HackerTrans
TopNewTrendsCommentsPastAskShowJobs

pfdomizer

4 karmajoined 4 ay önce

Submissions

[untitled]

1 points·by pfdomizer·dün·0 comments

[untitled]

1 points·by pfdomizer·6 gün önce·0 comments

[untitled]

1 points·by pfdomizer·11 gün önce·0 comments

[untitled]

1 points·by pfdomizer·15 gün önce·0 comments

[untitled]

1 points·by pfdomizer·2 ay önce·0 comments

[untitled]

1 points·by pfdomizer·2 ay önce·0 comments

[untitled]

1 points·by pfdomizer·2 ay önce·0 comments

[untitled]

1 points·by pfdomizer·2 ay önce·0 comments

[untitled]

1 points·by pfdomizer·3 ay önce·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 ay önce·2 comments

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

github.com
2 points·by pfdomizer·3 ay önce·0 comments

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

github.com
3 points·by pfdomizer·3 ay önce·0 comments

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

github.com
7 points·by pfdomizer·3 ay önce·4 comments

comments

pfdomizer
·3 ay önce·discuss
No but it should work i just tested it on a 5090
pfdomizer
·3 ay önce·discuss
Thanks, happy to hear that!
pfdomizer
·3 ay önce·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).