595 lines
22 KiB
Python
595 lines
22 KiB
Python
# # import re
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# # import PyPDF2
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# # import tempfile
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# # from utils.ocr_engine import OcrEngine
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# #
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# #
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# # # 假设您的OCR函数名为 `ocr_extract`，并接受图片文件路径作为参数
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# # # 请将此函数替换为您实际的OCR实现
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# #
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# # def clean_page_content(text, common_header):
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# # # 首先删除抬头公共部分
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# # if common_header: # 确保有公共抬头才进行替换
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# # for header_line in common_header.split('\n'):
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# # if header_line.strip(): # 只处理非空行
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# # # 替换首次出现的完整行
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# # text = re.sub(r'^' + re.escape(header_line.strip()) + r'\n?', '', text, count=1)
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# #
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# # # 删除页码 eg:89/129 这个代码分三步走可以把89/129完全删除
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# # text = re.sub(r'^\s*\d+\s*(?=\D)', '', text) # 删除开头的页码，仅当紧跟非数字字符时
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# # text = re.sub(r'\s+\d+\s*$', '', text) # 删除结尾的页码
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# # text = re.sub(r'\s*\/\s*\d+\s*', '', text) # 删除形如 /129 的页码
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# # text = re.sub(r'\s*[—-]\s*\d+\s*[—-]\s*', '', text) # 删除形如 '—2—' 或 '-2-' 的页码
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# # return text
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# #
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# #
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# # def extract_common_header(pdf_path):
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# # from PyPDF2 import PdfReader
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# #
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# # def get_headers(pdf_document, start_page, pages_to_read):
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# # headers = []
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# # for i in range(start_page, min(start_page + pages_to_read, len(pdf_document.pages))):
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# # page = pdf_document.pages[i]
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# # text = page.extract_text() or ""
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# # if text:
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# # # 只取每页的前三行，去除前后的空白字符
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# # first_lines = [line.strip() for line in text.strip().split('\n')[:3]]
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# # headers.append(first_lines)
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# # return headers
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# #
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# # def find_common_headers(headers):
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# # if not headers:
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# # return []
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# #
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# # # 使用 zip 对齐所有页的对应行
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# # common_headers = []
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# # for lines in zip(*headers):
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# # # 检查所有行是否完全相同
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# # if all(line == lines[0] for line in lines[1:]):
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# # common_headers.append(lines[0])
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# # return common_headers
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# #
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# # pdf_document = PdfReader(pdf_path)
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# # total_pages = len(pdf_document.pages)
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# #
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# # # 定义两个提取策略
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# # strategies = []
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# # if total_pages >= 3:
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# # # 策略1：中间的3页
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# # middle_page = total_pages // 2
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# # start_page = max(0, middle_page - 1)
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# # strategies.append((start_page, 3))
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# # elif total_pages == 2:
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# # # 策略1：2页
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# # strategies.append((0, 2))
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# # else:
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# # # 策略1：1页
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# # strategies.append((0, 1))
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# #
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# # # 策略2：前三页
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# # if total_pages >= 3:
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# # strategies.append((0, 3))
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# # elif total_pages == 2:
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# # strategies.append((0, 2))
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# # elif total_pages == 1:
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# # strategies.append((0, 1))
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# #
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# # common_headers = []
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# #
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# # for idx, (start, count) in enumerate(strategies):
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# # headers = get_headers(pdf_document, start, count)
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# # if len(headers) < 2:
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# # continue # 需要至少2页来比较
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# #
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# # current_common = find_common_headers(headers)
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# # if current_common:
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# # common_headers = current_common
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# # break # 找到共同部分后退出
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# # # 如果没有找到，继续下一个策略
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# #
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# # return '\n'.join(common_headers)
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# #
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# #
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# # def extract_images_from_page(reader, page):
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# # images = []
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# # try:
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# # for img in page.images:
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# # xref = img['xref']
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# # image = reader.extract_image(xref)
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# # image_bytes = image['image']
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# # image_ext = image['ext']
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# # images.append({'data': image_bytes, 'ext': image_ext})
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# # except Exception as e:
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# # print(f"提取第{reader.pages.index(page) + 1}页图片时出错: {e}")
