One热中出错：深度必须为&gt；=2，但它是1

2022-08-23 00:00:00 p5.js javascript ml5

所以我在js中使用ml5在一个简单的NeuralNetwork上工作，它将使用P5 js库通过图像进行训练，将图像放入一个数组中，然后通过ml5训练它们，但我遇到了一个主要问题，我花了几个小时寻找这个错误的答案，但在任何地方都找不到它。使用库p5、p5、sketch、ml5

JS档案

let RustImage = [];

function preload() {
    for (let i = 0; i < 5; i++) {
        RustImage[i] = loadImage(`RustPhotos/2020-12-08 (${i+7}).png`);

    }
}
let NodeClassifier;

function setup() {
    createCanvas(440, 440);
    // background(0);
    // image(RustImage[0], 0, 0, width, height);

    let options = {
        inputs: [128, 128, 4],
        task: "imageClassification",
        debug: true,
    };

    NodeClassifier = ml5.neuralNetwork(options);

    for (let i = 0; i < RustImage.length; i++) {
        NodeClassifier.addData({ image: RustImage[i] }, { label: "SulfurNode" });
    }
    NodeClassifier.normalizeData();
    NodeClassifier.train({ epochs: 5 }, finishedTraining);

}

function finishedTraining() {
    console.log("Finished Training!");
}

HTML

<!DOCTYPE html>
<html lang="en">

<head>
    <title>Getting Started with ml5.js</title>
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <script src="https://cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js"></script>
    <script src="p5.js"></script>
    <script src="p5.sound.js"></script>
    <script src="sketch.js"></script>
    <script src="https://unpkg.com/ml5@latest/dist/ml5.min.js"></script>
</head>

<body>
    <script src="improring.js"></script>
</body>

</html>

如果有人可以帮助您，并且他们知道此错误的答案或简单的修复方法，请发表意见。

完全错误

Uncaught Error: Error in oneHot: depth must be >=2, but it is 1
node_modules/@tensorflow/tfjs-core/dist/tf-core.esm.js:17
oneHot_ @ c:UsersmattdDesktopXamphtdocsJs Importing Lib
ode_modules@tensorflow	fjs-coredist	f-core.esm.js:17:357944
oneHot @ c:UsersmattdDesktopXamphtdocsJs Importing Lib
ode_modules@tensorflow	fjs-coredist	f-core.esm.js:17:71801
◀ load ▶
<anonymous> @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:65707:28
◀ Promise.then ▶
_main.default.loadImage @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:65671:30
<anonymous> @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:48748:67
preload @ C:UsersmattdDesktopXamphtdocsJs Importing Libimproring.js:5:24
_start @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:48706:19
p5 @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:49057:22
_globalInit @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:48197:17
◀ Promise.then ▶
51.../core/main @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:48222:71
o @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:34:19
<anonymous> @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:38:22
38../color/color_conversion @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:41211:11
o @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:34:19
r @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:51:9
<anonymous> @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:55:7
<anonymous> @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:18:12
<anonymous> @ cdn.jsdelivr.net/npm/p5@1.1.9/lib/p5.js:20:3

解决方案

不确定它们是否相同，但在我的情况下，某些训练数据集只有1个输出标签的单一结果，因此模型不会训练。

它似乎与"；深度必须为>；=2有某种匹配，但它是1条消息(&q；)。

为确保我只需在数据集中手动添加另一个结果并重新启动

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