/// <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);
}
async Task ProcessOutputAsync(ONNXModelOutput evalOutput)
{
// Get the label and loss from the output
loss = (evalOutput.loss[0]["AnSungEmpty"] * 100.0f).ToString("#0.00");
loss2 = (evalOutput.loss[0]["ChamGgeEmpty"] * 100.0f).ToString("#0.00");
loss3 = (evalOutput.loss[0]["MiYuckGukEmpty"] * 100.0f).ToString("#0.00");
loss4 = (evalOutput.loss[0]["ShinRaMyunEmpty"] * 100.0f).ToString("#0.00");
loss5 = (evalOutput.loss[0]["AllSet"] * 100.0f).ToString("#0.00");
// Display the score
await this.Dispatcher.RunAsync(CoreDispatcherPriority.Normal,
() =>
{
scoreTB.Text = "An Sung Tang Myun Empty" + "\n " + loss + "%"
+ "\nCham Gge Ra Myun Empty" + "\n " + loss2 + "%"
+ "\nMi Yuck Guk Ra Myun Empty" + "\n " + loss3 + "%"
+ "\nShin Ra Myun Empty" + "\n " + loss4 + "%"
+ "\n\n All Ra Myuns are set" + "\n " + loss5 + "%";
}
);
}