/// <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)); }