Keras.Models.BaseModel model = Keras.Models.Model.LoadModel("keras_model.h5");
bool actionBtn;
void Whl(){
while (actionBtn){
Bitmap imbit = GetImageBitmap();
NDArray ndarray = imbit.ToNDArray(flat: false, copy: true, discardAlpha: true);
NDArray normalized_image_array = (ndarray.astype(NumSharp.np.float32) / 127.0) - 1;
float[] fArr = normalized_image_array.ToArray<float>().Select(x => (float)x).ToArray();
Numpy.NDarray npArr = Numpy.np.array(fArr, Numpy.np.float32).reshape(1, 224, 224, 3);
var y = model.Predict(npArr);
y = y.argmax();
Console.WriteLine(y.asscalar<int>().ToString());
Thread.Sleep(1000);
}
}
private void Event(object sender, EventArgs e)
{
this.actionBtn = (bool)sender;
if (actionBtn)
{
Task.Run(()=>Whl());
}
}
