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HTML

<!doctype html>
<html>
<head>
<meta charset="utf-8">
<title>Metacar: Discrete Actions in traffic.</title>
<link rel="icon" href="/public/img/icon.png">
<link rel="stylesheet" href="/public/css/general.css">
<link href="https://fonts.googleapis.com/css?family=Tajawal" rel="stylesheet">
</head>
<body>
<header>
<div class="header_container">
<h1><a href="/">Metacar</a></h1>
<a href="https://github.com/thibo73800/metacar"><img src="/public/img/github-logo.png" /></a>
</div>
</header>
<div class="canvas_container">
<!--
You just have to add a div with an ID as bellow and include the js to start
using metacar. -->
<div class="canvas" id="canvas"></div>
</div>
<div class="body_container">
<h3 id="trainingProgress"></h3>
<h3 style="float: left">Current state (Lidar points)</h3><br><br><br>
<div id="realtime_viewer" style="float: left"></div>
<p>
<b>Policy Gradient</b> algorithm based on Monte Carlo exploration. <br>
You can use the <b>arrow keys</b> to control the car by yourself.<br><br>
Click on <b>"Load trained agent"</b> to load the model. Then click on <b>"Play"</b>
to see the result. <br>
The left window gives you an overview of what the autonomous vehicle (in red) sees.<br><br>
The algorithm is implemented <a href="https://github.com/thibo73800/metacar/blob/master/demo/webapp/public/js/policy_agent.js">here</a> using <a href="https://github.com/thibo73800/metacar">the metacar environment.</a>
</p>
</div>
<script src="https://cdnjs.cloudflare.com/ajax/libs/pixi.js/4.7.1/pixi.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.11.6"> </script>
<script src="/dist/metacar.min.js"></script>
<script type="text/javascript" src="/public/js/utils.js"></script>
<script type="text/javascript" src="/public/js/viewer.js"></script>
<script type="text/javascript" src="/public/js/policy_monte_carlo/policy_agent.js"></script>
<script type="text/javascript" src="/public/js/policy_monte_carlo/index.js"></script>
</body>
</html>