Ask HN: How to OCR a PDF and preserve whitespace?

I’ve found that the built in OCR in the iPhone is just way better and more accurate than everything else out there. I’m talking about how if you have an image in your camera roll on the iPhone, you can select the text and copy it out. I had the idea to simply expose that service better so it could be applied to PDFs and made my first ever iPhone app that does this. It can easily handle hundreds of pages too. Only problem is that it’s an iPhone app so it can’t easily be included in a programmatic fashion, but if you’re only trying to convert a reasonable number of documents it’s worth a try— the accuracy is really good:

https://apps.apple.com/us/app/super-pdf-ocr/id6479674248

Not sure if a multi-step is ok, but convert pdf to image format such as png, use AI to recognize 'tabular blocks', convert pdf to 'text format' with tabular blocks as embeddable image to preserve spacing.

https://stackoverflow.com/questions/3203790/parsing-pdf-file...

https://excalibur-py.readthedocs.io/en/master/

https://ledgerbox.io/blog/extract-tables-with-tesseract-ocr

https://www.johnsnowlabs.com/extract-tabular-data-from-pdf-i...

bit more in-depth review : https://dev.to/upsilon_it/how-to-extract-tabular-data-from-p...

Did you try textract? https://aws.amazon.com/textract/

In my experience it works amazingly well with columns / tabulated content.

Many of the free or cheap OCR services are based on the free, open-source Tesseract OCR.

https://github.com/tesseract-ocr/tesseract/

Those services usually do not expose all of the options. If you’re handy with shell scripts or Python, you can probably get better performance by hand-tuning options for your particular images. For example, if I recall there are page segmentation options to tell Tesseract to expect multi-column text. That alone might get you better performance than the automatic mode.

Do give LLMWhisperer[1] a try. It does a good job preserving the layout for the most part — but one cannot escape PDF hell.

Try LLMwhisperer Playground[2] with your documents; there is no need for any setup.

Extracting multi-column layout example - https://imgur.com/roYmv0I

[1] https://llmwhisperer.unstract.com/ [2] https://pg.llmwhisperer.unstract.com/

Can you use ImageMagick to split the columns into single files…? E.g. if the columns are the same on every page, you can feed the coordinates to ImageMagick. Then do OCR on each of those files.

Tabula works for tables.

But if you think about space and font widtgs, youll realize nontrivial. Fonts are often variable sizes and table alignments are often left, right or center aligned.

A more general tool ive used is PaddleOCR

Your use case seems very specific. I personally am very happy with ocrmypdf[1], which is free and puts an invisible text layer into the pdf. However, since it is free, I'm pretty sure it cannot compete with the commercial solutions you tried.

There also is an older version PDF XChange viewer, that has the ability to do the same thing, although it is presented as "viewer".

1: https://github.com/ocrmypdf/OCRmyPDF/

LLMWhisperer from Zipstack at https://llmwhisperer.unstract.com/ or https://github.com/VikParuchuri/surya will do a good job for you.

LLMWhisperer has some nice tooling where they can fall back to OCR as well forcing text extraction from scanned documents as well as documents that have the text preserved as text.

Google’s OCR service is reliably accurate and can handle large documents (up to 20MB) https://cloud.google.com/vision/docs/ocr

I've had really good results with Python's pdfminer.six, it's also very easy to use.

https://pypi.org/project/pdfminer.six/

we have an internal api at markets.sh for ingesting large financial reports and newspaper data. solves this exact problem. i‘ll be happy to give you test access. drop me an email at max at markets.sh

You could try this one here: https://github.com/madnight/pdf-layout-text-stripper