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# # return images
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# #
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# #
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# # def extract_text_by_page(file_path):
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# # common_header = extract_common_header(file_path)
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# # # print(f"公共抬头：{common_header}")
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# # # print("--------------------正文开始-------------------")
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# # result = ""
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# # with open(file_path, 'rb') as file:
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# # reader = PyPDF2.PdfReader(file)
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# # num_pages = len(reader.pages)
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# # # print(f"Total pages: {num_pages}")
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# # for page_num in range(num_pages):
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# # page = reader.pages[page_num]
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# # text = page.extract_text() or ""
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# #
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# # # 提取图片并进行OCR
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# # images = extract_images_from_page(reader, page)
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# # ocr_text = ""
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# # for image in images:
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# # image_data = image['data']
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# # image_ext = image['ext']
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# # try:
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# # with tempfile.NamedTemporaryFile(delete=True, suffix='.' + image_ext) as temp_image:
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# # temp_image.write(image_data)
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# # temp_image.flush()
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# # # 调用OCR函数
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# # ocr_result = OcrEngine.recognize_text_from_image(temp_image.name)
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# # ocr_text += ocr_result + "\n"
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# # except Exception as e:
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# # print(f"处理第{page_num + 1}页图片时出错: {e}")
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# #
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# # # 清理文本
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# # cleaned_text = clean_page_content(text, common_header)
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# # # 合并OCR文本
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# # if ocr_text.strip():
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# # cleaned_text += "\n" + ocr_text
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# # result += cleaned_text
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# # return result
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# #
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# #
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# # def extract_text_json_by_page(file_path):
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# # common_header = extract_common_header(file_path)
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# # # print(f"公共抬头：{common_header}")
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# # # print("--------------------正文开始-------------------")
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# # result = {}
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# # with open(file_path, 'rb') as file:
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# # reader = PyPDF2.PdfReader(file)
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# # num_pages = len(reader.pages)
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# # # print(f"Total pages: {num_pages}")
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# # for page_num in range(num_pages):
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# # page = reader.pages[page_num]
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# # text = page.extract_text() or ""
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# #
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# # # 提取图片并进行OCR
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# # images = extract_images_from_page(reader, page)
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# # ocr_text = ""
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# # for image in images:
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# # image_data = image['data']
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# # image_ext = image['ext']
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# # try:
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# # with tempfile.NamedTemporaryFile(delete=True, suffix='.' + image_ext) as temp_image:
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# # temp_image.write(image_data)
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# # temp_image.flush()
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# # # 调用OCR函数
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# # ocr_result = OcrEngine.recognize_text_from_image(temp_image.name)
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# # ocr_text += ocr_result + "\n"
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# # except Exception as e:
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# # print(f"处理第{page_num + 1}页图片时出错: {e}")
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# #
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# # # 清理文本
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# # cleaned_text = clean_page_content(text, common_header)
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# # # 合并OCR文本
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# # if ocr_text.strip():
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# # cleaned_text += "\n" + ocr_text
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# # result[str(page_num + 1)] = cleaned_text
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# # return result
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# #
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# #
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# # if __name__ == '__main__':
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# # pdf_path = "C:/test/iDS-TCE900神捕电警抓拍单元产品介绍.pdf"
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# # res = extract_text_json_by_page(pdf_path)
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# # print(res)
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# import json
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# import os
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# import re
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# import shutil
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# import uuid
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#
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# import PyPDF2
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# import fitz # PyMuPDF
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# import tempfile
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# from utils.ocr_engine import OcrEngine
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#
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#
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# # 假设您的OCR函数名为 `ocr_extract`，并接受图片文件路径作为参数
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# def ocr_extract(image_path):
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# # 示例：调用您的OCR脚本并返回识别的文本
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# # 例如：
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# # return your_ocr_function(image_path)
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# # 将图片保存到tmp目录
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# # shutil.copy(image_path, f'tmp/{uuid.uuid4()}.png')
