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index.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta http-equiv="X-UA-Compatible" content="ie=edge">
<title>JS图像识别</title>
</head>
<body>
<img src="http://p.pstatp.com/avatar/100x100/1dd5000048d6334c26b4.png" crossorigin="anonymous" id="some_image">
<input type="button" id="test" value="识别车的logo" >
<script src="./convnet-min.js"></script>
<script src="./car.js"></script>
<script src="https://cdn.bootcss.com/jquery/3.3.1/jquery.min.js"></script>
<script>
let layer_defs = [];
let imageList = [];
const net = new convnetjs.Net();
//构建层
//图片的宽度和高度，要与待识别的图意志哦，本例是100X100
layer_defs.push({type:'input', out_sx:100, out_sy:100, out_depth:1});
layer_defs.push({type:'conv', sx:5, filters:16, stride:1, pad:2, activation:'relu'});
layer_defs.push({type:'pool', sx:2, stride:2});
layer_defs.push({type:'conv', sx:5, filters:20, stride:1, pad:2, activation:'relu'});
layer_defs.push({type:'pool', sx:2, stride:2});
layer_defs.push({type:'conv', sx:5, filters:20, stride:1, pad:2, activation:'relu'});
layer_defs.push({type:'pool', sx:2, stride:2});
layer_defs.push({type:'softmax', num_classes:10});
net.makeLayers(layer_defs);
//训练层，图像识别的特定的参数
const trainer = new convnetjs.SGDTrainer(net, {method:'adadelta', batch_size:5, l2_decay:0.001});
// trainer.train(x, 0);
//把img图片放到imageList数组中
for(var i=0; i<carList.length;i++){
imageList.push(loadImg(i));
}
//训练模型，返回一个函数，
function loadImg(i){
return function(){
return new Promise(function(resolve,reject){
let image = new Image();
image.crossOrigin = "Anonymous";//跨域
image.src = carList[i].url;
//加载成功，进行转换，并训练
image.onload = function(){
let vol = convnetjs.img_to_vol(image);
trainer.train(vol,i);
resolve();
};
image.onerror = reject;
})
}
};
//给按钮绑定事件
$("#test").click(function(){
const carNameList = ["奥迪","阿尔法-罗密欧","阿斯顿 马丁","AC Schnitzer","ALPINA","安凯客车"];
//训练模型--遍历imagelist中的promise，对象都是函数，执行后返回Promise训练后的结果
Promise.all(imageList.map(imageContainer=>imageContainer())).then(function(){
//拿到页面上的图片进行识别
const test = convnetjs.img_to_vol(document.getElementById("some_image"));
//把结果放到result数组中，一群0-1的小数放在里面
let result = Array.from(net.forward(test).w);
//找到数组中值最大的那个，他的索引就是对应的车牌的索引哦
let max = Math.max.apply(Math,result);
console.log("这个汽车logo可能是：" + carNameList[result.indexOf(max)]);
});
});
</script>
</body>
</html>