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DeepSeek OCR

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Re: DeepSeek OCR

#71

Post by CaptainOfCoit »

cahaya wrote: post #60
pietz wrote: post #42

My impression is that OCR is basically solved at this point. The OmniAI benchmark that's also referenced here wasn't updated with new models since February 2025. I assume that's because general purpose LLMs have gotten better at OCR than their own OCR product. I've been able to solve a broad range of OCR tasks by simply sending each page as an image to Gemini 2.5 Flash Lite and asking it nicely to extract the content…

Lot's of OCR/ LLM's (Even Gemini Pro 2.5) still struggle converting complex tables to markdown or HTML: Tables with multiple headers and merged cells that get mixed up, multiple columns with tick boxes get mixed up, multi page tables that are not understood correctly. Also Llamaindex fails miserably on those things. Curious to hear which OCR/ LLM excels with these specific issues? Example complex table: https://cdn.a…

> Lot's of OCR/ LLM's (Even Gemini Pro 2.5) still struggle converting complex tables to markdown or HTML:

But that's something else, that's no longer just OCR ("Optical Character Recognition"). If the goal suddenly changes from "Can take letters in images and make into digital text" to "Can replicate anything seen on a screen", the problem-space gets too big.

For those images you have, I'd use something like Magistral + Structured Outputs instead, first pass figure out what's the right structure to parse into, second pass to actually fetch and structure the data.

Re: DeepSeek OCR

#72

Post by eeixlk »

CaptainOfCoit wrote: post #71
cahaya wrote: post #60

Earlier quoted context omitted.

Lot's of OCR/ LLM's (Even Gemini Pro 2.5) still struggle converting complex tables to markdown or HTML: Tables with multiple headers and merged cells that get mixed up, multiple columns with tick boxes get mixed up, multi page tables that are not understood correctly. Also Llamaindex fails miserably on those things. Curious to hear which OCR/ LLM excels with these specific issues? Example complex table: https://cdn.a…

> Lot's of OCR/ LLM's (Even Gemini Pro 2.5) still struggle converting complex tables to markdown or HTML: But that's something else, that's no longer just OCR ("Optical Character Recognition"). If the goal suddenly changes from "Can take letters in images and make into digital text" to "Can replicate anything seen on a screen", the problem-space gets too big. For those images you have, I'd use something like Magistra…

htceaad t nofdnsy lyruuieo sieerrr t owcope?

Re: DeepSeek OCR

#73

Post by red75prime »

raincole wrote: post #47
pietz wrote: post #42

My impression is that OCR is basically solved at this point. The OmniAI benchmark that's also referenced here wasn't updated with new models since February 2025. I assume that's because general purpose LLMs have gotten better at OCR than their own OCR product. I've been able to solve a broad range of OCR tasks by simply sending each page as an image to Gemini 2.5 Flash Lite and asking it nicely to extract the content…

If you can accept that the machine just make up what it doesn't recognize instead of saying "I don't know," then yes it's solved. (I'm not being snarky. It's acceptable in some cases.)

Just checked it with Gemini 2.5 Flash. Instructing it to mark low-confidence words seems to work OK(ish).

Re: DeepSeek OCR

#74

Post by Y_Y »

jdthedisciple wrote: post #38
raincole wrote: post #29

Earlier quoted context omitted.

It's a very famous (classical) Chinese phrase. Both translations don't catch the meaning well though. It means: "worry before the rest of the world (notice that they have something to) worry." The next part is 後天下之樂而樂("be happy only after the rest of the world is happy.") I don't know why it's a prompt example.

Sibling comment has the second part as 后天下之乐而乐 which one is correct?

It depends on who you think is the rightful successor to the Qing dynasty

Re: DeepSeek OCR

#75

Post by numpad0 »

jdthedisciple wrote: post #39
gudzpoz wrote: post #32

Earlier quoted context omitted.

This clause is usually used together with the next sentence in the original poem: > 先天下之忧而忧，后天下之乐而乐 > (put the world's worries before yours, and put your happiness after the world's) > edit: this translation is wrong, and raincole has a definitely better translation Since the model is a language model, they probably use this to demonstrate the model's language capabilities – the model should be able to complete the w…

Sibling comment has the second part as 後天下之樂而樂 Which one is correct?

  a) 后天下之乐而乐
  b) 後天下之樂而樂
  c) 後天下之楽而楽
a) is clearly Simplified Chinese from a sibling comment, b) is Traditional copied from your comment, and c) is as I just typed in my own language. Unicode Hanzi/Kanji are a mess and there are characters same or different, in appearance or in binary, depending on intended variants, languages, fonts, systems, keyboard, distance between Earth and Alpha Centauri, etc.

Re: DeepSeek OCR

#76

Post by numpad0 »

yoran wrote: post #19

How does an LLM approach to OCR compare to say Azure AI Document Intelligence ( https://learn.microsoft.com/en-us/azure/ai-services/document... ) or Google's Vision API ( https://cloud.google.com/vision?hl=en )?

Classical OCR still probably make undesirable su6stıtutìons in CJK from there being far too many of similar ones, even some absurd ones that are only distinguishable under microscope or by looking at binary representations. LLMs are better constrained to valid sequences of characters, and so they would be more accurate.

Or at least that kind of thing would motivate them to re-implement OCR with LLM.

Re: DeepSeek OCR

#77

Post by CheeseFromLidl »

piker wrote: post #5

This looks really cool for prototyping and playing around. It seems to me though if one is building a modern application that needs to get image segmentation and/or text recognition right there are better APIs available than natural language? It seems like a lot of effort to make a production-scale CV application to weigh it down with all of an LLM’s shortcomings. Not a field I’m familiar with but I would assume that…

As a hobby photographer, I organise everything for speedy retrieval but this would be amazing to search my collection.

Re: DeepSeek OCR

#78

Post by sbinnee »

pietz wrote: post #42

My impression is that OCR is basically solved at this point. The OmniAI benchmark that's also referenced here wasn't updated with new models since February 2025. I assume that's because general purpose LLMs have gotten better at OCR than their own OCR product. I've been able to solve a broad range of OCR tasks by simply sending each page as an image to Gemini 2.5 Flash Lite and asking it nicely to extract the content…

Maybe for English. Other languages are very much not solved.

Re: DeepSeek OCR

#79

Post by [deleted] »

krackers wrote: post #8

The paper is more interesting than just another VLM for OCR, they start talking about compression and stuff. E.g. there is this quote >Our work represents an initial exploration into the boundaries of vision-text compression, investigating how many vision tokens are required to decode text tokens. The preliminary results are encouraging: DeepSeek-OCR achieves near-lossless OCR compression at approximately 10× ratios,…

[deleted]

Re: DeepSeek OCR

#80

Post by 2big2fail_47 »

I find it interesting that there's all these independent AI-OCR Projects but still no commercial offering. Is it still too inaccurate, too complex or simply too expensive?
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