Xamarin张量流

Question

我想在Android设备上开发TensorFlow，到目前为止我用python和导出模型训练到Protobuf .pb文件

在python上测试的.pb文件，它的返回没有错误

    ......
graph = load_graph("./frozen_model.pb")
    for op in graph.get_operations():
        print(op.name)

    with tf.Session(graph=graph) as sess:
        tf_predik = graph.get_tensor_by_name("prefix/tf_pred:0")
        tf_data = graph.get_tensor_by_name("prefix/tf_data:0")
        img = np.invert(Image.open("7.png").convert('L')).ravel(); image = array(img).reshape(1, 28,28,1);
        fd = {tf_data: image};
        test_pred = sess.run(tf_predik, feed_dict=fd); temp = np.argmax(test_pred, axis=1); print(temp)

我在Xamarin Android上尝试：

using Org.Tensorflow.Contrib.Android;
.....

var assets = Android.App.Application.Context.Assets;
                var inferenceInterface = new TensorFlowInferenceInterface(assets, "frozen_model.pb");
     using (Stream inputSteam = this.Assets.Open("7.png"))
                {

                    byte[] bytes = inputSteam.ReadAllBytes();// convert to byte array???


                    inferenceInterface.Feed("tf_data", bytes, bytes.Length);
                    inferenceInterface.Run(new [] { "tf_pred:0" });
                    inferenceInterface.Fetch("tf_pred:0", predictions);
                    ....

                }      

我收到一个错误：

Java.Lang.IllegalArgumentException：期望arg [0]为float但提供uint8

预先感谢。

Answer 1

期望arg [0]为float，但提供了uint8

TensorFlowInferenceInterface.Feed期待一个浮点数组，因此你需要转换基于资产的图像，将其文件编码（jpg | png | ...）解码为Bitmap并从中获取浮点数组。

Android Bitmap To Float Array

public float[] AndroidBitmapToFloatArray(Bitmap bitmap)
{
    // Assuming a square image to sample|process, adjust based upon your model requirements
    const int sizeX = 255;
    const int sizeY = 255;

    float[] floatArray;
    int[] intArray;
    using (var sampleImage = Bitmap.CreateScaledBitmap(bitmap, sizeX, sizeY, false).Copy(Bitmap.Config.Argb8888, false))
    {
        floatArray = new float[sizeX * sizeY * 3];
        intArray = new int[sizeX * sizeY];
        sampleImage.GetPixels(intArray, 0, sizeX, 0, 0, sizeX, sizeY);
        sampleImage.Recycle();
    }
    for (int i = 0; i < intArray.Length; ++i)
    {
        var intValue = intArray[i];
        floatArray[i * 3 + 0] = ((intValue & 0xFF) - 104);
        floatArray[i * 3 + 1] = (((intValue >> 8) & 0xFF) - 117);
        floatArray[i * 3 + 2] = (((intValue >> 16) & 0xFF) - 123);
    }
    return floatArray;
}

Example:

float[] feedArray;
using (var imageAsset = Assets.Open("someimage"))
using (var bitmappAsset = BitmapFactory.DecodeStream(imageAsset))
{
    feedArray = AndroidBitmapToFloatArray(bitmappAsset);
}
inferenceInterface.Feed("tf_data", feedArray, feedArray.Length);