/// <summary>
/// Make a prediction using the standard interface
/// </summary>
/// <param name="input">an instance of ComputerInput to predict from</param>
/// <param name="error">If an error occurs, upon return contains an NSError object that describes the problem.</param>
public ComputerOutput GetPrediction(ComputerInput input, out NSError error)
{
var prediction = model.GetPrediction(input, out error);
if (prediction == null)
{
return(null);
}
var lossValue = prediction.GetFeatureValue("loss").DictionaryValue;
var classLabelValue = prediction.GetFeatureValue("classLabel").StringValue;
return(new ComputerOutput(lossValue, classLabelValue));
}
/// <summary>
/// Make a prediction using the convenience interface
/// </summary>
/// <param name="data"> as color (kCVPixelFormatType_32BGRA) image buffer, 227 pizels wide by 227 pixels high</param>
/// <param name="error">If an error occurs, upon return contains an NSError object that describes the problem.</param>
public ComputerOutput GetPrediction(CVPixelBuffer data, out NSError error)
{
var input = new ComputerInput(data);
return(GetPrediction(input, out error));
}