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# # return "OCR提取的文本" # 替换为实际的OCR结果
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# return OcrEngine.recognize_text_from_image(image_path)
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#
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#
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# def clean_page_content(text, common_header):
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# # 首先删除抬头公共部分
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# if common_header: # 确保有公共抬头才进行替换
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# for header_line in common_header.split('\n'):
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# if header_line.strip(): # 只处理非空行
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# # 替换首次出现的完整行
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# text = re.sub(r'^' + re.escape(header_line.strip()) + r'\n?', '', text, count=1)
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#
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# # 删除页码 eg:89/129 这个代码分三步走可以把89/129完全删除
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# text = re.sub(r'^\s*\d+\s*(?=\D)', '', text) # 删除开头的页码，仅当紧跟非数字字符时
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# text = re.sub(r'\s+\d+\s*$', '', text) # 删除结尾的页码
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# text = re.sub(r'\s*\/\s*\d+\s*', '', text) # 删除形如 /129 的页码
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# text = re.sub(r'\s*[—-]\s*\d+\s*[—-]\s*', '', text) # 删除形如 '—2—' 或 '-2-' 的页码
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# return text
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#
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#
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# def extract_common_header(pdf_path):
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# from PyPDF2 import PdfReader
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#
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# def get_headers(pdf_document, start_page, pages_to_read):
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# headers = []
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# for i in range(start_page, min(start_page + pages_to_read, len(pdf_document.pages))):
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# page = pdf_document.pages[i]
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# text = page.extract_text() or ""
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# if text:
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# # 只取每页的前三行，去除前后的空白字符
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# first_lines = [line.strip() for line in text.strip().split('\n')[:3]]
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# headers.append(first_lines)
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# return headers
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#
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# def find_common_headers(headers):
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# if not headers:
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# return []
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#
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# # 使用 zip 对齐所有页的对应行
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# common_headers = []
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# for lines in zip(*headers):
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# # 检查所有行是否完全相同
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# if all(line == lines[0] for line in lines[1:]):
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# common_headers.append(lines[0])
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# return common_headers
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#
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# pdf_document = PdfReader(pdf_path)
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# total_pages = len(pdf_document.pages)
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#
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# # 定义两个提取策略
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# strategies = []
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# if total_pages >= 3:
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# # 策略1：中间的3页
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# middle_page = total_pages // 2
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# start_page = max(0, middle_page - 1)
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# strategies.append((start_page, 3))
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# elif total_pages == 2:
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# # 策略1：2页
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# strategies.append((0, 2))
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# else:
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# # 策略1：1页
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# strategies.append((0, 1))
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#
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# # 策略2：前三页
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# if total_pages >= 3:
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# strategies.append((0, 3))
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# elif total_pages == 2:
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# strategies.append((0, 2))
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# elif total_pages == 1:
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# strategies.append((0, 1))
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#
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# common_headers = []
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#
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# for idx, (start, count) in enumerate(strategies):
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# headers = get_headers(pdf_document, start, count)
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# if len(headers) < 2:
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# continue # 需要至少2页来比较
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#
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# current_common = find_common_headers(headers)
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# if current_common:
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# common_headers = current_common
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# break # 找到共同部分后退出
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# # 如果没有找到，继续下一个策略
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#
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# return '\n'.join(common_headers)
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#
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#
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# def extract_images_with_pymupdf(pdf_path):
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# images = []
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# try:
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# doc = fitz.open(pdf_path)
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# for page_num in range(len(doc)):
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# page = doc.load_page(page_num)
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# image_list = page.get_images(full=True)
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# for img in image_list:
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# xref = img[0]
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# base_image = doc.extract_image(xref)
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# image_bytes = base_image['image']
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# image_ext = base_image.get('ext', 'png')
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# # image_width = base_image.get['xres']
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# # image_height = base_image.get['yres']
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# # images.append({'data': image_bytes, 'ext': image_ext, 'page_num': page_num + 1, 'width': image_width, 'height': image_height}).
