236 lines
9.4 KiB
Python
236 lines
9.4 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 subprocess
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__dir__ = os.path.dirname(os.path.abspath(__file__))
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sys.path.append(__dir__)
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sys.path.insert(0, os.path.abspath(os.path.join(__dir__, '../')))
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os.environ["FLAGS_allocator_strategy"] = 'auto_growth'
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import cv2
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import json
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import numpy as np
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import time
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import logging
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from copy import deepcopy
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from attrdict import AttrDict
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from ppocr.utils.utility import get_image_file_list, check_and_read_gif
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from ppocr.utils.logging import get_logger
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from tools.infer.predict_system import TextSystem
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from ppstructure.layout.predict_layout import LayoutPredictor
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from ppstructure.table.predict_table import TableSystem, to_excel
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from ppstructure.utility import parse_args, draw_structure_result
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from ppstructure.recovery.recovery_to_doc import convert_info_docx
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logger = get_logger()
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class StructureSystem(object):
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def __init__(self, args):
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self.mode = args.mode
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self.recovery = args.recovery
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if self.mode == 'structure':
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if not args.show_log:
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logger.setLevel(logging.INFO)
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if args.layout == False and args.ocr == True:
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args.ocr = False
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logger.warning(
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"When args.layout is false, args.ocr is automatically set to false"
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)
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args.drop_score = 0
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# init model
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self.layout_predictor = None
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self.text_system = None
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self.table_system = None
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if args.layout:
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self.layout_predictor = LayoutPredictor(args)
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if args.ocr:
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self.text_system = TextSystem(args)
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if args.table:
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if self.text_system is not None:
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self.table_system = TableSystem(
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args, self.text_system.text_detector,
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self.text_system.text_recognizer)
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else:
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self.table_system = TableSystem(args)
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elif self.mode == 'vqa':
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raise NotImplementedError
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def __call__(self, img, return_ocr_result_in_table=False):
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time_dict = {
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'layout': 0,
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'table': 0,
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'table_match': 0,
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'det': 0,
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'rec': 0,
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'vqa': 0,
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'all': 0
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}
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start = time.time()
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if self.mode == 'structure':
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ori_im = img.copy()
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if self.layout_predictor is not None:
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layout_res, elapse = self.layout_predictor(img)
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time_dict['layout'] += elapse
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else:
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h, w = ori_im.shape[:2]
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layout_res = [dict(bbox=None, label='table')]
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res_list = []
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for region in layout_res:
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res = ''
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if region['bbox'] is not None:
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x1, y1, x2, y2 = region['bbox']
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x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
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roi_img = ori_im[y1:y2, x1:x2, :]
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else:
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x1, y1, x2, y2 = 0, 0, w, h
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roi_img = ori_im
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if region['label'] == 'table':
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if self.table_system is not None:
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res, table_time_dict = self.table_system(
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roi_img, return_ocr_result_in_table)
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time_dict['table'] += table_time_dict['table']
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time_dict['table_match'] += table_time_dict['match']
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time_dict['det'] += table_time_dict['det']
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time_dict['rec'] += table_time_dict['rec']
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else:
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if self.text_system is not None:
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if self.recovery:
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wht_im = np.ones(ori_im.shape, dtype=ori_im.dtype)
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wht_im[y1:y2, x1:x2, :] = roi_img
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filter_boxes, filter_rec_res, ocr_time_dict = self.text_system(
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wht_im)
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else:
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filter_boxes, filter_rec_res, ocr_time_dict = self.text_system(
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roi_img)
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time_dict['det'] += ocr_time_dict['det']
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time_dict['rec'] += ocr_time_dict['rec']
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# remove style char
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style_token = [
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'<strike>', '<strike>', '<sup>', '</sub>', '<b>',
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'</b>', '<sub>', '</sup>', '<overline>',
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'</overline>', '<underline>', '</underline>', '<i>',
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'</i>'
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]
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res = []
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for box, rec_res in zip(filter_boxes, filter_rec_res):
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rec_str, rec_conf = rec_res
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for token in style_token:
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if token in rec_str:
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rec_str = rec_str.replace(token, '')
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if not self.recovery:
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box += [x1, y1]
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res.append({
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'text': rec_str,
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'confidence': float(rec_conf),
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'text_region': box.tolist()
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})
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res_list.append({
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'type': region['label'].lower(),
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'bbox': [x1, y1, x2, y2],
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'img': roi_img,
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'res': res
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})
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end = time.time()
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time_dict['all'] = end - start
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return res_list, time_dict
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elif self.mode == 'vqa':
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raise NotImplementedError
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return None, None
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def save_structure_res(res, save_folder, img_name):
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excel_save_folder = os.path.join(save_folder, img_name)
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os.makedirs(excel_save_folder, exist_ok=True)
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res_cp = deepcopy(res)
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# save res
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with open(
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os.path.join(excel_save_folder, 'res.txt'), 'w',
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encoding='utf8') as f:
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for region in res_cp:
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roi_img = region.pop('img')
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f.write('{}\n'.format(json.dumps(region)))
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if region['type'] == 'table' and len(region[
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'res']) > 0 and 'html' in region['res']:
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excel_path = os.path.join(excel_save_folder,
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'{}.xlsx'.format(region['bbox']))
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to_excel(region['res']['html'], excel_path)
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elif region['type'] == 'figure':
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img_path = os.path.join(excel_save_folder,
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'{}.jpg'.format(region['bbox']))
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cv2.imwrite(img_path, roi_img)
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def main(args):
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image_file_list = get_image_file_list(args.image_dir)
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image_file_list = image_file_list
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image_file_list = image_file_list[args.process_id::args.total_process_num]
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structure_sys = StructureSystem(args)
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img_num = len(image_file_list)
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save_folder = os.path.join(args.output, structure_sys.mode)
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os.makedirs(save_folder, exist_ok=True)
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for i, image_file in enumerate(image_file_list):
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logger.info("[{}/{}] {}".format(i, img_num, image_file))
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img, flag = check_and_read_gif(image_file)
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img_name = os.path.basename(image_file).split('.')[0]
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if not flag:
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img = cv2.imread(image_file)
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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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continue
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starttime = time.time()
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res, time_dict = structure_sys(img)
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if structure_sys.mode == 'structure':
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save_structure_res(res, save_folder, img_name)
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draw_img = draw_structure_result(img, res, args.vis_font_path)
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img_save_path = os.path.join(save_folder, img_name, 'show.jpg')
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elif structure_sys.mode == 'vqa':
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raise NotImplementedError
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# draw_img = draw_ser_results(img, res, args.vis_font_path)
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# img_save_path = os.path.join(save_folder, img_name + '.jpg')
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cv2.imwrite(img_save_path, draw_img)
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logger.info('result save to {}'.format(img_save_path))
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if args.recovery:
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convert_info_docx(img, res, save_folder, img_name)
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elapse = time.time() - starttime
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logger.info("Predict time : {:.3f}s".format(elapse))
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if __name__ == "__main__":
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args = parse_args()
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if args.use_mp:
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p_list = []
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total_process_num = args.total_process_num
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for process_id in range(total_process_num):
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cmd = [sys.executable, "-u"] + sys.argv + [
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"--process_id={}".format(process_id),
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"--use_mp={}".format(False)
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]
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p = subprocess.Popen(cmd, stdout=sys.stdout, stderr=sys.stdout)
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p_list.append(p)
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for p in p_list:
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p.wait()
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else:
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main(args)
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