public async Task PerformCalculation()
{
await Task.Run(() =>
{
var sortedFaces = InputHelper.TransformIntoListOfLists(Faces);
Console.WriteLine("Szykuje dane zbioru uczacego");
var neuralLearningInput = NetworkHelper.CreateNetworkInputDataSet(sortedFaces, 12, 5, DataSetType.Learning, 12 /*, new bool[] { true,true, false, true,false,true,true,true,true,true,false,false }*/);
var neuralLearningOutput = NetworkHelper.CreateNetworkOutputDataSet(sortedFaces, 12, 5, DataSetType.Learning, 15);
var neuralValidationInput = NetworkHelper.CreateNetworkInputDataSet(sortedFaces, 12, 5, DataSetType.Validation, 12 /*, new bool[] { true, true, false, true, false, true, true, true, true, true, false, false }*/);
var neuralValidationOutput = NetworkHelper.CreateNetworkOutputDataSet(sortedFaces, 12, 5, DataSetType.Validation, 15);
var neuralTestingInput = NetworkHelper.CreateNetworkInputDataSet(sortedFaces, 12, 5, DataSetType.Testing, 12 /*, new bool[] { true, true, false, true, false, true, true, true, true, true, false, false }*/);
var neuralTestingOutput = NetworkHelper.CreateNetworkOutputDataSet(sortedFaces, 12, 5, DataSetType.Testing, 15);
var learningSet = NetworkHelper.NormaliseDataSet(neuralLearningInput, neuralLearningOutput);
var validationSet = NetworkHelper.NormaliseDataSet(neuralValidationInput, neuralValidationOutput);
var testingSet = NetworkHelper.NormaliseDataSet(neuralTestingInput, neuralTestingOutput);
var network = NetworkHelper.LearnNetwork(learningSet, testingSet, Faces[0].features.Count, peopleNumber, inputData, validationSet);
learnedNetwork = network;
});
}