index.html
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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>Web Attendance System</title>
<style>
#container {
margin: 15px auto;
border: 10px #333 solid;
}
#videoInput {
background-color: #666;
}
#canvasOutput {
background-color: #666;
}
#messagebox {
height: 300px;
overflow-y: auto;
}
.w3-center {
text-align:center!important
}
.w3-container {
padding:0.01em 16px;
}
.w3-tag{background-color:#000;color:#fff;display:inline-block;padding-left:8px;padding-right:8px;text-align:center}
.message {
padding: 20px;
font-weight: bold;
color: white;
}
.attend {
background-color: #4CAF50;
}
.already {
background-color: #2196F3;
}
.late {
background-color: #ff9800;
}
.fail {
background-color: #f44336;
}
</style>
<script type='text/javascript' src="{{url_for('static', filename='js/opencv.js')}}"></script>
<script type='text/javascript' src="{{url_for('static', filename='js/utils.js')}}"></script>
<script type='text/javascript' src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
<script type='text/javascript'>
function init()
{
let video = document.getElementById('videoInput');
let container = document.getElementById('container');
let canvasOutput = document.getElementById("canvasOutput");
if (navigator.mediaDevices.getUserMedia){
navigator.mediaDevices.getUserMedia({ video: true })
.then(function (stream) {
video.srcObject = stream;
video.addEventListener('canplay', () => {
var screenWidth = $(document).width();
var screenHeight = $(document).height();
var headerHeight = $('#header').height();
var messageboxHeight = $('#messagebox').height();
var ratio = 1.0;
video.width = video.videoWidth;
video.height = video.videoHeight;
if (video.width > screenWidth || video.height + headerHeight + messageboxHeight > screenHeight){
ratio = Math.min(screenWidth / video.width * 1.0, screenHeight / ((video.height + headerHeight + messageboxHeight) * 1.0));
}
container.style.width = Math.round(video.width * ratio) + 'px';
container.style.height = Math.round(video.height * ratio) + 'px';
canvasOutput.width = Math.round(video.width * ratio);
canvasOutput.height = Math.round(video.height * ratio);
load_cascade();
});
}).catch(function (err0r) {
console.log("Something went wrong!");
streaming = false;
});
}
}
function load_cascade()
{
let faceCascadeFile = 'haarcascade_frontalface_default.xml'
let faceCascadeURL = 'static/js/haarcascade_frontalface_default.xml'
let utils = new Utils('errorMessage');
utils.createFileFromUrl(faceCascadeFile, faceCascadeURL, () => {
main()
});
}
function main()
{
let video = document.getElementById("videoInput");
let canvasOutput = document.getElementById("canvasOutput");
let canvasContext = canvasOutput.getContext('2d');
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 dsize = new cv.Size(canvasOutput.width, canvasOutput.height);
let cap = new cv.VideoCapture(video);
let faces = new cv.RectVector();
let classifier = new cv.CascadeClassifier();
class Tracker{
constructor(){
this.arr = new Array();
}
register = function(x, y, width, height) {
var x_center = (x + width) / 2;
var y_center = (y + height) / 2;
var now = Date.now()
this.arr = this.arr.filter(ent => now - ent.time < 300);
for (const prop in this.arr){
var prop_x_center = (this.arr[prop].x + this.arr[prop].width) / 2;
var prop_y_center = (this.arr[prop].y + this.arr[prop].height) / 2;
if (Math.abs(x_center - prop_x_center) < 10 && Math.abs(y_center - prop_y_center) < 10){
this.arr[prop].x = x;
this.arr[prop].y = y;
this.arr[prop].width = width;
this.arr[prop].height = height;
this.arr[prop].time = now;
return false;
}
}
var ent = {x: x, y: y, width: width, height: height, time: now}
this.arr.push(ent)
return true;
}
};
var tracker = new Tracker();
var streaming = true;
classifier.load('haarcascade_frontalface_default.xml');
const FPS = 30;
function processVideo() {
try {
if (!streaming) {
// clean and stop.
src.delete();
dst.delete();
faces.delete();
classifier.delete();
return;
}
let begin = Date.now();
// start processing.
cap.read(src);
cv.flip(src, src, 1);
src.copyTo(dst);
// detect faces.
let msize = new cv.Size(video.width / 4, video.height / 4);
classifier.detectMultiScale(dst, faces, 1.1, 3, 0, msize);
// 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], 8);
let cropped = new cv.Mat();
let margin_x = 0;
let margin_y = 0;
if (face.width > face.height)
{
margin_y = (face.width - face.height) / 2;
}
else
{
margin_x = (face.height - face.width) / 2;
}
Math.max(face.width, face.height)
Math.min(face.width, face.height)
let rect = new cv.Rect(Math.max(face.x-margin_x, 0), Math.max(face.y-margin_y, 0), Math.min(face.width+margin_x, src.cols), Math.min(face.height+margin_y, src.rows));
cropped = src.roi(rect);
let tempCanvas = document.createElement("canvas");
cv.imshow(tempCanvas,cropped);
if (tracker.register(face.x, face.y, face.width, face.height)){
let b64encoded = tempCanvas.toDataURL("image/jpeg", 1.0);
b64encoded = b64encoded.replace('data:image/jpeg;base64,', '');
$.ajax({
type: "POST",
url: "/verify",
dataType: "json",
data: {'image':b64encoded},
success: function(data){
if (data.status == "attend"){
var newHead = "<div class='message attend'>";
var newTail = "</div>";
var newContent = '[' + data.student_id + '/' + data.student_name + ']' + "출석되었습니다.";
$('#messagebox').prepend(newHead + newContent + newTail).stop().animate({ scrollTop: 0 }, 1000);
}
else if (data.status == "already"){
var newHead = "<div class='message already'>";
var newTail = "</div>";
var newContent = '[' + data.student_id + '/' + data.student_name + ']' + "이미 출석되었습니다.";
$('#messagebox').prepend(newHead + newContent + newTail).stop().animate({ scrollTop: 0 }, 1000);
}
else if (data.status == "fail"){
var newHead = "<div class='message fail'>";
var newTail = "</div>";
var newContent = "인식 실패";
$('#messagebox').prepend(newHead + newContent + newTail).stop().animate({ scrollTop: 0 }, 1000);
}
}
});
}
}
// to do resize preview
cv.resize(dst, dst, dsize, 0, 0, cv.INTER_AREA);
cv.imshow('canvasOutput', dst);
// schedule the next one.
let delay = 1000/FPS - (Date.now() - begin);
setTimeout(processVideo, delay);
} catch (err) {
console.log(err);
}
}
setTimeout(processVideo, 0);
}
</script>
</head>
<body onload="cv['onRuntimeInitialized']=()=>{ init(); };">
<div id="header">
<!-- Header -->
<header class="w3-container w3-center w3-padding-32">
<h1><b>얼굴 인식 출석 시스템</b></h1>
<p>Made by <span class="w3-tag">정해갑</span></p>
</header>
</div>
<div id="container">
<video autoplay="true" id="videoInput" style="display: none; object-fit: cover;"></video>
<canvas id="canvasOutput"></canvas>
</div>
<div id="messagebox">
</div>
</body>
</html>