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object_detection.html
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<html>
<head>
<title>object detection</title>
<meta charset="utf-8">
<script src="script/tfjs.1.3.1.js"> </script>
<script src="script/coco-ssd.js"> </script>
</head>
<body>
<h1>目标识别</h1>
<div id="demo" style="position: relative;min-height: 50px">
<!--视频-->
<div id="wrap" style="width:640px;height:480px;position:relative;display: none">
<video id="video" width="640" height="480" autoplay></video>
<img src="https://ossweb-img.qq.com/images/game/brand/game-logo.png" id="logo" alt="" style="display:none">
</div>
<!--图片-->
<div id="upload" style="display:none;position: absolute;z-index:99">
<input id="img_input" type="file" accept="image/*" onchange="uploadPic(event)" />
<label for="img_input"></label>
</div>
<!--图片预览-->
<div id="preview"></div>
<!--canvas-->
<canvas id="draw" style="position: absolute;left:0;top:0;z-index:9;width:0px;height:0px;z-index:9;"></canvas>
</div>
<!--状态-->
<p id="status"></p>
<p>官方地址：<a href="https://github.com/tensorflow/tfjs-models/tree/master/coco-ssd">https://github.com/tensorflow/tfjs-models/tree/master/coco-ssd</a></p>
<p>前端智能DEMO合集：<a href="http://allan5.com/FE-AI/">http://allan5.com/FE-AI/</a></p>
<script>
let net = null;
let c = document.getElementById('draw');
let ctx = c.getContext('2d');
let canvasVideoSize = {'width':640,'height':480}
const status = document.getElementById('status')
let video = document.getElementById('video');
window.addEventListener("DOMContentLoaded", function() {
video = document.getElementById('video');
let mediaConfig = {
'audio': false,
'video': {
facingMode: 'user',
width: 640,
height: 480,
}
};
//加载模型
loadModel()
if(navigator.mediaDevices && navigator.mediaDevices.getUserMedia) {
navigator.mediaDevices.getUserMedia(mediaConfig).then(function(stream) {
document.getElementById('wrap').style.display = 'block'
setInterval(function(){
//预测
predict(video)
},500)
video.srcObject = stream;
video.play();
}).catch((e)=>{
//不支持摄像头显示图片逻辑
document.getElementById('upload').style.display = 'block'
});
}
}, false);
//图片
function uploadPic(e){
let file = e.target.files[0];
if (!file.type.match('image.*')) return;
let reader = new FileReader();
let PREVIEW = document.getElementById('preview');
reader.readAsDataURL(file);
status.innerText = '正在预测..'
reader.onload = function(e){
PREVIEW.innerHTML = '';
PREVIEW.innerHTML = `<img id="pic" src='${e.target.result}' >`;
let image = new Image();
image.src= e.target.result;
image.onload = function () {
//在image加载后重设canvas大小对象
canvasVideoSize = {'width':image.width,'height':image.height}
//预测
predict(image)
}
}
}
//加载模型
async function loadModel(){
status.innerText = '正在加载模型...'
net = await cocoSsd.load({
modelUrl:'model/object_detection/model.json'
});
status.innerText = '模型加载完成'
}
//预测主函数
async function predict(o){
if(!net) return
const predict = await net.detect(o);
console.log(predict)
status.innerText = ''
ctx.clearRect(0,0,0,0);
//初始化canvas width height
c.width = canvasVideoSize.width;
c.height = canvasVideoSize.height;
c.style.height = canvasVideoSize.height;
c.style.width = canvasVideoSize.width;
predict.forEach(e => {
draw(e)
});
}
function draw(e) {
let BOX = e.bbox;
ctx.beginPath()
//设置绘制属性
ctx.strokeStyle="aqua";
ctx.fillStyle = "aqua";
ctx.font = "bold 20px arial";
//绘制边框
ctx.strokeRect(BOX[0],BOX[1],BOX[2],BOX[3]);
ctx.fillText(e.class+' '+e.score,BOX[0]+10,BOX[1]+20);
}
</script>
</body>
</html>