public FormManualTrain(Form1 frm1)
{
InitializeComponent();
browseImage = new OpenFileDialog();
_form1 = frm1;
eigenRecog = new Classifier_Train();
face = new HaarCascade("haarcascade_frontalface_default.xml");
eyeWithGlass = new CascadeClassifier("haarcascade_eye_tree_eyeglasses.xml");
mydb = new DBConn();
minEye = new Size(10, 10);
maxEye = new Size(225, 225);
font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.5d, 0.5d);
if (File.ReadAllText("setting.txt") != null)
{
folderPath = File.ReadAllText("setting.txt");
}
else
{
FolderBrowserDialog b = new FolderBrowserDialog();
b.Description = "Please select your installation path";
DialogResult r = b.ShowDialog();
if (r == DialogResult.OK) // Test result.
{
folderPath = b.SelectedPath;
Console.WriteLine(folderPath);
File.WriteAllText(@"setting.txt", folderPath);
MessageBox.Show("Path is at " + folderPath);
}
}
}
private bool LoadTrainingData()
{
mydb = new DBConn();
imagelabel = mydb.getLabelNumList().ToArray();
imageStringlabel = mydb.getLabelList().ToArray();
trainingImages = mydb.getTrainedImageList();
Itrainingimage = trainingImages;
if (mydb.getImageCount() > 0)
{
if (trainingImages.Length != 0)
{
f_recognize = new FisherFaceRecognizer(0, 123.0);
f_recognize.Train(Itrainingimage, imagelabel);
return true;
}
else
{
return false;
}
}
else
{
return false;
}
}
public FormManageData(Form1 frm1,Classifier_Train cls)
{
InitializeComponent();
db = new DBConn();
_form1 = frm1;
FillData();
eigenRecog = cls;
browseImage = new OpenFileDialog();
}
public TestRecog()
{
mydb = new DBConn();
totalImage = mydb.getImageCount();
trainImageArr = mydb.getTrainedImageList();
diffFaceList = new List<Image<Gray, byte>>();
AvgFace = getAVGface(trainImageArr);
diffFaceArr = getDiffFace();
}
public FormTrain(Form1 frm1)
{
InitializeComponent();
_form1 = frm1;
eigenRecog = new Classifier_Train();
face = new HaarCascade("haarcascade_frontalface_default.xml");
eyeWithGlass = new CascadeClassifier("haarcascade_eye_tree_eyeglasses.xml");
mydb = new DBConn();
minEye = new Size(10, 10);
maxEye = new Size(225, 225);
font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.5d, 0.5d);
captureT = new Capture();
Application.Idle += new EventHandler(runningCamera);
}
public FormLab()
{
InitializeComponent();
db = new DBConn();
}
private bool LoadTrainingData()
{
mydb = new DBConn();
allname = mydb.getLabelList();
trainingImages = mydb.getTrainedImageList();
int[] temp = Enumerable.Range(0,(allname.Count)).ToArray();
if (mydb.getImageCount() > 0)
{
if (trainingImages.Length != 0)
{
//set round and ...
//termCrit = new MCvTermCriteria(mydb.getImageCount(), 0.001);
//Eigen face recognizer
recognizer = new FisherFaceRecognizer(0,3200);//4000
recognizer.Train(trainingImages, temp);
return true;
}
else
{
return false;
}
}
else
{
return false;
}
}
public Form1()
{
InitializeComponent();
face = new HaarCascade("haarcascade_frontalface_default.xml");
eyeWithGlass = new CascadeClassifier("haarcascade_eye_tree_eyeglasses.xml");
mydb = new DBConn();
maxImageCount = (int)Math.Sqrt(mydb.getImageCount());
if (maxImageCount % 2 == 0)
{
maxImageCount--;
if(maxImageCount > 15){
maxImageCount = 15;
}
}
else
{
if (maxImageCount > 15)
{
maxImageCount = 15;
}
}
progressBar1.Maximum = maxImageCount;
recogNameResult = new List<string>();
recogDistanceResult = new List<double>();
minEye = new Size(10, 10);
maxEye = new Size(225, 225);
font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.4d, 0.4d);
fontbig = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.6d, 0.6d);
fontverybig = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.8d, 0.8d);
//log record
DateTime now = DateTime.Now;
logName = now.ToString();
logName = logName.Replace("/", "").Replace(":", "").Replace(" ", "");
label2.Text = "Idle";
if(File.Exists("setting.txt")){
folderPath = File.ReadAllText("setting.txt");
}
else
{
FolderBrowserDialog b = new FolderBrowserDialog();
b.Description = "Please select your installation path";
DialogResult r = b.ShowDialog();
if (r == DialogResult.OK) // Test result.
{
folderPath = b.SelectedPath;
Console.WriteLine(folderPath);
File.WriteAllText(@"setting.txt", folderPath);
MessageBox.Show("Path is at " + folderPath);
}
}
pL[0] = new Point(x0, y0);
pL[1] = new Point(x0, y1);
pL[2] = new Point(x1, y1);
pR[0] = new Point(x3, y0);
pR[1] = new Point(x3, y1);
pR[2] = new Point(x2, y1);
eigenRecog = new Classifier_Train();
}
private bool LoadTrainingData()
{
mydb = new DBConn();
allname = mydb.getAllImageID();
string[] allname_st = allname.Select(x => x.ToString()).ToArray();
trainingImages = mydb.getTrainedImageList();
//trainingImages = mydb.getRawTrainedImageList();
if (mydb.getImageCount() > 0)
{
if (trainingImages.Length != 0)
{
//set round and ...
//termCrit = new MCvTermCriteria(mydb.getImageCount(), 0.001);
termCrit = new MCvTermCriteria(5000, 0.0001);
//Eigen face recognizer
recognizer = new EigenObjectRecognizer(trainingImages, allname_st, maxRecognizeTreshold, ref termCrit);
return true;
}
else
{
return false;
}
}
else
{
return false;
}
}
public Form1()
{
InitializeComponent();
face = new HaarCascade("haarcascade_frontalface_default.xml");
calcface = new HaarCascade("haarcascade_frontalface_default.xml");
eyeWithGlass = new CascadeClassifier("haarcascade_eye_tree_eyeglasses.xml");
nose = new CascadeClassifier("haarcascade_mcs_nose.xml");
mouth = new CascadeClassifier("haarcascade_mcs_mouth.xml");
mydb = new DBConn();
recogNameResult = new List<string>();
recogDistanceResult = new List<double>();
minEye = new Size(10, 10);
maxEye = new Size(225, 225);
minNose = new Size(10, 10);
maxNose = new Size(225, 225);
minMouth = new Size(10, 10);
maxMouth = new Size(225, 225);
font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.5d, 0.5d);
//log record
DateTime now = DateTime.Now;
logName = now.ToString();
logName = logName.Replace("/", "").Replace(":", "").Replace(" ", "");
}