/// <summary>
/// Make a prediction using the standard interface
/// </summary>
/// <param name="input">an instance of FreeSoundsPlusModel25Input to predict from</param>
/// <param name="error">If an error occurs, upon return contains an NSError object that describes the problem.</param>
public FreeSoundsPlusModel25Output GetPrediction(FreeSoundsPlusModel25Input input, out NSError error)
{
if (input == null)
{
throw new ArgumentNullException(nameof(input));
}
var prediction = model.GetPrediction(input, out error);
if (prediction == null)
{
return(null);
}
var classLabelProbsValue = prediction.GetFeatureValue("classLabelProbs").DictionaryValue;
var classLabelValue = prediction.GetFeatureValue("classLabel").StringValue;
return(new FreeSoundsPlusModel25Output(classLabelProbsValue, classLabelValue));
}
/// <summary>
/// Make a prediction using the convenience interface
/// </summary>
/// <param name="audioSamples">Input audio samples to be classified as 15600 1-dimensional array of floats</param>
/// <param name="options">prediction options</param>
/// <param name="error">If an error occurs, upon return contains an NSError object that describes the problem.</param>
public FreeSoundsPlusModel25Output GetPrediction(MLMultiArray audioSamples, MLPredictionOptions options, out NSError error)
{
var input = new FreeSoundsPlusModel25Input(audioSamples);
return(GetPrediction(input, options, out error));
}