public async Task <Inceptionv3_convertedOutput> Evaluate(StorageFile file)
{
Inceptionv3_convertedInput tensorInput = new Inceptionv3_convertedInput();
byte[] image = await ResizedImage(file, INPUT_WIDTH, INPUT_HEIGHT);
List <float> input = new List <float>();
List <float> R = new List <float>();
List <float> G = new List <float>();
List <float> B = new List <float>();
for (int j = 0; j < INPUT_HEIGHT; j++)
{
for (int i = 0; i < INPUT_WIDTH; i++)
{
R.Add(GetPixel(image, i, j, INPUT_WIDTH, INPUT_HEIGHT).R / 255f);
G.Add(GetPixel(image, i, j, INPUT_WIDTH, INPUT_HEIGHT).G / 255f);
B.Add(GetPixel(image, i, j, INPUT_WIDTH, INPUT_HEIGHT).B / 255f);
}
}
input.AddRange(R);
input.AddRange(G);
input.AddRange(B);
tensorInput.input_1_0 = TensorFloat.CreateFromArray(new long[] { 1, 256, 256, 3 }, input.ToArray());
return(await Model.EvaluateAsync(tensorInput));
}
public async Task <Inceptionv3_convertedOutput> EvaluateAsync(Inceptionv3_convertedInput input)
{
binding.Bind("input_1_0", input.input_1_0);
var result = await session.EvaluateAsync(binding, "0");
var output = new Inceptionv3_convertedOutput();
output.dense_2_Softmax_01 = result.Outputs["dense_2_Softmax_01"] as TensorFloat;
return(output);
}
