Quick and Dirty OCR of Facebook Papers

Gizmodo has been working through the Facebook Papers and releasing the docs that they process and review.

As luck would have it, I had some ugly but functional code lying around that would do a first pass on OCR on these docs. That code is in the pdf_to_image.py script. I’d welcome improvement to the code, especially in image cleanup prior to OCR (lines 92-97, approx). I experimented with cleaning up the image via PIL and cv2, but the results were less accurate, almost certainly due to my lack of familiarity with either of these approaches.

These Facebook Papers are especially challenging from an OCR perspective because many of them are pictures taken of a screen, so the base image quality isn’t especially good. Because of this, not every document can be processed cleanly, and the documents that do get processed have some cruft in them.

With that said, the text pulled from these files simplifies the process of parsing through a large amount of data for keywords.

Other (Better) Options

This OCR should be seen as a first step. Text files are generally a decent starting point because they allow for a wide range of follow on analysis.

And, other/better options exist. For a comprehensive, contained analysis, these other options will almost certainly be a better choice.

Want to help?

If you want to collaborate on this project, let me know!

GitHub

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