/// <summary>
/// Smoothing Black-White picture.
/// </summary>
/// <param name="pic">Picture.</param>
/// <param name="type">Type of smootthing.</param>
/// <param name="matrixSize">Size of matrix of smooth.</param>
/// <returns>Smoothed picture.</returns>
public static Bitmap SmoothBWPicture(this Bitmap pic, SmoothMatrixType type, int matrixSize)
{
double[,] matrix = new double[matrixSize, matrixSize];
// Calculate matrix of smooth
switch (type)
{
case SmoothMatrixType.Simple:
{
double temp = 1.0 / (matrixSize * matrixSize);
for (int i = 0; i < matrixSize; i++)
{
for (int j = 0; j < matrixSize; j++)
{
matrix[i, j] = temp;
}
}
break;
}
case SmoothMatrixType.Gauss:
{
//TODO doesn't work
// calculate discret gauss matrix
double div = 0;
for (int i = 0; i < matrixSize; i++)
{
for (int j = 0; j < matrixSize; j++)
{
matrix[i, j] = GaussCoeff(i, j, 1);
div += matrix[i, j] * matrix[i, j];
}
}
// norm matrix
for (int i = 0; i < matrixSize; i++)
{
for (int j = 0; j < matrixSize; j++)
{
matrix[i, j] /= div;
}
}
break;
}
}
// Smooth pitcture
Bitmap result = SmoothingBW(pic, matrix);
return(result);
}
public Bitmap CannyProcessing(SmoothMatrixType type, int size)
{
Invoke(new Action(() => StateLbl.Text = "Начато преобразование"));
var bitmap = new Bitmap(originalPic, 64, 64).GetBWPicture();
Invoke(new Action(() =>
{
StateLbl.Text = "Получено чернобелое изображение";
resultPicBox.Image = bitmap;
UpdateForm();
}));
var smoothedBWPicture = bitmap.SmoothBWPicture(type, size);
Invoke(new Action(() =>
{
StateLbl.Text = "Получено размытое изображение";
resultPic = bitmap;
UpdateForm();
}));
var gradients = smoothedBWPicture.FindGradients();
Invoke(new Action(() =>
{
StateLbl.Text = "Найдены градиенты";
StateLbl.Refresh();
}));
var gradientsWithSuppressedMaximums = gradients.SuppressMaximums();
Invoke(new Action(() =>
{
StateLbl.Text = "Удалены немаксимумы";
StateLbl.Refresh();
}));
var cuttedGradients = gradientsWithSuppressedMaximums.BlackEdge(size / 2 + 1);
Invoke(new Action(() =>
{
StateLbl.Text = "Закрашены края";
StateLbl.Refresh();
}));
var filteredGradients = cuttedGradients;//.Filtering();
//Invoke(new Action(() =>
//{
// StateLbl.Text = "Произведена фильтрация. Готово!";
// StateLbl.Refresh();
//}));
//Invoke(new Action(() =>
//{
// StateLbl.Text = "Нейросеть вычисляет есть ли человек на фотографии!";
// StateLbl.Refresh();
// BNPNet net = new BNPNet(@"C:\Users\vladb\Desktop\somaset\network.json");
// var output = net.GetResult(filteredGradients.LengthsToArray().ToVector());
// StateLbl.Text = "Человек " + ((1 - output[0]) < 0.2 ? "присутствует" : "отсутствует") + " на фотографии";
// StateLbl.Refresh();
//}));
return(filteredGradients.ToBitmap());
}
