非机构化解析【包含PDF、word、PPT】

此项目是针对PDF、docx、doc、PPT四种非结构化数据进行解析，识别里面的文本和图片。

代码结构

├── Dockerfile
├── requirements
├── resluts
├── test_data
│   ├── 20151202033304658.pdf
│   ├── 2020_World_Energy_Data.pdf
│   ├── 2022110404_pdf.docx
│   ├── 2022110404_pdf.pdf
│   ├── H3_AP201701200282787162_01.pdf
│   ├── H3_AP202205271568109307_1.pdf
│   ├── H3_AP202205271568109307_1.pptx
│   ├── test.pdf
│   ├── test.pptx
│   ├── test_table.pdf
│   └── test_word.docx
├── Unstr_ApiSever.py ###----------API服务
├── Unstructured_PDF_Operation_Code.py
├── Unstructured_PPT_Operation_Code.py
├── Unstructured_Word_Operation_Code.py

PDF操作

部分代码展示

import fitz,os
doc = fitz.open('./test_data/2022110404_pdf.pdf')
def func(doc):for i in range(len(doc)):imglist = doc.getPageImageList(i)for j, img in enumerate(imglist):xref = img[0]pix = fitz.Pixmap(doc, xref)  # make pixmap from imageif pix.n - pix.alpha < 4:  # can be saved as PNGpix.writePNG("p%s-%s.png" % (i + 1, j + 1))else:  # CMYK: must convert firstpix0 = fitz.Pixmap(fitz.csRGB, pix)pix0.writePNG("p%s-%s.png" % (i + 1, j + 1))pix0 = None  # free Pixmap resourcespix = None  # free Pixmap resourcesif __name__ == "__main__":func(doc=fitz.open('./test_data/2022110404_pdf.pdf'))         # input the path of pdf filefunc1('./test_data')  # input the path of pdf file            pdf_path = "./test_data/2022110404_pdf.pdf"doc = fitz.open(pdf_path)num_pages = doc.page_count# Text info of PDFfor page_index in range(num_pages):page = doc.load_page(page_index)text = page.get_text()print(f"第{page_index + 1}页的文本内容为：\n{text}\n")

结果如下：
在这里插入图片描述

word操作

import docx
import os, re
from docx import Documentclass Word:"""Word操作"""def Word_get_pictures(self,infile):try:in_File = infile.split('/')[2][:-5]  ##---------Word名称new_filepath = os.path.join('%s/%s') % ('./resluts', in_File)doc = docx.Document(infile)dict_rel = doc.part._relsfor rel in dict_rel:rel = dict_rel[rel]if "image" in rel.target_ref:if not os.path.exists(new_filepath):os.makedirs(new_filepath)img_name = re.findall("/(.*)", rel.target_ref)[0]word_name = os.path.splitext(new_filepath)[0]if os.sep in word_name:new_name = word_name.split('\\')[-1]else:new_name = word_name.split('/')[-1]img_name = f'{new_name}-' + '-' + f'{img_name}'with open(f'{new_filepath}/{img_name}', "wb") as f:f.write(rel.target_part.blob)except:passdef Word_Get_txt(self,infile):in_File = infile.split('/')[2][:-5]  ##---------Word名称new_filepath = os.path.join('%s/%s') % ('./resluts', in_File)document = Document(infile)all_paragraphs = document.paragraphsall_tables = document.tableswith open(os.path.join("%s/%s.txt") % (new_filepath, "resluts"), 'w', encoding='utf-8') as f:for paragraph in all_paragraphs:# print(paragraph.text.replace("   ", "").replace(" ", ""))f.write(paragraph.text.replace("   ", "").replace(" ", ""))for table in all_tables:for row in table.rows:for cell in row.cells:f.write(cell.text)# print(cell.text)  # 打印
if __name__ == '__main__':# 获取文件夹下的word文档列表,路径自定义# os.chdir("./test_data/2022110404_pdf.docx")Word().Word_get_pictures("./test_data/2022110404_pdf.docx")Word().Word_Get_txt("./test_data/2022110404_pdf.docx")

结果如下：
在这里插入图片描述

PPT操作

import os
from zipfile import ZipFile
from pptx import Presentation
from docx import Documentclass PPT:def PPT_get_pictrue(self,infile):in_File = infile.split('/')[2][:-5] new_filepath = os.path.join('%s/%s') % ('./resluts', in_File)if not os.path.exists(new_filepath):os.makedirs(new_filepath)with ZipFile(infile) as f:for file in f.namelist():if file.startswith("ppt/media/"):f.extract(file, path=new_filepath)return new_filepathdef PPT_get_words_to_txt(self,inpath, outpath):m_ppt = Presentation(inpath)# print(len(m_ppt.slides))with open(os.path.join('%s/%s.txt') % (outpath, 'resluts'), 'w', encoding='utf-8') as f:for slide in m_ppt.slides: for shape in slide.shapes:if not shape.has_text_frame: continuefor paragraph in shape.text_frame.paragraphs: for content in paragraph.runs:f.write(content.text + '\n')def PPT_get_words_to_docx(self,filepath,save_path):wordfile = Document()pptx = Presentation(filepath)for slide in pptx.slides:for shape in slide.shapes:if shape.has_text_frame:text_frame = shape.text_framefor paragraph in text_frame.paragraphs:wordfile.add_paragraph(paragraph.text)wordfile.save(save_path)if __name__ == "__main__":infile = "./test_data/OpenCV算法解析.pptx"new_infile=PPT().PPT_get_pictrue(infile)PPT().PPT_get_words_to_txt(infile,new_infile)

结果如下：
在这里插入图片描述