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# images.append({'data': image_bytes, 'ext': image_ext, 'page_num': page_num + 1})
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#
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# # 确保输出目录存在
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# if not os.path.exists("output_dir"):
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# os.makedirs("output_dir")
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# print(f"创建输出目录: output_dir")
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# # 构建图片文件名，例如: page_1_img.png
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# image_filename = f"page_{page_num}_img.{image_ext}"
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# image_path = os.path.join("output_dir", image_filename)
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# try:
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# with open(image_path, 'wb') as img_file:
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# img_file.write(image_bytes)
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# print(f"保存图片: {image_path}")
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# except Exception as e:
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# print(f"保存图片 {image_filename} 时出错: {e}")
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#
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# except Exception as e:
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# print(f"提取图片时出错: {e}")
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# return images
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#
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#
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# def extract_text_json_by_page(file_path):
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# common_header = extract_common_header(file_path)
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# # print(f"公共抬头：{common_header}")
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# # print("--------------------正文开始-------------------")
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# result = {}
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# # 如果已经有保存的ocr结果,直接读取
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# # TODO 待修改
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# if os.path.exists(file_path + ".json"):
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# with open(file_path + ".json", 'r', encoding='utf-8') as f:
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# result = json.load(f)
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# return result
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# images = extract_images_with_pymupdf(file_path)
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# # filtered_images = filter_images(images)
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# ocr_text_dict = {}
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# for img in images:
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# try:
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# with tempfile.NamedTemporaryFile(delete=False, suffix='.' + img['ext']) as temp_image:
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# temp_image.write(img['data'])
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# temp_image.flush()
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# # 调用OCR函数
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# ocr_result = ocr_extract(temp_image.name)
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# if img['page_num'] in ocr_text_dict:
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# ocr_text_dict[img['page_num']] += ocr_result + "\n"
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# else:
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# ocr_text_dict[img['page_num']] = ocr_result + "\n"
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# except Exception as e:
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# print(f"OCR处理失败: {e}")
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# finally:
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# try:
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# os.remove(temp_image.name)
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# except Exception as e:
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# print(f"删除临时文件失败: {e}")
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#
