/// <summary>
/// Выполнить распознавание.
/// </summary>
private static void DoRecognizeWork()
{
Console.BackgroundColor = ConsoleColor.Green;
Console.ForegroundColor = ConsoleColor.Black;
Console.WriteLine(ConsoleMessageConstants.RECOGNIZE_RESULT_MESSAGE);
Console.BackgroundColor = ConsoleColor.Black;
Console.ForegroundColor = ConsoleColor.Green;
Console.WriteLine(ConsoleMessageConstants.LOAD_PATH_MESSAGE);
var path = GetPathToWeightFiles();
var weightLodUtil = new WeightLoadUtil(path);
weightLodUtil.Load();
var data = weightLodUtil.GetData();
var coreToLoad = weightLodUtil.GetNewCore();
FilterCoreModel.UpdateCore(coreToLoad);
var breakFlag = false;
var isFirstIteration = true;
do
{
if (isFirstIteration)
{
RecognizeImage(data);
isFirstIteration = false;
}
Console.WriteLine(ConsoleMessageConstants.RECOGNIZE_ANOTHER_MESSAGE);
var dialogResult = Console.ReadLine();
if (DialogConstants.NoResults.Contains(dialogResult))
{
breakFlag = true;
}
if (DialogConstants.YesResults.Contains(dialogResult))
{
RecognizeImage(data);
}
} while (!breakFlag);
Console.WriteLine(ConsoleMessageConstants.PRESS_ANY_KEY_MESSAGE);
Console.ReadKey();
Console.WriteLine(ConsoleMessageConstants.EXIT_MESSAGE);
System.Threading.Thread.Sleep(500);
Environment.Exit(0);
}
/// <summary>
/// Выполнить обучение.
/// </summary>
private static void DoLearnWork()
{
Console.BackgroundColor = ConsoleColor.Green;
Console.ForegroundColor = ConsoleColor.Black;
Console.WriteLine(ConsoleMessageConstants.LEARN_RESULT_MESSAGE);
Console.BackgroundColor = ConsoleColor.Black;
Console.ForegroundColor = ConsoleColor.Green;
var pathToFiles = GetPathToFiles();
var pathToResources = PathHelper.GetResourcesPath();
if (string.IsNullOrEmpty(pathToFiles))
{
pathToFiles = pathToResources;
}
var images = Directory.GetFiles(pathToFiles).ToList();
var converter = new ImageConverterUtil(images);
var listOfPicturesMatrix = converter.ConvertImagesToMatrix();
var iterationsCount = listOfPicturesMatrix.Count;
var configuration = new Configuration
{
Alpha = 3.1,
Epsilon = 3.1,
EpochCount = 3,
IdealResult = 1,
IterationsInEpochCount = iterationsCount
};
var layers = new List <Layer>();
var filterCore = FilterCoreModel.Initialize();
LayersInitialize(listOfPicturesMatrix, layers, filterCore,
out Dictionary <string, double> inputLayerWeights,
out List <NeuronModel> convolutionalLayerNeurons,
out List <NeuronModel> hiddenLayerNeurons,
out NeuronModel outputNeuron);
var learningUtil = new LearningUtil(layers, configuration, listOfPicturesMatrix);
learningUtil.StartToLearn();
}
/// <summary>
/// Обновить ядро фильтра.
/// </summary>
/// <param name="gradients">Матрица градиентов.</param>
private void UpdateCore(double[,] gradients)
{
var updatedCore = new double[MatrixConstants.FILTER_MATRIX_SIZE,
MatrixConstants.FILTER_MATRIX_SIZE];
for (var xIndex = 0; xIndex < MatrixConstants.FILTER_MATRIX_SIZE; ++xIndex)
{
for (var yIndex = 0; yIndex < MatrixConstants.FILTER_MATRIX_SIZE; ++yIndex)
{
updatedCore[xIndex, yIndex] = _configuration.Epsilon *
gradients[xIndex, yIndex] + _configuration.Alpha *
FilterCoreModel.LastCoreValue[xIndex, yIndex];
}
}
FilterCoreModel.UpdateCore(updatedCore);
}
