public PostureRecognition(PatternType patternType, DataTrainingType dataTrainingType, int iterations) { this.networkPattern = PatternResolver <InputDataType, OutputDataType> .ResolvePattern(patternType, dataTrainingType); var activationFunction = new ActivationFunction(); activationFunction.InitializeSigmodeFunction(1.0); network = new NeuronNetwork(activationFunction, iterations); }
public static INeuralNetworkPattern <InputDataType, OutputDataType> ResolvePattern(PatternType patternType, DataTrainingType dataTrainigType) { var dataTrainingT = DataTrainingResolver <InputDataType, OutputDataType> .ResolveDataTraining(dataTrainigType); NeuralNetworkPatternBase <InputDataType, OutputDataType> neuralNetworkPattern; switch (patternType) { case PatternType.AnglePatternAll: neuralNetworkPattern = new AnglePatternAll <InputDataType, OutputDataType>(); break; case PatternType.AnglePatternElbowKnee: neuralNetworkPattern = new AnglePatternElbowKnee <InputDataType, OutputDataType>(); break; default: throw new ArgumentException("Not Pattern Found"); } neuralNetworkPattern.DataTrainingResolver = dataTrainingT; return(neuralNetworkPattern); }
public static IDataTraining <InputDataType, OutputDataType> ResolveDataTraining(DataTrainingType patternType) { switch (patternType) { case DataTrainingType.DataTrainingFile: return(new DataTrainingFile <InputDataType, OutputDataType>()); default: throw new ArgumentException("Not DataTrainingType Found"); } }