public async Task <modelOutput> EvaluateAsync(modelInput input)
{
var output = new modelOutput();
binding.Bind("data", input.data);
binding.Bind("classLabel", output.ClassLabel);
binding.Bind("loss", output.Loss);
var result = await session.EvaluateAsync(binding, "0");
output.ClassLabel = result.Outputs["classLabel"] as TensorString;
output.Loss = result.Outputs["loss"] as List <IDictionary <string, float> >;
return(output);
}
private async void EvaluateVideoFrameAsync(VideoFrame inputImage)
{
elaborate = true;
//Image crop to required size
ModelInput.data = ImageFeatureValue.CreateFromVideoFrame(await CenterCropImageAsync(inputImage, 227, 227));
//Evaluate the model
ModelOutput = await ModelGen.EvaluateAsync(ModelInput);
//If no results
if (ModelOutput.Loss == null || ModelOutput.Loss.Count == 0)
{
return;
}
var loss = ModelOutput.Loss.ToList()[0];
//Find max
var maxValue = loss.Values.Max();
if (maxValue > 0.7)
{
lastAlert = DateTime.Now;
var pos = loss.Values.ToList().IndexOf(maxValue);
var label = loss.Keys.ToList().ElementAt(pos);
await Dispatcher.RunAsync(CoreDispatcherPriority.Normal,
() =>
{
//Get current image
var source = new SoftwareBitmapSource();
source.SetBitmapAsync(inputImage.SoftwareBitmap);
//Create alarm image
var lossStr = new ResultModel
{
Name = label,
Percent = maxValue * 100.0f,
Image = source
};
resultsList.Insert(0, lossStr);
PlaySound();
});
}
elaborate = false;
}
