troika VS jeelizFaceFilter

troika (specifically troika-three-text)

Text is relatively hard to render with WebGL and browsers have a limit, of usually 16 framebuffers that you can use for WebGL contexts. Our charts are written for a WebGL target so we don't want to use up that precious resource for text rendering. In our specific use case we usually have a large degree of control over the browser so we can configure it, but if the target is web we don't have that control. Grabbing a WebGL context also takes a significant period of time, usually a hundred milliseconds or more on my computer, and not displaying data in that time isn't a great user experience.

There's a great WebGL library for doing that on the web using any .ttf, .otf, or .woff font - https://github.com/protectwise/troika/tree/master/packages/t...

Ikr! That's what I was thinking when I came across Jeeliz. Now I have worked with tensorflow.js based libraries in the past but they're usually quite CPU intensive for a live video use case. Jeeliz looked promising as it's designed for this use case. So I thought why not try it out by adding some 3d AR filters to our video calls. Well! that is what we're going to do.

I created a demo face filter web app using jeeliz. It has great features however, I found that the tracking performance wasn't perfect. Media pipe seems to require building out custom features manually to achieve the face filter app I need. I'm wondering if building a more custom app with mediapipe would be worth the extra effort over Jeeliz.