index.html 2.79 KB
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>Display Webcam Stream</title>
 
<style>
#container {
	margin: 0px auto;
	width: 640px;
	height: 480px;
	border: 10px #333 solid;
}
#videoElement {
	width: 640px;
	height: 480px;
	background-color: #666;
}
</style>
</head>
 
<body>
<div id="container">
	<video autoplay="true" id="videoElement"> <!-- style="visibility: hidden"-->
	
	</video>
	<canvas id='canvasOutput'>
	
	</canvas>
</div>
<script type='text/javascript' src={{url_for('static', filename='js/opencv.js')}}>
<script type='text/javascript'>
var video = document.querySelector("#videoElement");
if (navigator.mediaDevices.getUserMedia){
    navigator.mediaDevices.getUserMedia({ video: true })
	.then(function (stream) {
            video.srcObject = stream;
	}).catch(function (err0r) {
            console.log("Something went wrong!");
        });
}
</script>
<script>
function openCvReady() {
    cv['onRuntimeInitialized']=()=>{
        // do all your work here
        let video = document.getElementById('videoElement');
        let src = new cv.Mat(video.height, video.width, cv.CV_8UC4);
        let dst = new cv.Mat(video.height, video.width, cv.CV_8UC4);
        let gray = new cv.Mat();
        let cap = new cv.RectVector();
        let classifier = new cv.CascadeClassifier();
        classifier.load({{url_for('static', filename='js/haarcascade_frontalface_default.xml')}})
        const FPS = 30;
        function processVideo() {
            try {
                if (!streaming) {
                    // clean and stop.
                    src.delete();
                    dst.delete();
                    gray.delete();
                    faces.delete();
                    classifier.delete();
                    return;
                }
                let begin = Date.now();
                // start processing.
                cap.read(src);
                src.copyTo(dst);
                cv.cvtColor(dst, gray, cv.COLOR_RGBA2GRAY, 0);
                // detect faces.
                classifier.detectMultiScale(gray, faces, 1.1, 3, 0);
                // draw faces.
                for (let i = 0; i < faces.size(); ++i) {
                    let face = faces.get(i);
                    let point1 = new cv.Point(face.x, face.y);
                    let point2 = new cv.Point(face.x + face.width, face.y + face.height);
                    cv.rectangle(dst, point1, point2, [255, 0, 0, 255]);
                }
                cv.imshow('canvasOutput', dst);
                // schedule the next one.
                let delay = 1000/FPS - (Date.now() - begin);
                setTimeout(processVideo, delay);
            } catch (err) {
                utils.printError(err);
        }
        // schedule the first one.
        setTimeout(processVideo, 0);
    };
  };
}
</script>
</body>
</html>