gg VS pigo

The author explicitly says:

> You don't need to download any dependencies such as plantUML or Graphviz, which is what most of the tools out there require and what was also my motivation to start this project. go-uml is using a 2D graphics engine written 100% in Go https://github.com/fogleman/gg

So no, this is not a solution for these requirements.

I really like the [fogleman/gg](https://github.com/fogleman/gg) package for image manipulation, it is pure Go and has many functions to draw and manipulate images.

you can try something like: https://github.com/fogleman/gg to create such images from templates

I've always used the GG library for my image processing needs, and I've heard of libvips somewhere before (likely from the Node.js world) but didn't know it had a Go port/wrapper. :) I'll definitely check that out as well

what library are you using? I recommend this one.

Mainly, the standard library and my favorite gg.

Have you been hit by https://github.com/fogleman/gg/issues/85 when writing your book?

It does relatively little, and that's the point! It works really well when you combine it with other packages; I find it plays very well with fogleman/gg, but your objectives may differ. The dev is very responsive and helpful (even if I don't understand their tweets).

That piece of code makes all the magic. With the help of Fogleman library manipulating images in Go is a breeze. Let's check what this is doing:

The base image package doesn't have text rendering functions. It would probably be easier to use a higher level library like https://github.com/fogleman/gg

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.