Andrés Cuervo cwervo

Web Technologies Only

AR.js
clmtrackr
OpenCV.js
TensorFlow.js, you can build your own computer vision technology.
ML5.js — similar goal to TensorFlow.js, build your own ML to recognize patterns, including computer vision!
Tracking.js — a component based CV tracking system written in JS, you can write functions that define what features you're looking for

	let scene,
	camera,
	renderer,
	cube;

	function init () {
	scene = new THREE.Scene();
	camera = new THREE.PerspectiveCamera( 75, window.innerWidth/window.innerHeight, 0.1, 1000 );
	renderer = new THREE.WebGLRenderer();
	renderer.setSize( window.innerWidth, window.innerHeight );

	AFRAME.registerComponent('10print', {
	schema : {
	x : { default : 0 },
	y : { default : 0 },
	width : { default : 30 },
	height : { default : 5 },
	spacing : { default : 1 },

	color : { default : 'white', type : 'color'},
	side: { default : 'double' }

	-- Written with LÖVE2D 0.10.2 (Super Toast)

	local height = love.graphics.getHeight( )
	local width = love.graphics.getWidth( )

	local t = 0

	love.graphics.setColor(255, 255, 255)
	love.graphics.setLineWidth(1)

	AFRAME.registerComponent('outline-geometry', {
	schema : {
	margin : { default : 1.025 },
	color: { default : 'red' },
	},
	init : function () {
	var p = this.el;
	var p_prime = p.cloneNode(true);
	p_prime.removeAttribute('outline-geometry')
	p_prime.setAttribute('material', 'color', this.data.color)

	// Note: requires https://rawgit.com/jeromeetienne/ar.js/master/aframe/build/aframe-ar.js
	// or A-Frame.js + AR.js + THREEx + some other bindings,
	// basically, just use Jerome Etienne's A-Frame AR lib ¯\_(ツ)_/¯


	// This is all based off Jerome Etienne's work, and he originally linked to
	// these two sources, so I'll do the same here:
	// http://http.developer.nvidia.com/CgTutorial/cg_tutorial_chapter07.html
	// https://www.clicktorelease.com/code/streetViewReflectionMapping/#51.50700703827454,-0.12791916931155356