public async Task <IDictionary <string, float> > EvaluateAsync(SoftwareBitmap bitmap)
{
var videoFrame = VideoFrame.CreateWithSoftwareBitmap(bitmap);
var imageFeatureValue = ImageFeatureValue.CreateFromVideoFrame(videoFrame);
var input = new SmartInkModelInput()
{
data = imageFeatureValue
};
var output = new SmartInkModelOutput();
_binding.Bind("data", input.data);
_binding.Bind("classLabel", output.ClassLabel);
_binding.Bind("loss", output.Loss);
LearningModelEvaluationResult result = await _session.EvaluateAsync(_binding, "0");
output.ClassLabel = result.Outputs["classLabel"] as TensorString;//).GetAsVectorView()[0];
output.Loss = result.Outputs["loss"] as IList <IDictionary <string, float> >;
var dict = new Dictionary <string, float>();
foreach (var key in output.Loss[0].Keys)
{
dict.Add(key, output.Loss[0][key]);
}
return(dict);
}
/// <summary>
/// Evaluate the model
/// </summary>
/// <param name="input">The VideoFrame to evaluate</param>
/// <returns></returns>
public async Task <ONNXModelOutput> EvaluateAsync(ONNXModelInput input)
{
var output = new ONNXModelOutput();
var binding = new LearningModelBinding(_session);
binding.Bind("data", input.data);
binding.Bind("classLabel", output.classLabel);
binding.Bind("loss", output.loss);
LearningModelEvaluationResult result = await _session.EvaluateAsync(binding, "0");
return(output);
}
public async Task <ModelOutput> EvaluateAsync(OnnxModelInput input)
{
var output = new ModelOutput();
var binding = new LearningModelBinding(_session);
binding.Bind("data", input.Data);
//binding.Bind("classLabel", output.ClassLabel);
//binding.Bind("loss", output.Loss);
LearningModelEvaluationResult evalResult = await _session.EvaluateAsync(binding, "0");
return(output);
}
public static unsafe T Output <T>(this LearningModelEvaluationResult self, int index) where T : class
{
return(self.Outputs.ElementAt(index).Value as T);
}
public static unsafe object Output(this LearningModelEvaluationResult self, int index)
{
return(self.Outputs.ElementAt(index).Value as object);
}
