This link was a good reference while figuring out how to find tables. I'll provide some brief examples for a couple of the steps that do require code. Some of the steps don't require code, they take advantage of external tools like pdfimages and tesseract. I wrote a python package with modules that can help with those steps. Use OpenCV to crop and clean up each cell so that there is no noise that will confuse OCR software.Ĭombine the extracted text of each cell into the format you need. Use OpenCV to find and extract each cell from the table. Use Tesseract to detect rotation and ImageMagick mogrify to fix it. Use pdfimages from to turn the pages of the pdf into images. I could not find a workable off-the-shelf solution nothing that gave me the accuracy I needed. I'll try to keep them in sync.This answer is for anyone encountering pdfs with images and needing to use OCR. With open('example.pdf', 'rb') as in_file:ĭevice = TextConverter(rsrcmgr, output_string, laparams=LAParams()) from io import StringIOįrom pdfminer.pdfdocument import PDFDocumentįrom pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter This method is suggested in the other answers, but I would only recommend this when you need to customize some component. For example, it allows you to create your own layout algorithm. There is also a composable api that gives a lot of flexibility in handling the resulting objects. ![]() ![]() from pdfminer.high_level import extract_text This approach is the go-to solution if you want to programmatically extract information from a PDF. ![]() If you want to extract text (properties) with Python, you can use the high-level api. If you want to extract text just once you can use the commandline tool pdf2txt.py: $ pdf2txt.py example.pdf (All the examples assume your PDF file is called example.pdf) Behind the scenes, all of these api's use the same logic for parsing and analyzing the layout. Nowadays, it has multiple api's to extract text from a PDF, depending on your needs. It is a community-maintained version of pdfminer for python 3. Here's his benchmarkįull disclosure, I am one of the maintainers of pdfminer.six. Update (): According to Martin Thoma, PyPDF2 has improved a lot in the past 2 years, so do give it a try as well. Pdfminer.six also has a huge footprint, requiring pycryptodome which needs GCC and other things installed pushing a minimal install docker image on Alpine Linux from 80 MB to 350 MB. I timed text extraction with timeit on a 15" MBP (2018), timing only the extraction function (no file opening etc.) with a 10 page PDF and got the following results: PDFminer.six: 2.88 sec However, text extraction with PDFminer.six is significantly slower than PyPDF2 by a factor of 6. PDFminer.six works more reliably than PyPDF2 (which fails with certain types of PDFs), in particular PDF version 1.7 Performance and Reliability compared with PyPDF2 ![]() If the PDF is already in memory, for example if retrieved from the web with the requests library, it can be converted to a stream using the io library: import io Or alternatively: with open('report.pdf','rb') as f: Using a PDF saved on disk text = extract_text('report.pdf') Importing the package from pdfminer.high_level import extract_text Installing the package $ pip install pdfminer.six This works in May 2020 using PDFminer six in Python3. I used the Python library pdfminer.six, released on November 2018. Verified in Python Version 3.xĮdit: The solution works with Python 3.7 at October 3, 2019. PDFMiner's structure changed recently, so this should work for extracting text from the PDF files.Įdit : Still working as of the June 7th of 2018. Interpreter = PDFPageInterpreter(rsrcmgr, device)įor page in PDFPage.get_pages(fp, pagenos, maxpages=maxpages, password=password,caching=caching, check_extractable=True): Here is a working example of extracting text from a PDF file using the current version of PDFMiner(September 2016) from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreterįrom nverter import TextConverterĭevice = TextConverter(rsrcmgr, retstr, codec=codec, laparams=laparams)
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |