SWPBL_HUSK/index.html at master · FEKimseongeun/SWPBL_HUSK · GitHub

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<!DOCTYPE html>
<!--[if lt IE 7]>      <html class="no-js lt-ie9 lt-ie8 lt-ie7"> <![endif]-->
<!--[if IE 7]>         <html class="no-js lt-ie9 lt-ie8"> <![endif]-->
<!--[if IE 8]>         <html class="no-js lt-ie9"> <![endif]-->
<!--[if gt IE 8]>      <html class="no-js"> <!--<![endif]-->
<html>
    <head>
        <meta charset="utf-8">
        <meta http-equiv="X-UA-Compatible" content="IE=edge">
        <title></title>
        <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css"
        integrity="sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh" crossorigin="anonymous">
        <link rel="preconnect" href="https://fonts.gstatic.com">
<link href="https://fonts.googleapis.com/css2?family=Open+Sans:wght@800&display=swap" rel="stylesheet">
<link rel="preconnect" href="https://fonts.gstatic.com">
<link href="https://fonts.googleapis.com/css2?family=Montserrat:wght@300;400&display=swap" rel="stylesheet">
        <link rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/earlyaccess/notosanskr.css">
        <title>AI MASK CHECKING PROGRAM</title>
        <link rel="stylesheet" href="index.css">

    </head>
    <body>
        <div class="main-background"></div>
        <div class="main-logo">
            <img src="images/HUSK_SMU.png" style="width:90px;
            height: 70px;">
        </div>
        <nav>
            <ul>
                <li><a href="intro.html" >HUSK</a></li>
                <li><a href="about.html">ABOUT</a></li>
            </ul>
        </nav>

        <div class="main-content"></div>
            <div class="main_text">SHOW YOUR FACE</div>
            <button type="button" onclick="init()">Start</button>
            <div class="label-container" id="label-container"></div>

        </div>
        <div class="square"></div>
        <div class="webcam-container" id="webcam-container"></div>
        <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@1.3.1/dist/tf.min.js"></script>
        <script src="https://cdn.jsdelivr.net/npm/@teachablemachine/image@0.8/dist/teachablemachine-image.min.js"></script>
        <script type="text/javascript">
            // More API functions here:
            // https://github.com/googlecreativelab/teachablemachine-community/tree/master/libraries/image

            // the link to your model provided by Teachable Machine export panel
            const URL = "https://teachablemachine.withgoogle.com/models/WCUO2kwJa/";

            let model, webcam, labelContainer, maxPredictions;
            const data={
                "마스크안씀":{
                    "name":"마스크 안씀",
                    "message" : "마스크를 써주세요."
                },
                "마스크씀":{
                    "name":"마스크 씀",
                    "message" : "안전합니다."
                },
                "코턱스크":{
                    "name":"코스크&턱스크",
                    "message":"마스크를 제대로 써주세요."
                }
            }
            // Load the image model and setup the webcam
            async function init() {
                const modelURL = URL + "model.json";
                const metadataURL = URL + "metadata.json";

                model = await tmImage.load(modelURL, metadataURL);
                maxPredictions = model.getTotalClasses();

                // Convenience function to setup a webcam
                const flip = true; // whether to flip the webcam
                webcam = new tmImage.Webcam(700, 700, flip); // width, height, flip
                await webcam.setup(); // request access to the webcam
                await webcam.play();
                window.requestAnimationFrame(loop);

                // append elements to the DOM
                document.getElementById("webcam-container").appendChild(webcam.canvas);
                labelContainer = document.getElementById("label-container");
                for (let i = 0; i < maxPredictions; i++) { // and class labels
                    labelContainer.appendChild(document.createElement("div"));
                }
            }

            async function loop() {
                webcam.update(); // update the webcam frame
                await predict();
                window.requestAnimationFrame(loop);
            }


            var status="마스크 안씀"
            var audio
            // run the webcam image through the image model
            async function predict() {
                const prediction = await model.predict(webcam.canvas);
                // predict can take in an image, video or canvas html element
                if(prediction[0].probability.toFixed(2) == '1.00'){

                    if(status=="마스크 씀"||status=="코턱스크"){
                        audio=new Audio('Audio1.mp3');
                        audio.play();
                    }
                    status="마스크 안씀"
                }else if(prediction[1].probability.toFixed(2) == '1.00'){

                    if(status=="마스크 안씀"||status=="코턱스크"){
                    audio=new Audio('Audio2.m4a');
                    audio.play();}
                    status="마스크 씀"
                }else if(prediction[2].probability.toFixed(2) == '1.00'){

                    if(status=="마스크 씀"||status=="마스크 안씀"){
                    var audio=new Audio('Audio3.m4a');
                    audio.play();}
                    status="코턱스크"
                }

                for (let i = 0; i < maxPredictions; i++) {
                    if(prediction[i].probability.toFixed(2) == '1.00'){
                            const item=data[prediction[i].className]
                            labelContainer.innerHTML=`${item.message}`
                    }


                    // const classPrediction =
                    //     prediction[i].className + ": " + prediction[i].probability.toFixed(2);
                    // labelContainer.childNodes[i].innerHTML = classPrediction;
                }
            }

        </script>


    </body>
</html>