mirror of
https://github.com/luzhisheng/js_reverse.git
synced 2025-04-20 03:59:57 +08:00
提取pdf文件中图片和文字
This commit is contained in:
aiyingfeng
parent
749cf70dcd
commit
b13155d7f2
@ -1,4 +1,4 @@
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from program.discern import Discern
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from program.testing_agency_report import TestingAgencyReport
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discern = Discern()
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discern.run('./file_test')
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testing_agency_report = TestingAgencyReport()
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testing_agency_report.run('./file', './target_img', './docs')
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@ -1,65 +0,0 @@
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from datetime import datetime
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from base import Base
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from PIL import Image
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import pytesseract
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import platform
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class ImageTextOcr(Base):
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def __init__(self):
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super(ImageTextOcr, self).__init__()
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current_os = platform.system()
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if current_os == 'Windows':
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pytesseract.pytesseract.tesseract_cmd = r'E:\pc\tesseract-ocr\tesseract.exe'
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self.log("当前操作系统是 Windows")
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elif current_os == 'Linux':
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self.log("当前操作系统是 Ubuntu")
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else:
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self.log(f"当前操作系统是 {current_os}")
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def is_valid_time(self, input_str):
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try:
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valid_time = datetime.strptime(input_str, "%Y-%m-%d") # 根据实际时间格式调整
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return valid_time
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except ValueError:
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return False
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def image_text_ocr(self, text_dict, path):
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valid_time_list = []
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# 加载图像
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image = Image.open(path)
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result = pytesseract.image_to_string(image, config=r'--oem 3 --psm 6 -l chi_sim+eng')
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lines = result.split()
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for line in lines:
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if 'S$T' in line or 'SST' in line:
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text_dict['方案编号'] = line.replace('S$T', 'SST').replace('试验方案编号:', '')
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if 'CNAS' in line:
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text_dict['标志'] = 'cnas中文,'
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if '200015344424' in line:
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text_dict['标志'] = '国cma,'
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valid_time = self.is_valid_time(line)
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if valid_time:
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valid_time_list.append(valid_time)
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if valid_time_list:
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text_dict['签发日期'] = max(valid_time_list).strftime("%Y-%m-%d")
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return text_dict
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def run(self, text_dict, path):
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res_list = self.image_text_ocr(text_dict, path)
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return res_list
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if __name__ == '__main__':
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image_text_ocr = ImageTextOcr()
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text_dict = {
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'方案编号': '',
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'签发日期': '',
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'标志': ''
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}
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res = image_text_ocr.run(text_dict, '../target_img/output_image-003.png')
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print(res)
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101
pdf处理/program/pdf_base.py
Normal file
101
pdf处理/program/pdf_base.py
Normal file
@ -0,0 +1,101 @@
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from datetime import datetime
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from base import Base
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import subprocess
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from PIL import Image
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import pandas as pd
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import pytesseract
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import platform
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import os
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class PDFBase(Base):
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def __init__(self):
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super(Base, self).__init__()
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current_os = platform.system()
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if current_os == 'Windows':
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pytesseract.pytesseract.tesseract_cmd = r'E:\pc\tesseract-ocr\tesseract.exe'
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self.log("当前操作系统是 Windows")
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elif current_os == 'Linux':
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self.log("当前操作系统是 Ubuntu")
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else:
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self.log(f"当前操作系统是 {current_os}")
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def download_img(self, input_pdf, output_image):
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"""
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下载pdf中全部图片
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:param input_pdf:
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:param output_image:
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:return:
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"""
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try:
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subprocess.run(f"pdfimages -png '{input_pdf}' {output_image}/image", shell=True,
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capture_output=True, text=True)
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except Exception as e:
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self.log(f"出现异常：{e}")
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@staticmethod
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def read_img_ocr(img_path):
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"""
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读取图片中文字内容
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:param img_path:
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:return:
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"""
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image = Image.open(img_path)
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result = pytesseract.image_to_string(image, config=r'--oem 3 --psm 6 -l chi_sim+eng')
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lines = result.split()
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return lines
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def remove_img(self, img_path):
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"""
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删除当前文件夹下所有的图片
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:param img_path:
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:return:
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"""
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with os.scandir(img_path) as entries:
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for entry in entries:
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if entry.is_file():
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file_path = entry.path
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try:
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os.remove(file_path)
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except Exception as e:
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self.log(f"错误信息：{e}")
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@staticmethod
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def is_valid_time(input_str):
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"""
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判断是否是时间格式
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:param input_str:
