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");
}
}
