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from dotenv import load_dotenv
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import os
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env = os.environ.get('env', 'dev')
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load_dotenv(dotenv_path='.env.dev' if env == 'dev' else '.env', override=True)
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import time
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import traceback
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import cv2
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from helper.image_helper import pdf2image, image_orient_cls, page_detection_visual
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from helper.page_detection.main import layout_analysis
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from helper.content_recognition.main import rec
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from helper.db_helper import insert_pdf2md_table
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import tempfile
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from loguru import logger
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import datetime
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import shutil
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def _pdf2markdown_pipeline(pdf_path, tmp_dir):
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start_time = time.time()
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# 1. pdf -> images
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t1 = time.time()
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pdf2image(pdf_path, tmp_dir)
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t2 = time.time()
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# 2. 图片方向分类
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t3 = time.time()
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orient_cls_results = image_orient_cls(tmp_dir)
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t4 = time.time()
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for r in orient_cls_results:
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clsid = r[0]['class_ids'][0]
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filename = r[0]['filename']
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if clsid == 1 or clsid == 3:
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img = cv2.imread(filename)
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img = cv2.rotate(img, cv2.ROTATE_90_CLOCKWISE)
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cv2.imwrite(filename, img)
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filepaths = os.listdir(tmp_dir)
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filepaths.sort(key=lambda x: int(x.split('/')[-1].split('.')[0]))
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filepaths = [f'{tmp_dir}/{_}' for _ in filepaths]
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# filepaths = filepaths[250:251]
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# 3. 版面分析
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t5 = time.time()
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layout_detection_results = layout_analysis(filepaths)
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t6 = time.time()
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# 3.1 visual
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if int(os.environ['VISUAL']):
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visual_dir = './visual_images'
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for f in os.listdir(visual_dir):
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if f.endswith('.jpg'):
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os.remove(f'{visual_dir}/{f}')
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for i in range(len(layout_detection_results)):
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vis_img = page_detection_visual(layout_detection_results[i])
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cv2.imwrite(f'{visual_dir}/{i + 1}.jpg', vis_img)
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# 4. 内容识别
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t7 = time.time()
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layout_recognition_results = rec(layout_detection_results, tmp_dir)
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t8 = time.time()
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end_time = time.time()
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logger.info(f'{pdf_path} analysis completed in {round(end_time - start_time, 3)} seconds, including {round(t2 - t1, 3)} for pdf to image, {round(t4 - t3, 3)} second for image orient classification, {round(t6 - t5, 3)} seconds for page detection, and {round(t8 - t7, 3)} seconds for layout recognition, page number: {len(filepaths)}')
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return layout_recognition_results
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def pdf2markdown_pipeline(pdf_path: str):
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pdf_name = pdf_path.split('/')[-1]
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start_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
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process_status = 0
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tmp_dir = tempfile.mkdtemp()
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try:
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results = _pdf2markdown_pipeline(pdf_path, tmp_dir)
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except Exception:
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logger.error(f'analysis pdf error! \n{traceback.format_exc()}')
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process_status = 3
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end_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
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insert_pdf2md_table(pdf_path, pdf_name, process_status, start_time, end_time, None)
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pdf_id = None
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else:
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process_status = 2
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end_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
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pdf_id = insert_pdf2md_table(pdf_path, pdf_name, process_status, start_time, end_time, results)
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finally:
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shutil.rmtree(tmp_dir)
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return process_status, pdf_id
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if __name__ == '__main__':
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pdf2markdown_pipeline('/mnt/pdf2markdown/龙源电力：2023年年度审计报告.PDF')
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