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 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 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 widthTest() //Проверка получения ширины изображения в пикселях
{
//arrange
Data.Image img = new Data.Image("Data\\sample_01.png");
//act
double widh = img.width();
//assert
Debug.WriteLine("Проверка ширины");
Assert.AreEqual(widh, 20);
}
public void tallTest() //Проверка считывания высоты изображения при создании объекта конструктором Image(path)
{
//arrange
string path = "Data\\sample_01.png";
Data.Image img = new Data.Image(path);
//act
double rez = img.tall;
double exepected = 1;
//assert
Assert.AreEqual(exepected, rez);
}
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 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));
}
}
}
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 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);
}
static void Main(string[] args)
{
IParser parser = new Parser();
ICalculated calculated;
IPreserveOBJ preserveOBJ = new PreserveOBJ();
IPreservePNG preservePNG = new PreservePNG();
IElimination elimination;
IAnalysis analysis;
Setting setting = null;
INIManager manager;
List <string> filesImagesname;
string pathFolder;
string pathConfig;
string pathSetting;
string saveFolder;
if (args.Length == 0)
{
Console.WriteLine("usage: Get3DModel.exe <path to folder>"); Environment.Exit(-1);
}
pathFolder = args[0];
pathSetting = pathFolder + "\\setting.ini";
manager = new INIManager(pathSetting);
string[] separators = { "\\" };
string[] words = pathFolder.Split(separators, StringSplitOptions.RemoveEmptyEntries);
saveFolder = words[0];
for (int i = 1; i < words.Length - 1; i++)
{
saveFolder = saveFolder + "\\" + words[i];
}
saveFolder = saveFolder + "\\Resulst_" + words[words.Length - 1];
Directory.CreateDirectory(saveFolder);
StreamWriter timeTxt = new StreamWriter(saveFolder + "\\time.txt");
string[] listFileFolder = Directory.GetDirectories(pathFolder);
foreach (string folder in listFileFolder)
{
FileInfo fileInfFolder = new FileInfo(folder);
string nameFolder = fileInfFolder.Name;
string saveFolderCurrent = saveFolder + "\\" + nameFolder;
Directory.CreateDirectory(saveFolderCurrent);
filesImagesname = Directory.GetFiles(folder, "*.png").ToList <string>();
pathConfig = Directory.GetFiles(folder).ToList().First(
x => x.EndsWith(".camera") || x.EndsWith(".ini") || x.EndsWith("ConfigurationFile.txt"));
FileInfo fileInf = new FileInfo(pathConfig);
if (fileInf.Exists)
{
setting = new Setting(pathConfig);
}
else
{
Console.WriteLine("the configuration file is not found");
Environment.Exit(-1);
}
Stopwatch timeForParsing = new Stopwatch();
timeForParsing.Restart();
string nameCoreElimination = manager.GetPrivateString("ELIMINATION", "core");
IMathematical coreElimination = getMathematical(nameCoreElimination);
if (coreElimination != null)
{
string thresholdElimination = manager.GetPrivateString("ELIMINATION", "threshold");
if (thresholdElimination != "default")
{
double deltaTheshold = Convert.ToDouble(thresholdElimination);
coreElimination.setDeltaThreshold(deltaTheshold);
}
elimination = new Elimination(coreElimination);
}
else
{
elimination = new Elimination();
}
for (int i = 0; i < filesImagesname.Count; i++)
{
if (filesImagesname[i].EndsWith("sharpImage.png"))
{
continue;
}
Data.Image itemImage = new Data.Image(filesImagesname[i]);
elimination.calculateGradientImage(itemImage);
}
List <Data.Point> goodPoint = elimination.getSolution();
string boolSelectionCore = manager.GetPrivateString("SELECTION_CORE", "selection_core");
if (boolSelectionCore == "true")
{
string nameCore3x3 = manager.GetPrivateString("CORE", "3_core");
IMathematical core3x3 = getMathematical(nameCore3x3);
if (core3x3 == null)
{
core3x3 = new MathematicialSearchPoint1();
}
string nameCore5x5 = manager.GetPrivateString("CORE", "5_core");
IMathematical core5x5 = getMathematical(nameCore5x5);
if (core5x5 == null)
{
core5x5 = new MathematicialSearchPoint8();
}
string nameCore7x7 = manager.GetPrivateString("CORE", "7_core");
IMathematical core7x7 = getMathematical(nameCore5x5);
if (core7x7 == null)
{
core7x7 = new MathematicialSearchPoint9();
}
analysis = new Analysis(goodPoint, core3x3, core5x5, core7x7);
for (int i = 0; i < filesImagesname.Count; i++)
{
