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); }