[elanning]

I’ve done a lot of OCR work and tesseract is nearly a decade out of date at this point. It is not a serious technology for anything requiring good accuracy or minor complexity. From what I’ve seen, GPT-4V completely smokes tesseract, but then again, most modern OCR systems do. If you want fast and pretty powerful OCR, check out paddle. If you want slower but higher accuracy, check out transformer based models such as TrOCR.

[nh2]

See this for a comparison of PaddleOCR, TrOCR, and various cloud ones (note: on documents of typed and handwritten text):

https://news.ycombinator.com/item?id=32077375

[authorfly]

Caveat that being from 2022, the Tesseract version used was almost certainly v4 (if Linux), rather than v5 which is much better (and widely available on Windows in 2022, but not Linux yet).

However Tesseract is quite behind still as you note, even with v5.

[authorfly]

Running PaddleOCR in production now, I would suggest contrasting Tesseract v4 and v5, since v5 is a lot better(but until recently has not been available on Linux) - PaddleOCR does still smoke it though, you are right (especially for concurrency and fairly easily just setting different workers to different GPUs for best concurrent batching).

[cpursley]

How is Paddle on complex data tables? This is my biggest challenge at the moment.

[Zuiii]

Tesseract's true value is being one apt-get command away (i.e. opensource). Does Debian host more modern OCR systems in their repos?

[nunez]

Tesseract the tool is one apt-get away but the trained models are not, and I've found that they are a starting point, not a final destination. You still have to do more training on top of them for anything that isn't black text on a crisp white background.

[elanning]

Big mistake on my part; I should clarify I fine-tuned both PaddleOCR and TrOCR on large amounts of data specific to my domain. I cannot speak on the best out of the box “ready to go” solutions (besides cloud ones, which were quite good with the right pre and post processing).