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:return:
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"""
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try:
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valid_time = datetime.strptime(input_str, "%Y-%m-%d")
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return valid_time
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except ValueError:
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return False
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@staticmethod
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def export_excel(export, excel_path):
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"""
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将字典列表转换为DataFrame
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:param export:
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:return:
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"""
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pf = pd.DataFrame(list(export))
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current_time = datetime.now()
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formatted_time = current_time.strftime('%Y-%m-%d-%H-%M-%S')
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file_path = pd.ExcelWriter(f'{excel_path}/无源{formatted_time}.xlsx')
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# 替换空单元格
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pf.fillna(' ', inplace=True)
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# 输出
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pf = pf.sort_values(by='样品名称')
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pf.to_excel(file_path, index=False)
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# 保存表格
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file_path.close()
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if __name__ == '__main__':
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pdf_base = PDFBase()
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# pdf_base.download_img('../file_test/1.pdf', '../target_img/')
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res = pdf_base.read_img_ocr('../target_img/image-017.png')
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print(res)
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@ -1,67 +1,56 @@
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import pandas as pd
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from PIL import Image
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from program.pdf_base import PDFBase
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import pdfplumber
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import re
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import PyPDF2
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from datetime import datetime
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from base import Base
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from program.image_text_ocr import ImageTextOcr
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import os
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import cv2
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import os
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import re
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class Discern(Base):
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class TestingAgencyReport(PDFBase):
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def __init__(self):
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super(Discern, self).__init__()
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self.image_text_ocr = ImageTextOcr()
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super(TestingAgencyReport, self).__init__()
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self.xlsx_keys = {}
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self.xlsx_keys_list = []
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self.num = 0
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def export_excel(self, export):
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# 将字典列表转换为DataFrame
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pf = pd.DataFrame(list(export))
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current_time = datetime.now()
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formatted_time = current_time.strftime('%Y-%m-%d-%H-%M-%S')
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file_path = pd.ExcelWriter(f'./docs/无源{formatted_time}.xlsx')
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# 替换空单元格
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pf.fillna(' ', inplace=True)
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# 输出
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pf = pf.sort_values(by='样品名称')
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pf.to_excel(file_path, index=False)
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# 保存表格
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file_path.close()
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def pdf_images(self, pdf_path, img_path):
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self.download_img(pdf_path, img_path)
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with os.scandir(img_path) as entries:
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for entry in entries:
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if entry.is_file():
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text_dict = {
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'方案编号': '',
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'签发日期': '',
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'标志': ''
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}
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def is_valid_time(self, input_str):
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try:
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valid_time = datetime.strptime(input_str, "%Y-%m-%d") # 根据实际时间格式调整
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return valid_time
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except ValueError:
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return False
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try:
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lines = self.read_img_ocr(entry.path)
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valid_time_list = []
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for line in lines:
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if 'S$T' in line or 'SST' in line:
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text_dict['方案编号'] = line.replace('S$T', 'SST').replace('试验方案编号:', '')
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def pdf_all_text(self, pdf_path):
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with pdfplumber.open(pdf_path) as pdf:
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for page in pdf.pages[1:]:
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# 提取页面文本
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text = page.extract_text()
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lines = text.split()
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valid_time_list = []
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for line in lines:
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if 'SST' in line and not self.xlsx_keys['方案编号']:
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self.xlsx_keys['方案编号'] = line
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if 'CNAS' in line:
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text_dict['标志'] = 'cnas中文,'
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if '签发日期' in line and not self.xlsx_keys['签发日期']:
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self.xlsx_keys['签发日期'] = line.replace('签发日期', '')
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if '200015344424' in line:
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text_dict['标志'] = '国cma,'
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if 'GLP' in line:
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self.xlsx_keys['标志'] += 'GLP,'
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valid_time = self.is_valid_time(line)
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if valid_time:
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valid_time_list.append(valid_time)
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if valid_time_list:
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text_dict['签发日期'] = max(valid_time_list).strftime("%Y-%m-%d")
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except cv2.error as c:
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self.log(c)
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valid_time = self.is_valid_time(line)
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if valid_time:
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valid_time_list.append(valid_time)
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if valid_time_list:
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self.xlsx_keys['签发日期'] = max(valid_time_list).strftime("%Y-%m-%d")
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if text_dict.get('标志'):
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self.xlsx_keys['标志'] += text_dict.get('标志')
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if text_dict.get('方案编号'):
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self.xlsx_keys['方案编号'] = text_dict.get('方案编号')
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if text_dict.get('签发日期'):
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self.xlsx_keys['签发日期'] = text_dict.get('签发日期')
