private void addAllImagesToDBToolStripMenuItem_Click(object sender, EventArgs e)
{
FBD = new FolderBrowserDialog();
if (FBD.ShowDialog() == DialogResult.OK)
{
DirectoryInfo myFolder = new DirectoryInfo(FBD.SelectedPath);
foreach (string filename in Directory.GetFiles(FBD.SelectedPath))
{
bitmap = new Bitmap(filename);
hog = new HistogramsOfOrientedGradients();
hog.ProcessImage(bitmap);
human = new Human();
if (filename.Contains("image_human"))
{
human.IsHuman = 1;
}
else
{
human.IsHuman = 0;
}
line = AuxiliaryFunctions.ToOneLine(hog.Histograms);
byteArray = AuxiliaryFunctions.DoubleArrayToByte(line);
human.HOG = byteArray;
humanModel = new HumanModel();
humanModel.Insert(human);
}
}
}
public static bool CompareHOG(double[, ][] hogHist)
{
double[, ][] hogHistogram = hogHist;
double[] line = AuxiliaryFunctions.ToOneLine(hogHistogram);
double percent = SVM.Probability(line);
bool isHuman = percent >= 0.5;
if (isHuman)
{
tuple.Add(Tuple.Create(Counter, percent, isHuman, cropRect));
}
return(isHuman);
}
private void addAllImagesToDBToolStripMenuItem_Click(object sender, EventArgs e)
{
humanList = new List <Human>();
if (FBD.ShowDialog() == DialogResult.OK)
{
DirectoryInfo myFolder = new DirectoryInfo(FBD.SelectedPath);
fileCount = Directory.GetFiles(FBD.SelectedPath).Count();
InitializeProgressBar();
foreach (string filename in Directory.GetFiles(FBD.SelectedPath))
{
bitmap = new Bitmap(filename);
hog = new HistogramsOfOrientedGradients();
hog.ProcessImage(bitmap);
human = new Human();
if (filename.Contains("image_human"))
{
human.IsHuman = 1;
}
else
{
human.IsHuman = -1;
}
line = AuxiliaryFunctions.ToOneLine(hog.Histograms);
byteArray = AuxiliaryFunctions.DoubleArrayToByte(line);
human.HOG = byteArray;
//XML file
humanList.Add(human);
index++;
if (index % (fileCount / 100) == 0)
{
progressValue++;
label1.Text = (progressValue + " %").ToString();
pb.Value = progressValue <= 100?progressValue:100;
Thread.Sleep(10);
}
}
if (!File.Exists("Database.xml"))
{
AuxiliaryFunctions.Serialize(humanList, "Database.xml");
}
else
{
humanList.AddRange(AuxiliaryFunctions.Deserialize <List <Human> >("Database.xml"));
AuxiliaryFunctions.Serialize(humanList, "Database.xml");
}
}
}
public static void AllPassesOfWindow(System.Drawing.Image src, int step)
{
tuple.Clear();
progressValue = 0;
Counter = 0;
Counter = 0;
int width = 64;
int height = 128;
while (width < src.Width && height < src.Height)
{
OnePassOfWindow(src, width, height, step);
width = (int)Math.Round(width * 1.5);
height = (int)Math.Round(height * 1.5);
}
tuple = tuple.OrderByDescending(x => x.Item2).ToList();
AuxiliaryFunctions.WritePercentage(tuple.ToArray(), @"Output\percentage.txt");
}
private void trainHumansToolStripMenuItem_Click_1(object sender, EventArgs e)
{
//XML file
humanList = new List <Human>();
humanList = AuxiliaryFunctions.Deserialize <List <Human> >("Database.xml");
trainArray = new double[humanList.Count][];
outputArray = new double[humanList.Count];
fileCount = humanList.Count;
InitializeProgressBar();
for (int i = 0; i < humanList.Count; i++)
{
trainArray[i] = AuxiliaryFunctions.ByteArrayToDouble(humanList[i].HOG);
outputArray[i] = humanList[i].IsHuman;
index++;
if (index % (fileCount / 100) == 0)
{
progressValue++;
label1.Text = (progressValue + " %").ToString();
pb.Value = progressValue <= 100 ? progressValue : 100;
Thread.Sleep(10);
}
}
//trainArray = humanList.Select(x => AuxiliaryFunctions.ByteArrayToDouble(x.HOG)).ToArray();
//outputArray = humanList.Select(x => (double)x.IsHuman).ToArray();
var teacher = new SequentialMinimalOptimization <Gaussian>()
{
UseComplexityHeuristic = true,
UseKernelEstimation = true
};
SupportVectorMachine <Gaussian> svm = teacher.Learn(trainArray, outputArray);
resultLine = svm.Weights;
AuxiliaryFunctions.WriteWeight(resultLine, "weight.txt");
AuxiliaryFunctions.MakeSerialization(svm, "SVM_G.xml");
}