Show HN: Local-first fast CPU image to text for screenshots, PDFs, webpages(github.com)
github.com
Show HN: Local-first fast CPU image to text for screenshots, PDFs, webpages
https://github.com/kouhxp/textsnap
18 comments
What's the performance like compared to tesseract?
I don't see tesseract mentioned anywhere in the readme, which is surprising considering that's the number one tool most go to for Image > text OCR.
No rigorous eval, and I love Tesseract. Here's the example that motivated me to build textsnap (which is in the github's README), parsed with Tesseract:
https://imgur.com/a/i2eQra8
https://imgur.com/a/i2eQra8
Very noticable difference and the exact issue I run repeatedly with tesseract! Definitely going to try dropping textsnap into my scripts now. Thanks!!
Curious how it does on multi-page scanned PDFs vs. single screenshots? The ORT vision/decoder split is the part that usually makes or breaks CPU VLM OCR...
I had to extract the image from a PDF for it to work. Then run it on each page image extracted.
Thanks
- how well do you think this ll work with code? i mean take code screenshots and convert it into actual code for vscode
Just ran
textsnap "https://i.ytimg.com/vi/LBNDfxjEYlA/maxresdefault.jpg"
and got this $('.count').each(function () {
$('this').prop('Counter', 0).animate({
Counter: $('this').text()
}, {
duration: 4000,
easing: 'swing',
step: 'function (now) {
$('this").text(Math.ceil(now));
}
});
});This is awesome! Been needing something like this for some research paper diagrams I've been indexing.
Very cool, I'm building my own local-first product as well
thank you! what is it about?