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def pdf_text(self, pdf_path):
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with pdfplumber.open(pdf_path) as pdf:
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@ -97,67 +86,32 @@ class Discern(Base):
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self.xlsx_keys['公司名称'] = self.xlsx_keys['公司名称'].replace('中检华通威国际检验(苏州)有限公司', ''). \
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replace('中检华通威国际检验（苏州）有限公司', '')
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def processing_image(self, img_file, standard=205):
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""" 1.将图片进行降噪处理, 通过二值化去掉后面的背景色并加深文字对比度 """
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img = Image.open(img_file)
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img = img.convert('L')
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pixels = img.load()
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for x in range(img.width):
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for y in range(img.height):
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if pixels[x, y] > standard:
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pixels[x, y] = 255
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else:
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pixels[x, y] = 0
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img.save(img_file)
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def pdf_all_text(self, pdf_path):
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with pdfplumber.open(pdf_path) as pdf:
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for page in pdf.pages[1:]:
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# 提取页面文本
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text = page.extract_text()
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lines = text.split()
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valid_time_list = []
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for line in lines:
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def pdf_images(self, pdf_path):
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self.num = 0
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pdf_reader = PyPDF2.PdfReader(pdf_path)
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for page_num in range(len(pdf_reader.pages)):
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page = pdf_reader.pages[page_num]
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xObject = page['/Resources']['/XObject'].get_object()
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if 'SST' in line and not self.xlsx_keys['方案编号']:
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self.xlsx_keys['方案编号'] = line
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for obj in xObject:
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if xObject[obj]['/Subtype'] == '/Image':
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self.num += 1
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image_file = f"./target_img/image_{self.num}.png"
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with open(image_file, "wb") as f:
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f.write(xObject[obj].get_data())
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if page_num != 0:
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self.processing_image(image_file)
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if '签发日期' in line and not self.xlsx_keys['签发日期']:
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self.xlsx_keys['签发日期'] = line.replace('签发日期', '')
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def get_images_text(self):
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for i in range(1, self.num + 1):
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text_dict = {
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'方案编号': '',
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'签发日期': '',
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'标志': ''
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}
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try:
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text_dict = self.image_text_ocr.run(text_dict, f'./target_img/image_{i}.png')
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except cv2.error as c:
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self.log(c)
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pass
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if 'GLP' in line:
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self.xlsx_keys['标志'] += 'GLP,'
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if text_dict.get('标志'):
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self.xlsx_keys['标志'] += text_dict.get('标志')
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if text_dict.get('方案编号'):
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self.xlsx_keys['方案编号'] = text_dict.get('方案编号')
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if text_dict.get('签发日期'):
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self.xlsx_keys['签发日期'] = text_dict.get('签发日期')
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valid_time = self.is_valid_time(line)
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if valid_time:
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valid_time_list.append(valid_time)
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if valid_time_list:
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self.xlsx_keys['签发日期'] = max(valid_time_list).strftime("%Y-%m-%d")
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def remove_file(self, folder_path):
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with os.scandir(folder_path) as entries:
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for entry in entries:
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if entry.is_file():
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file_path = entry.path
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try:
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os.remove(file_path)
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except Exception as e:
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pass
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def run(self, folder_path):
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with os.scandir(folder_path) as entries:
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def discern(self, pdf_path, img_path, excel_path):
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with os.scandir(pdf_path) as entries:
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for entry in entries:
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self.xlsx_keys = {
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'登记日期': '',
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@ -170,26 +124,30 @@ class Discern(Base):
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'签发日期': '',
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'公司名称': ''
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}
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self.remove_file('./target_img')
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self.remove_img(img_path)
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if entry.is_file():
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file_path = entry.path
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pdf_path = entry.path
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file_name = entry.name
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self.log(file_name)
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self.xlsx_keys['文件名'] = file_name
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self.pdf_text(file_path)
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self.pdf_images(file_path)
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self.get_images_text()
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self.pdf_all_text(file_path)
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self.pdf_text(pdf_path)
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self.pdf_images(pdf_path, img_path)
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self.pdf_all_text(pdf_path)
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if not self.xlsx_keys['方案编号']:
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matches = re.findall(r'SST\d+BB', file_name)
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if matches:
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self.xlsx_keys['方案编号'] = matches[0]
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else:
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self.log("未找到匹配的模式方案编号")
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self.xlsx_keys_list.append(self.xlsx_keys)
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self.export_excel(self.xlsx_keys_list)
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self.export_excel(self.xlsx_keys_list, excel_path)
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def run(self, pdf_path, img_path, excel_path):
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self.discern(pdf_path, img_path, excel_path)
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if __name__ == '__main__':
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discern = Discern()
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discern.run('./file_test')
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testing_agency_report = TestingAgencyReport()
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testing_agency_report.run('../file_test', '../target_img', '../docs')
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