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# with open(file_path, 'rb') as file:
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# reader = PyPDF2.PdfReader(file)
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# num_pages = len(reader.pages)
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# # print(f"Total pages: {num_pages}")
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# for page_num in range(num_pages):
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# page = reader.pages[page_num]
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# text = page.extract_text() or ""
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# # 清理文本
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# cleaned_text = clean_page_content(text, common_header)
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# # 合并OCR文本
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# if (page_num + 1) in ocr_text_dict and ocr_text_dict[page_num + 1].strip():
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# cleaned_text += "\n" + ocr_text_dict[page_num + 1]
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# result[str(page_num + 1)] = cleaned_text
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# print("pdf预处理完成")
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# return result
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#
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#
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# def filter_images(images, min_width=200, min_height=200, text_threshold=5):
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# """
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# 过滤图像，保留可能包含文本的图像。
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# :param images: 图像列表，每个图像包含 data, ext, page_num, width, height
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# :param min_width: 最小宽度
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# :param min_height: 最小高度
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# :param text_threshold: 检测到的文本字符数阈值
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# :return: 过滤后的图像列表
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# """
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# filtered = []
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# for img in images:
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# # 基于尺寸过滤
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# if img['width'] < min_width or img['height'] < min_height:
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# continue
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# # 基于文本检测过滤
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# try:
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# # with tempfile.NamedTemporaryFile(delete=True, suffix='.' + img['ext']) as temp_image:
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# # temp_image.write(img['data'])
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# # temp_image.flush()
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# # # 使用OCR快速检测文本
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# # ocr_result = ocr_extract(temp_image.name)
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# # if len(ocr_result.strip()) >= text_threshold:
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# # img['ocr_text'] = ocr_result
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# # filtered.append(img)
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# filtered.append(img)
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# except Exception as e:
|
||
# print(f"过滤图像时出错: {e}")
|
||
#
|
||
# return filtered
|
||
#
|
||
#
|
||
# if __name__ == '__main__':
|
||
# pdf_path = "C:/test/发言系统11.pdf"
|
||
# res = extract_text_json_by_page(pdf_path)
|
||
# print(res)
|
||
|
||
import os
|
||
import re
|
||
import json
|
||
import tempfile
|
||
import shutil
|
||
import uuid
|
||
from PyPDF2 import PdfReader
|
||
import fitz # PyMuPDF
|
||
from utils.ocr_engine import OcrEngine # 请确保OcrEngine已经正确导入
|
||
from utils.local_ocr import LocalOCR
|
||
|
||
local_ocr = LocalOCR()
|
||
|
||
|
||
def ocr_extract(image_path):
|
||
# 调用您的OCR引擎来识别图像中的文本
|
||
# return OcrEngine.recognize_text_from_image(image_path)
|
||
# 调用本地ocr
|
||
return local_ocr.run(image_path)
|
||
|
||
|
||
def clean_page_content(text, common_header):
|
||
# 删除公共抬头
|
||
if common_header:
|
||
for header_line in common_header.split('\n'):
|
||
if header_line.strip():
|
||
text = re.sub(r'^' + re.escape(header_line.strip()) + r'\n?', '', text, count=1)
