public TensorflowModelOutput Evaluate(TensorfloModelInput input)
{
var outputNames = new[] { OutputName };
var outputs = new float[labels.Count()];
inferenceInterface.Feed(InputName, input.Data, 1, InputSize, InputSize, 3);
inferenceInterface.Run(outputNames);
inferenceInterface.Fetch(OutputName, outputs);
return(TensorflowModelOutput.CreateTensorflowModelOutput(labels, outputs));
}
public async Task <IReadOnlyList <ImageClassification> > ClassifyImage(byte[] image)
{
if (!IsInitialized)
{
await Init();
}
var input = TensorfloModelInput.CreateFrom(image);
var results = tensorflowModel.Evaluate(input);
return(results.Loss
.Select(p => new ImageClassification(p.Key, p.Value))
.Where(p => p.Probability > 0.85)
.ToList());
}
