Question


async function train() {
    
    var labels = [0] // 0 = L 
    var tensorLabels = tf.oneHot(tf.tensor1d(labels, 'int32'), 3);

    var buffer = fs.readFileSync("./train/L/L.png")
    var tensorFeature = tf.node.decodeImage(buffer)

    var tensorFeatures = tf.stack([tensorFeature])
    
    const model = tf.sequential();
    model.add(tf.layers.conv2d({
      inputShape: [1, 132, 180, 3], // numberOfChannels = 3 for colorful images and one otherwise
      filters: 32,
      kernelSize: 3,
      activation: 'relu',
    }));
    model.add(tf.layers.flatten()),
    model.add(tf.layers.dense({units: 3, activation: 'softmax'}));

    model.compile({loss: 'meanSquaredError', optimizer: 'sgd'})
    model.fit(tensorFeatures, tensorLabels)
}

我正在尝试用字母“L”（132x180）训练张量流模型，我对 tf.我希望我能在使用图像的训练方面得到一些帮助。

Answer 1

通过改变 inputShape 修复：

 inputShape: [180, 132, 3],

错误：输入 0 与层 conv2d_Conv2D1 不兼容：预期 ndim=4，发现 ndim=5

1 个答案: