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Mistral OCR

mistral.ai

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Re: Mistral OCR

#152
post #40

The new Mistral OCR release looks impressive - 94.89% overall accuracy and significantly better multilingual support than competitors. As someone who's built document processing systems at scale, I'm curious about the real-world implications. Has anyone tried this on specialized domains like medical or legal documents? The benchmarks are promising, but OCR has always faced challenges with domain-specific terminology…

I'd love to try it for my domain (regulation), but $1/1000 pages is significantly more expensive than my current local Docling based setup that already does a great job of processing PDF's for my needs.

I think for regulated fields / high impact fields $1/1000 is well-worth the price; if the accuracy is close to 100% this is way better than using people, who are still error-prone

Re: Mistral OCR

#153
post #136

Co-founder of doctly.ai here (OCR tool) I love mistral and what they do. I got really excited about this, but a little disappointed after my first few tests. I tried a complex table that we use as a first test of any new model, and Mistral OCR decided the entire table should just be extracted as an 'image' and returned this markdown: ``` ![img-0.jpeg](img-0.jpeg) ``` I'll keep testing, but so far, very disappointing…

Where did you test it? At the end of the post they say: > Mistral OCR capabilities are free to try on le Chat but when asked, Le Chat responds: > can you do ocr? > I don't have the capability to perform Optical Character Recognition (OCR) directly. However, if you have an image with text that you need to extract, you can describe the text or provide details, and I can help you with any information or analysis related…

Yes I used the API. They have examples here:

https://docs.mistral.ai/capabilities/document/

I used base64 encoding of the image of the pdf page. The output was an object that has the markdown, and coordinates for the images:

[OCRPageObject(index=0, markdown='![img-0.jpeg](img-0.jpeg)', images=[OCRImageObject(id='img-0.jpeg', top_left_x=140, top_left_y=65, bottom_right_x=2136, bottom_right_y=1635, image_base64=None)], dimensions=OCRPageDimensions(dpi=200, height=1778, width=2300))] model='mistral-ocr-2503-completion' usage_info=OCRUsageInfo(pages_processed=1, doc_size_bytes=634209)

Re: Mistral OCR

#154

This is incredibly exciting. I've been pondering/experimenting on a hobby project that makes reading papers and textbooks easier and more effective. Unfortunately the OCR and figure extraction technology just wasn't there yet. This is a game changer. Specifically, this allows you to associate figure references with the actual figure, which would allow me to build a UI that solves the annoying problem of looking for a…

Wait does this deal with images?

The output includes images from the input. You can see that on one of the examples where a logo is cropped out of the source and included in the result.

Re: Mistral OCR

#157
post #130

Earlier quoted context omitted.

HTR ( Handwritten Text Recognition ) is a completely different space than OCR. What were you expecting exactly?

It fits the "use cases" mentioned in the article > Preserving historical and cultural heritage: Organizations and nonprofits that are custodians of heritage have been using Mistral OCR to digitize historical documents and artifacts, ensuring their preservation and making them accessible to a broader audience.

There is a difference between historical document and "my doctor prescription".

Someone coming here and saying it does not work with my old german hanwriting doesn't say much.

Re: Mistral OCR

#158
But what's the need exactly for OCR when you have multimodal LLMs that can read the same info and directly answer any questions about it ?

For a VLLM, my understanding is that OCR corresponds to a sub-field of questions, of the type 'read exactly what's written in this document'.

Re: Mistral OCR

#160

Co-founder of doctly.ai here (OCR tool) I love mistral and what they do. I got really excited about this, but a little disappointed after my first few tests. I tried a complex table that we use as a first test of any new model, and Mistral OCR decided the entire table should just be extracted as an 'image' and returned this markdown: ``` ![img-0.jpeg](img-0.jpeg) ``` I'll keep testing, but so far, very disappointing…

Does doctly do handwritten forms like dates? I have a lot of "This document filed and registered in the county of ______ on ______ of _____ 2023" sort of thing.

We've been getting great results with those aswell. But ofcourse there is always some chance of not getting it perfect, specially with different handwritings.

Give it a try, no credit cards needed to try it. If you email me (ali@doctly.ai) i can give you extra free credits for testing.

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