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Mistral OCR

mistral.ai

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Re: Mistral OCR

#141

Post by cooperaustinj »

WhitneyLand wrote: post #50

1. There’s no simple page / sandbox to upload images and try it. Fine, I’ll code it up. 2. “Explore the Mistral AI APIs” ( https://docs.mistral.ai ) links to all apis except OCR. 3. The docs on the api params refer to document chunking and image chunking but no details on how their chunking works? So much unnecessary friction smh.

There is an OCR page on the link you provided. It includes a very, very simple curl command (like most of their docs).

I think the friction here exists outside of Mistral's control.

Re: Mistral OCR

#142

Post by mvac »

Great progress, but unfortunately, for our use case (converting medical textbooks from PDF to MD), the results are not as good as those by MinerU/PDF-Extract-Kit [1].

Also the collab link in the article is broken, found a functional one [2] in the docs.

[1] https://github.com/opendatalab/MinerU [2] https://colab.research.google.com/github/mistralai/cookbook/...

Re: Mistral OCR

#143

Post by riquito »

Thaxll wrote: post #130
lokl wrote: post #126

Tried with a few historical handwritten German documents, accuracy was abysmal.

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cultural heritage: Organizations and nonprofits that are custodians of heritage have been using Mistral OCR to digitize historical documents and artifacts, ensuring their preservation and making them accessible to a broader audience.

Re: Mistral OCR

#144

Post by amelius »

newfocogi wrote: post #5

They say: "releasing the API mistral-ocr-latest at 1000 pages / $" I had to reread that a few times. I assume this means 1000pg/$1 but I'm still not sure about it.

Hmm, can it read small print? ;)

Re: Mistral OCR

#146

Post by resiros »

evmar wrote: post #129

I noticed on the Arabic example they lost a space after the first letter on the third to last line, can any native speakers confirm? (I only know enough Arabic to ask dumb questions like this, curious to learn more.) Edit: it looks like they also added a vowel mark not present in the input on the line immediately after. Edit2: here's a picture of what I'm talking about, the before/after: https://ibb.co/v6xcPMHv

Arabic speaker here. No, it's perfect.

Re: Mistral OCR

#147

Post by Grosvenor »

kapitalx wrote: post #81

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.

Re: Mistral OCR

#148

Post by Squarex »

bugglebeetle wrote: post #105

Congrats to Mistral for yet again releasing another closed source thing that costs more than running an open source equivalent: https://github.com/DS4SD/docling

I am all for open source, but where do you see benchmarks that conclude that it's just equivalent?

Re: Mistral OCR

#149

Post by kbyatnal »

cxie wrote: 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…

re: real world implications, LLMs and VLMs aren't magi, and anyone who goes in expecting 100% automation is in for a surprise (especially in domains like medical or legal).

IMO there's still a large gap for businesses in going from raw OCR outputs —> document processing deployed in prod for mission-critical use cases.

e.g. you still need to build and label datasets, orchestrate pipelines (classify -> split -> extract), detect uncertainty and correct with human-in-the-loop, fine-tune, and a lot more. You can certainly get close to full automation over time, but it's going to take time and effort.

But for RAG and other use cases where the error tolerance is higher, I do think these OCR models will get good enough to just solve that part of the problem.

Disclaimer: I started a LLM doc processing company to help companies solve problems in this space (https://extend.app/)

Re: Mistral OCR

#150

Post by pzo »

randomNumber7 wrote: post #122
Asraelite wrote: post #107

I never thought I'd see the day where technology finally advanced far enough that we can edit a PDF.

I never thought driving a car is harder than editing a pdf.

It's not about harder but about what error you can tolerate. Here if you have accuracy 99% for many applications it's enough. If you have 99% accuracy per trip of no crash during self driving then you gonna be dead within a year very likely.

For cars we need accuracy at least 99.99% and that's very hard.

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