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| # Copyright (c) 2022 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 | |
| __dir__ = os.path.dirname(os.path.abspath(__file__)) | |
| sys.path.append(__dir__) | |
| sys.path.insert(0, os.path.abspath(os.path.join(__dir__, '../..'))) | |
| import cv2 | |
| import pickle | |
| import paddle | |
| from tqdm import tqdm | |
| from ppstructure.table.table_metric import TEDS | |
| from ppstructure.table.predict_table import TableSystem | |
| from ppstructure.utility import init_args | |
| from ppocr.utils.logging import get_logger | |
| logger = get_logger() | |
| def parse_args(): | |
| parser = init_args() | |
| parser.add_argument("--gt_path", type=str) | |
| return parser.parse_args() | |
| def load_txt(txt_path): | |
| pred_html_dict = {} | |
| if not os.path.exists(txt_path): | |
| return pred_html_dict | |
| with open(txt_path, encoding='utf-8') as f: | |
| lines = f.readlines() | |
| for line in lines: | |
| line = line.strip().split('\t') | |
| img_name, pred_html = line | |
| pred_html_dict[img_name] = pred_html | |
| return pred_html_dict | |
| def load_result(path): | |
| data = {} | |
| if os.path.exists(path): | |
| data = pickle.load(open(path, 'rb')) | |
| return data | |
| def save_result(path, data): | |
| old_data = load_result(path) | |
| old_data.update(data) | |
| with open(path, 'wb') as f: | |
| pickle.dump(old_data, f) | |
| def main(gt_path, img_root, args): | |
| os.makedirs(args.output, exist_ok=True) | |
| # init TableSystem | |
| text_sys = TableSystem(args) | |
| # load gt and preds html result | |
| gt_html_dict = load_txt(gt_path) | |
| ocr_result = load_result(os.path.join(args.output, 'ocr.pickle')) | |
| structure_result = load_result( | |
| os.path.join(args.output, 'structure.pickle')) | |
| pred_htmls = [] | |
| gt_htmls = [] | |
| for img_name, gt_html in tqdm(gt_html_dict.items()): | |
| img = cv2.imread(os.path.join(img_root, img_name)) | |
| # run ocr and save result | |
| if img_name not in ocr_result: | |
| dt_boxes, rec_res, _, _ = text_sys._ocr(img) | |
| ocr_result[img_name] = [dt_boxes, rec_res] | |
| save_result(os.path.join(args.output, 'ocr.pickle'), ocr_result) | |
| # run structure and save result | |
| if img_name not in structure_result: | |
| structure_res, _ = text_sys._structure(img) | |
| structure_result[img_name] = structure_res | |
| save_result( | |
| os.path.join(args.output, 'structure.pickle'), structure_result) | |
| dt_boxes, rec_res = ocr_result[img_name] | |
| structure_res = structure_result[img_name] | |
| # match ocr and structure | |
| pred_html = text_sys.match(structure_res, dt_boxes, rec_res) | |
| pred_htmls.append(pred_html) | |
| gt_htmls.append(gt_html) | |
| # compute teds | |
| teds = TEDS(n_jobs=16) | |
| scores = teds.batch_evaluate_html(gt_htmls, pred_htmls) | |
| logger.info('teds: {}'.format(sum(scores) / len(scores))) | |
| if __name__ == '__main__': | |
| args = parse_args() | |
| main(args.gt_path, args.image_dir, args) | |