public void calculateGradientImageTest() //Проверка подсчета градиентов на картинке
{
//arrange
IParser parser = new Parser();
Bitmap bitmap = parser.readPNG("Data\\sample_10.png");
IMathematical strat = new MathematicialSearchPoint1(); //Подсчет градиента первой стратегией
strat.setImage(bitmap);
Elimination elemenation = new Elimination(strat);
Data.Image img = new Data.Image("Data\\sample_10.png");
//act
elemenation.calculateGradientImage(img);
double[,] exepected = new double[img.width(), img.height()];
double[,] actual = elemenation.swingSharpness;
//assert
for (int i = 0; i < img.width(); i++)
{
for (int j = 0; j < img.height(); j++)
{
Assert.AreEqual(strat.gradientAtPoint(i, j), actual[i, j]);
}
}
}
public void calculateGradientImage(Data.Image image)
{
if (swingSharpness == null)
{
swingSharpness = new double[image.width(), image.height()];
for (int x = 0; x < image.width(); x++)
{
for (int y = 0; y < image.height(); y++)
{
swingSharpness[x, y] = -255;
}
}
}
curentImage = image.image;
curentImage = changeImage.translateToMonochrome(curentImage);
matematical.setImage(curentImage);
/*
* for (int x = 0; x < image.width(); x++)
* for (int y = 0; y < image.height(); y++)
* {
* double gradient = matematical.gradientAtPoint(x, y);
* if (gradient > swingSharpness[x, y])
* swingSharpness[x, y] = gradient;
* }
*/
Parallel.For(0, 4, calculateGradientImage);
}
public void clarifySolution(Data.Image image)
{
if (swingSharpness == null)
{
swingSharpness = new double[image.width(), image.height()];
for (int x = 0; x < image.width(); x++)
{
for (int y = 0; y < image.height(); y++)
{
swingSharpness[x, y] = 0;
}
}
width = image.width();
height = image.height();
}
List <Data.Point> listPoint = new List <Data.Point>();
Bitmap curentImage = image.image;
curentImage = changeImage.translateToMonochrome(curentImage);
matematical.setImage(curentImage);
for (int x = 0; x < image.width(); x++)
{
for (int y = 0; y < image.height(); y++)
{
double gradient = matematical.gradientAtPoint(x, y);
if (gradient > swingSharpness[x, y])
{
listPoint.Add(new Data.Point(x, y));
swingSharpness[x, y] = gradient;
}
}
}
solution.setValue(listPoint, image);
}
public void getSolutionTest() //Проверка отсева (получения хороших точек)
{
//Хорошая точка-значение градиента больше порогового значения
//arrange
IMathematical strat = new MathematicialSearchPoint1();
Elimination elemenation = new Elimination(strat);
Data.Image img = new Data.Image("Data\\sample_10.png");
elemenation.calculateGradientImage(img); //Вычисление градиента
//act
double maxGradient = elemenation.swingSharpness[0, 0];
double minGradient = elemenation.swingSharpness[0, 0];
for (int i = 0; i < img.width(); i++) //Найти макс и мин
{
for (int j = 0; j < img.height(); j++)
{
maxGradient = Math.Max(maxGradient, elemenation.swingSharpness[i, j]);
minGradient = Math.Min(minGradient, elemenation.swingSharpness[i, j]);
}
}
double threshold = minGradient + ((maxGradient - minGradient) * 0.1); //порог
List <Data.Point> exepected = new List <Data.Point>();
for (int i = 0; i < img.width(); i++)
{
for (int j = 0; j < img.height(); j++)
{
if (elemenation.swingSharpness[i, j] >= threshold)
{
exepected.Add(new Data.Point(i, j));
}
}
}
List <Data.Point> actual = new List <Data.Point>();
actual = elemenation.getSolution();
//assert
Debug.WriteLine("Проверка количества точек");
Assert.AreEqual(actual.Count, exepected.Count);
Debug.WriteLine("Проверка самих точек");
int t = 0;
foreach (Data.Point p1 in exepected)
{
Assert.AreEqual(p1.x, actual[t].x);
Assert.AreEqual(p1.y, actual[t].y);
t++;
}
}
public void clarifySolution(Data.Image image)
{
Random random = new Random();
List <Point> listPoint = new List <Point>();
//Задаем случайное количество точек попавших в фокус
int countFocusPoint = random.Next(image.width(), image.width() * image.height());
for (int i = 0; i < countFocusPoint; i++)
{
int x = random.Next(1, image.width());
int y = random.Next(1, image.height());
Point point = new Point(x, y);
listPoint.Add(point);
}
solution.setValue(listPoint, image);
}
public void setValue(List <Point> coordinate, Image image)
{
if (nullSolution)
{
createdBeginSolution(image.width(), image.height());
}
foreach (Point point in coordinate)
{
mapHeights[point.x, point.y] = image.tall;
_sharpImage.SetPixel(point.x, point.y, image.GetPixel(point.x, point.y));
}
}
public void heightTest() //Проверка получения высоты изображения в пикселях
{
//arrange
Data.Image img = new Data.Image("Data\\sample_01.png");
//act
double height = img.height();
//assert
Debug.WriteLine("Проверка ширины");
Assert.AreEqual(height, 10);
}
public void clarifySolution(Data.Image image, List <IMathematical> coreGoodPoint, List <Data.Point> goodPoint)
{
if (swingSharpness == null)
{
swingSharpness = new double[image.width(), image.height()];
/* for (int x = 0; x < image.width(); x++)
* for (int y = 0; y < image.height(); y++)
* swingSharpness[x, y] = 0;*/
width = image.width();
height = image.height();
}
List <Data.Point> listPoint = new List <Data.Point>();
Bitmap curentImage = image.image;
curentImage = changeImage.translateToMonochrome(curentImage);
HashSet <IMathematical> set = new HashSet <IMathematical>(coreGoodPoint);
foreach (var i in set)
{
i.setImage(curentImage);
}
for (int i = 0; i < goodPoint.Count; i++)
{
int x = goodPoint[i].x;
int y = goodPoint[i].y;
matematical = set.First(item => item.GetType() == coreGoodPoint[i].GetType());
double gradient = matematical.gradientAtPoint(x, y);
if (gradient > swingSharpness[x, y])
{
listPoint.Add(new Data.Point(x, y));
swingSharpness[x, y] = gradient;
}
}
solution.setValue(listPoint, image);
}
public void GetPixelTest() //Проверка получения цвета пикселя изображения
{
//arrange
Data.Image img = new Data.Image("Data\\sample_01.png");
//act
//assert
Debug.WriteLine("Проверка цвета пикселя");
for (int i = 0; i < img.width(); i++) //По всем пикселям
{
for (int j = 0; j < img.height(); j++)
{
Assert.AreEqual(img.GetPixel(i, j), Color.FromArgb(0, 0, 0));
}
}
}
