / 'ppocr/utils/dict/table_dict.txt')
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if params.table_char_dict_path is None:
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if os.path.exists(str(Path(__file__).parent / 'ppocr/utils/dict/table_structure_dict.txt')):
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params.table_char_dict_path = str(
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Path(__file__).parent / 'ppocr/utils/dict/table_structure_dict.txt')
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else:
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params.table_char_dict_path = str(
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Path(__file__).parent.parent / 'ppocr/utils/dict/table_structure_dict.txt')
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print(params)
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super().__init__(params)
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def __call__(self, img):
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if isinstance(img, str):
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# download net image
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if img.startswith('http'):
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download_with_progressbar(img, 'tmp.jpg')
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img = 'tmp.jpg'
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image_file = img
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img, flag = check_and_read_gif(image_file)
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if not flag:
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with open(image_file, 'rb') as f:
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np_arr = np.frombuffer(f.read(), dtype=np.uint8)
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img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
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if img is None:
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logger.error("error in loading image:{}".format(image_file))
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return None
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if isinstance(img, np.ndarray) and len(img.shape) == 2:
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img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
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res = super().__call__(img)
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return res
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def main():
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# for cmd
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args = parse_args(mMain=True)
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image_dir = args.image_dir
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save_folder = args.output
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if image_dir.startswith('http'):
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download_with_progressbar(image_dir, 'tmp.jpg')
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image_file_list = ['tmp.jpg']
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else:
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image_file_list = get_image_file_list(args.image_dir)
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if len(image_file_list) == 0:
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logger.error('no images find in {}'.format(args.image_dir))
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return
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structure_engine = PaddleStructure(**(args.__dict__))
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for img_path in image_file_list:
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img_name = os.path.basename(img_path).split('.')[0]
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logger.info('{}{}{}'.format('*' * 10, img_path, '*' * 10))
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result = structure_engine(img_path)
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for item in result:
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logger.info(item['res'])
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save_res(result, save_folder, img_name)
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logger.info('result save to {}'.format(os.path.join(save_folder, img_name)))
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