private async Task EvaluteImageAsync(VideoFrame videoFrame)
{
try
{
var startTime = DateTime.Now;
if (model == null)
{
var modelFile = await StorageFile.GetFileFromApplicationUriAsync(new Uri("ms-appx:///Model/Inceptionv3.onnx"));
if (modelFile != null)
{
model = new Inceptionv3Model();
await MLHelper.CreateModelAsync(modelFile, model);
}
}
var input = new Inceptionv3Input()
{
image = ImageFeatureValue.CreateFromVideoFrame(videoFrame)
};
var res = await model.EvaluateAsync(input) as Inceptionv3Output;
if (res != null)
{
var results = new List <LabelResult>();
if (res.classLabelProbs != null)
{
var dict = res.classLabelProbs.FirstOrDefault();
foreach (var kv in dict)
{
results.Add(new LabelResult
{
Label = kv.Key,
Result = (float)Math.Round(kv.Value * 100, 2)
});
}
results.Sort((p1, p2) =>
{
return(p2.Result.CompareTo(p1.Result));
});
}
await Dispatcher.RunAsync(Windows.UI.Core.CoreDispatcherPriority.High, () =>
{
previewControl.EvalutionTime = (DateTime.Now - startTime).TotalSeconds.ToString();
outputText.Text = res.classLabel.GetAsVectorView().FirstOrDefault();
resultList.ItemsSource = results;
});
}
}
catch (Exception ex)
{
await AlertHelper.ShowMessageAsync(ex.ToString());
}
}
public async Task <Inceptionv3Output> EvaluateAsync(Inceptionv3Input input)
{
binding.Bind("image", input.image);
var result = await session.EvaluateAsync(binding, "0");
var output = new Inceptionv3Output();
output.classLabel = result.Outputs["classLabel"] as TensorString;
output.classLabelProbs = result.Outputs["classLabelProbs"] as IList <Dictionary <string, float> >;
return(output);
}
