clmtrackr
Version:
Javascript library for precise tracking of facial features via Constrained Local Models
66 lines (61 loc) • 1.77 kB
HTML
<html lang="en">
<head>
<title>Face tracker</title>
<meta charset="utf-8">
<style>
#container {
position : relative;
}
#canvas {
position : absolute;
left : 0;
top : 0;
}
</style>
</head>
<body>
<script src="./js/libs/utils.js"></script>
<script src="../build/clmtrackr.js"></script>
<div id="content">
<h2>Example</h2>
<div id="container">
<video id="video" width="368" height="288" autoplay loop playsinline>
<source src="./media/franck.mp4" type="video/mp4"/>
<source src="./media/franck.webm" type="video/webm"/>
</video>
<canvas id="canvas" width="368" height="288"></canvas>
</div>
<p>Printing coordinates of the first 10 points in facial features:</p>
<p id="positions"></p>
<script>
var videoInput = document.getElementById('video');
var ctracker = new clm.tracker();
ctracker.init();
ctracker.start(videoInput);
function positionLoop() {
requestAnimFrame(positionLoop);
var positions = ctracker.getCurrentPosition();
// do something with the positions ...
// print the positions
var positionString = "";
if (positions) {
for (var p = 0;p < 10;p++) {
positionString += "featurepoint "+p+" : ["+positions[p][0].toFixed(2)+","+positions[p][1].toFixed(2)+"]<br/>";
}
document.getElementById('positions').innerHTML = positionString;
}
}
positionLoop();
var canvasInput = document.getElementById('canvas');
var cc = canvasInput.getContext('2d');
function drawLoop() {
requestAnimFrame(drawLoop);
cc.clearRect(0, 0, canvasInput.width, canvasInput.height);
ctracker.draw(canvasInput);
}
drawLoop();
</script>
</div>
</body>
</html>