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pfdomizer

4 karmajoined 4 bulan yang lalu

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1 points·by pfdomizer·16 jam yang lalu·0 comments

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1 points·by pfdomizer·3 bulan yang lalu·0 comments

Show HN: We built an OCR server that can process 270 dense images/s on a 5090

github.com
8 points·by pfdomizer·3 bulan yang lalu·2 comments

TurboOCR: CUDA and TensorRT OCR Server at 270 img/s

github.com
2 points·by pfdomizer·3 bulan yang lalu·0 comments

Show HN: TurboOCR up to 1200 pages/s with Paddle and TensorRT (C++/CUDA, FP16)

github.com
3 points·by pfdomizer·3 bulan yang lalu·0 comments

TurboOCR: 270–1200 img/s OCR with Paddle and TensorRT (C++/CUDA, FP16)

github.com
7 points·by pfdomizer·3 bulan yang lalu·4 comments

comments

pfdomizer
·3 bulan yang lalu·discuss
No but it should work i just tested it on a 5090
pfdomizer
·3 bulan yang lalu·discuss
Thanks, happy to hear that!
pfdomizer
·3 bulan yang lalu·discuss
Docling and MinerU are great for structured output like markdown and table extraction, but they run at 1-5 pages/s because of the VLMs under the hood.

Turbo-OCR gives you bounding boxes, text, and layout regions at multiple hundred img/s depending on the text density. When you have many PDFs to process, it makes a huge difference. You can always pipe the output into a VLM for the pages that need deeper extraction. Structured extraction and markdown output are on the roadmap (without sacrificing too much speed).