|
||
|
||
# 删除页码
|
||
text = re.sub(r'^\s*\d+\s*(?=\D)', '', text) # 开头页码
|
||
text = re.sub(r'\s+\d+\s*$', '', text) # 结尾页码
|
||
text = re.sub(r'\s*\/\s*\d+\s*', '', text) # 形如 /129
|
||
text = re.sub(r'\s*[—-]\s*\d+\s*[—-]\s*', '', text) # 形如 '—2—' 或 '-2-'
|
||
|
||
return text
|
||
|
||
|
||
def extract_common_header(pdf_path):
|
||
def get_headers(pdf_document, start_page, pages_to_read):
|
||
headers = []
|
||
for i in range(start_page, min(start_page + pages_to_read, len(pdf_document.pages))):
|
||
page = pdf_document.pages[i]
|
||
text = page.extract_text() or ""
|
||
if text:
|
||
first_lines = [line.strip() for line in text.strip().split('\n')[:3]]
|
||
headers.append(first_lines)
|
||
return headers
|
||
|
||
def find_common_headers(headers):
|
||
if not headers:
|
||
return []
|
||
|
||
common_headers = []
|
||
for lines in zip(*headers):
|
||
if all(line == lines[0] for line in lines[1:]):
|
||
common_headers.append(lines[0])
|
||
return common_headers
|
||
|
||
pdf_document = PdfReader(pdf_path)
|
||
total_pages = len(pdf_document.pages)
|
||
|
||
strategies = []
|
||
if total_pages >= 3:
|
||
middle_page = total_pages // 2
|
||
start_page = max(0, middle_page - 1)
|
||
strategies.append((start_page, 3))
|
||
elif total_pages == 2:
|
||
strategies.append((0, 2))
|
||
else:
|
||
strategies.append((0, 1))
|
||
|
||
if total_pages >= 3:
|
||
strategies.append((0, 3))
|
||
elif total_pages == 2:
|
||
strategies.append((0, 2))
|
||
elif total_pages == 1:
|
||
strategies.append((0, 1))
|
||
|
||
common_headers = []
|
||
|
||
for start, count in strategies:
|
||
headers = get_headers(pdf_document, start, count)
|
||
if len(headers) < 2:
|
||
continue
|
||
|
||
current_common = find_common_headers(headers)
|
||
if current_common:
|
||
common_headers = current_common
|
||
break
|
||
|
||
return '\n'.join(common_headers)
|
||
|
||
|
||
def extract_images_from_page(pdf_path, page_num):
|
||
images = []
|
||
try:
|
||
doc = fitz.open(pdf_path)
|
||
if page_num < 0 or page_num >= len(doc):
|
||
print(f"页码 {page_num + 1} 超出范围")
|
||
return images
|
||
|
||
page = doc.load_page(page_num)
|
||
image_list = page.get_images(full=True)
|
||
for img in image_list:
|
||
xref = img[0]
|
||
base_image = doc.extract_image(xref)
|
||
image_bytes = base_image['image']
|
||
image_ext = base_image.get('ext', 'png')
|
||
images.append({'data': image_bytes, 'ext': image_ext, 'page_num': page_num + 1})
|
||
except Exception as e:
|
||
print(f"提取图片时出错: {e}")
|
||
return images
|
||
|
||
|
||
def extract_text_json_by_page(file_path, text_threshold=10):
|
||
"""
|
||
提取PDF每页的文本，若文本量低于text_threshold，则提取图片并OCR。
|
||
:param file_path: PDF文件路径
|
||
:param text_threshold: 文本量阈值（字符数）
|
||
:return: 字典，键为页码，值为对应的文本
|
||
"""
|
||
common_header = extract_common_header(file_path)
|
||
result = {}
|
||
|
||
# 如果已经有保存的OCR结果,直接读取
|
||
if os.path.exists(file_path + ".json"):
|
||
with open(file_path + ".json", 'r', encoding='utf-8') as f:
|
||
result = json.load(f)
|
||
return result
|
||
|
||
try:
|
||
reader = PdfReader(file_path)
|
||
num_pages = len(reader.pages)
|
||
|
||
for page_num in range(num_pages):
|
||
page = reader.pages[page_num]
|
||
text = page.extract_text() or ""
|
||
cleaned_text = clean_page_content(text, common_header)
|
||
|
||
# 检查文本量是否低于阈值
|
||
if len(cleaned_text.strip()) < text_threshold:
|
||
print(f"第 {page_num + 1} 页文本量低，开始提取图片并OCR")
|
||
images = extract_images_from_page(file_path, page_num)
|
||
for img in images:
|
||
try:
|
||
with tempfile.NamedTemporaryFile(delete=False, suffix='.' + img['ext']) as temp_image:
|
||
temp_image.write(img['data'])
|
||
temp_image.flush()
|
||
# 调用OCR函数
|
||
ocr_result = ocr_extract(temp_image.name)
|
||
if ocr_result.strip():
|
||
cleaned_text += "\n" + ocr_result
|
||
except Exception as e:
|
||
print(f"OCR处理失败: {e}")
|
||
finally:
|
||
try:
|
||
os.remove(temp_image.name)
|
||
except Exception as e:
|
||
print(f"删除临时文件失败: {e}")
|
||
|
||
result[str(page_num + 1)] = cleaned_text
|
||
|
||
except Exception as e:
|
||
print(f"处理PDF时出错: {e}")
|
||
|
||
# 保存结果到JSON文件
|
||
try:
|
||
with open(file_path + ".json", 'w', encoding='utf-8') as f:
|
||
json.dump(result, f, ensure_ascii=False, indent=4)
|
||
except Exception as e:
|
||
print(f"保存结果到JSON文件时出错: {e}")
|
||
|
||
print("PDF预处理完成")
|
||
return result
|
||
|
||
|
||
if __name__ == '__main__':
|
||
pdf_path = "C:/test/所投主要产品检测报告.pdf"
|
||
res = extract_text_json_by_page(pdf_path)
|
||
print(json.dumps(res, ensure_ascii=False, indent=4))
|