go-playground VS pigo

If someone interested to play with WASM capabilities, I've been working on custom playground that supports WebAssembly - https://goplay.tools.

If you're interested - take a look at our patched wasm_exec.js

https://goplay.tools/ with syntax highlighting and autocomplete.

If you have any ideas or suggestions - I recommend to create an issue on GitHub repo because it's complicated to track ideas on Reddit.

Thanks for the feedback, much appreciated. Apologies if my previous post looks like trying to push you into a particular direction; this wasn't my intention. Stay with your roadmap, goplay.tools is already super useful. If I need something extra I should really consider trying to contribute that – although I must admit I don't have much time either. But I'll keep it in mind.

The source code is on GitHub. https://github.com/x1unix/go-playground

Hello, I'm looking for contributors for my FOSS project - https://github.com/x1unix/go-playground.

Then I saw this library https://github.com/esimov/pigo but as far as I know, this library only detects if an image has face in it, but cannot really classify the face. CMIIW.

The task consists of porting a small portion of the PIGO face detection GO library (https://github.com/esimov/pigo/commit/29b25278c3e3436416440404b95cd3c18e145b3b) especially the face landmarks extraction section to WebAssembly/JavaScript or plain C depending of the programming language your are proficient with.

I tried https://github.com/ageitgey/face_recognition and https://github.com/esimov/pigo so far and they both work OK, but from there, you would need to add EXIF tags into your pictures, so they can be picked up by img-DB.

I'll use this post / opportunity to ask the HN community

(I know this is a technically complicated, and potentially sensitive subject)

I've been approached by a few people who are trying to make prescription glasses less expensive. It's a mix of (licensed) opticians, people interested in offering community health services, etc.

What is the current state of the art for PD measurement based on face / pupil tracking / detection using laptop webcams or mobile (front) cameras?

I imagine (obviously?) that there must be scholar research on the acceptable error margins for a PD measurement (depending on the type of vision condition, i.e. farsightedness, etc.)?

Would using something like Handsfree or https://github.com/esimov/pigo (which has pupil detection) be a good start, or would these be an ~order of magnitude off in terms of the necessary margins?

Thanks a lot.