if (filesImagesname[i].EndsWith("sharpImage.png"))
{
continue;
}
Data.Image itemImage = new Data.Image(filesImagesname[i]);
analysis.addImageAnalysis(itemImage);
}
List <IMathematical> coreGoodPoint = analysis.getCore();
calculated = new Calculated();
calculated.createdBeginSolution();
for (int i = 0; i < filesImagesname.Count; i++)
{
if (filesImagesname[i].EndsWith("sharpImage.png"))
{
continue;
}
Data.Image itemImage = new Data.Image(filesImagesname[i]);
calculated.clarifySolution(itemImage, coreGoodPoint, goodPoint);
}
}
else
{
string nameCore = manager.GetPrivateString("SELECTION_CORE", "default_core");
IMathematical core = getMathematical(nameCore);
if (core == null)
{
core = new MathematicialSearchPoint1();
}
calculated = new Calculated(core);
calculated.createdBeginSolution();
for (int i = 0; i < filesImagesname.Count; i++)
{
if (filesImagesname[i].EndsWith("sharpImage.png"))
{
continue;
}
Data.Image itemImage = new Data.Image(filesImagesname[i]);
calculated.clarifySolution(itemImage, goodPoint);
}
}
Solution solution = calculated.getSolution();
timeForParsing.Stop();
timeTxt.WriteLine(nameFolder + " - " + timeForParsing.ElapsedMilliseconds + " timeForParsing");
preserveOBJ.saveOBJ(solution, setting, saveFolderCurrent);
preservePNG.savePNG(solution, saveFolderCurrent);
saveDat(solution.Map, saveFolderCurrent);
}
timeTxt.Close();
}
static void Main(string[] args)
{
IParser parser = new Parser();
ICalculated calculated = new Calculated(new MathematicialSearchPoint1());
IPreserveOBJ preserveOBJ = new PreserveOBJ();
IPreservePNG preservePNG = new PreservePNG();
IElimination elimination = new Elimination();
IAnalysis analysis;
Setting setting = null;
double delta = 0.0;
List <string> filesImagesname;
string pathFolder;
string pathConfig;
if (args.Length == 0)
{
Console.WriteLine("usage: Get3DModel.exe <path to folder>"); Environment.Exit(-1);
}
pathFolder = args[0];
filesImagesname = Directory.GetFiles(pathFolder, "*.png").ToList <string>();
if (args.Length > 1)
{
delta = Convert.ToDouble(args[1]);
}
pathConfig = Directory.GetFiles(pathFolder).ToList().First(
x => x.EndsWith(".camera"));
FileInfo fileInf = new FileInfo(pathConfig);
if (fileInf.Exists)
{
setting = new Setting(pathConfig);
Console.WriteLine("the verification of the optics configuration file completed successfully");
}
else
{
Console.WriteLine("the configuration file is not found");
Environment.Exit(-1);
}
Stopwatch timeForParsing = new Stopwatch();
for (int i = 0; i < filesImagesname.Count && i < 50; i++)
{
if (filesImagesname[i].EndsWith("sharpImage.png"))
{
continue;
}
timeForParsing.Restart();
Data.Image itemImage = new Data.Image(filesImagesname[i]);
elimination.calculateGradientImage(itemImage);
timeForParsing.Stop();
Console.WriteLine(
string.Format("elimination of the {0} has finished\n\telapsed time: {1} milliseconds",
filesImagesname[i], timeForParsing.ElapsedMilliseconds));
GC.Collect();
}
List <Data.Point> goodPoint = elimination.getSolution();
analysis = new Analysis(goodPoint);
for (int i = 0; i < filesImagesname.Count; i++)
// Parallel.For(0, filesImagesname.Count, i =>
{
if (filesImagesname[i].EndsWith("sharpImage.png"))
{
continue;
}
timeForParsing.Restart();
Data.Image itemImage = new Data.Image(filesImagesname[i]);
lock (analysis) analysis.addImageAnalysis(itemImage);
timeForParsing.Stop();
Console.WriteLine(
string.Format("analysing of the {0} has finished\n\telapsed time: {1} milliseconds",
filesImagesname[i], timeForParsing.ElapsedMilliseconds));
} //);
List <IMathematical> coreGoodPoint = analysis.getCore();
analysis = null;
elimination = null;
GC.Collect();
calculated.createdBeginSolution();
for (int i = 0; i < filesImagesname.Count; i++)
{
if (filesImagesname[i].EndsWith("sharpImage.png"))
{
continue;
}
timeForParsing.Restart();
Data.Image itemImage = new Data.Image(filesImagesname[i]);
calculated.clarifySolution(itemImage, coreGoodPoint, goodPoint);
timeForParsing.Stop();
Console.WriteLine(
string.Format("processing of the {0} has finished\n\telapsed time: {1} milliseconds",
filesImagesname[i], timeForParsing.ElapsedMilliseconds));
}
Solution solution = calculated.getSolution();
Console.WriteLine("saving data was started");
preserveOBJ.saveOBJ(solution, setting, pathFolder);
preservePNG.savePNG(solution, pathFolder);
}
