public async Task InferenceImage(string _iamgePath)
{
StorageFile imageFile = await StorageFile.GetFileFromPathAsync(_iamgePath);
using (IRandomAccessStream stream = await imageFile.OpenAsync(FileAccessMode.Read))
{
// Create the decoder from the stream
BitmapDecoder decoder = await BitmapDecoder.CreateAsync(stream);
// Get the SoftwareBitmap representation of the file
SoftwareBitmap softwareBitmap = await decoder.GetSoftwareBitmapAsync();
VideoFrame vf = VideoFrame.CreateWithSoftwareBitmap(softwareBitmap);
await CropInputImageAsync(vf).ConfigureAwait(false);
ModelInput.data_0 = cropped_vf;
ModelOutput = await ModelGen.EvaluateAsync(ModelInput);
float maxProb = 0;
int maxIndex = 0;
for (int i = 0; i < ModelOutput.prob_1.Count; i++)
{
if (ModelOutput.prob_1[i] > maxProb)
{
maxIndex = i;
maxProb = ModelOutput.prob_1[i];
}
}
Console.WriteLine(string.Format("max {0}:{1}:{2}", maxIndex, classList.classList[maxIndex], maxProb));
}
}
public async Task <Vgg19ModelOutput> EvaluateAsync(Vgg19ModelInput input)
{
Vgg19ModelOutput output = new Vgg19ModelOutput();
LearningModelBindingPreview binding = new LearningModelBindingPreview(learningModel);
binding.Bind("data_0", input.data_0);
binding.Bind("prob_1", output.prob_1);
LearningModelEvaluationResultPreview evalResult = await learningModel.EvaluateAsync(binding, string.Empty);
return(output);
}