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);
}
private async void recognizeButton_Click(object sender, RoutedEventArgs e)
{
FileOpenPicker fileOpenPicker = new FileOpenPicker();
fileOpenPicker.SuggestedStartLocation = PickerLocationId.PicturesLibrary;
fileOpenPicker.FileTypeFilter.Add(".jpg");
fileOpenPicker.FileTypeFilter.Add(".bmp");
fileOpenPicker.FileTypeFilter.Add(".png");
fileOpenPicker.ViewMode = PickerViewMode.Thumbnail;
var inputFile = await fileOpenPicker.PickSingleFileAsync();
if (inputFile == null)
{
// The user cancelled the picking operation
return;
}
imageLabel.Text = "Recognizing...";
SoftwareBitmap softwareBitmap;
using (IRandomAccessStream stream = await inputFile.OpenAsync(FileAccessMode.Read))
{
// Create the decoder from the stream
BitmapDecoder decoder = await BitmapDecoder.CreateAsync(stream);
// Get the SoftwareBitmap representation of the file
softwareBitmap = await decoder.GetSoftwareBitmapAsync();
softwareBitmap = SoftwareBitmap.Convert(softwareBitmap, BitmapPixelFormat.Bgra8, BitmapAlphaMode.Ignore);
var source = new SoftwareBitmapSource();
await source.SetBitmapAsync(softwareBitmap);
previewImage.Source = source;
VideoFrame vf = VideoFrame.CreateWithSoftwareBitmap(softwareBitmap);
await CropImageAsync(vf);
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];
}
}
imageLabel.Text = string.Format("{0}\r\n({1})", classList.classList[maxIndex], maxProb);
}
}