/// <summary>
/// for singleton purpose
/// </summary>
/// <returns></returns>
public static DBConnecttion getInstance()
{
if (instance == null)
{
instance = new DBConnecttion();
}
return(instance);
}
/// <summary>
/// button event to person in database
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void button1_Click_1(object sender, EventArgs e)
{
if (!(IsEmptyOrWhiteSpace(textBoxName.Text)))
{
if (!(IsEmptyOrWhiteSpace(textBoxPersonName.Text)))
{
if (!(IsEmptyOrWhiteSpace(textBoxAge.Text)))
{
try
{
if (Utilities.checkUserName(textBoxName.Text) && !(labels.Contains(textBoxName.Text)))
{
Bitmap masterImage = (Bitmap)pictureBox1.Image;
Image <Gray, Byte> normalizedMasterImage = new Image <Gray, Byte>(masterImage);
trainingImages.Add(normalizedMasterImage);
labels.Add(textBoxName.Text);
for (int i = 1; i < trainingImages.ToArray().Length + 1; i++)
{
trainingImages.ToArray()[i - 1].Save(Application.StartupPath + "/Faces/" + textBoxName.Text + ".bmp"); //saving greyscaled face image as trained data
}
File.AppendAllText(Application.StartupPath + "/Faces/Faces.txt", textBoxName.Text + ","); //writing person username to database file
DBConnecttion.getInstance().createPerson(textBoxName.Text, textBoxPersonName.Text, textBoxAge.Text, "xc"); //inserting remaining person info in sqlite database
textBoxAge.Text = "";
textBoxName.Text = "";
textBoxPersonName.Text = "";
MessageBox.Show("Person Added to Database!");
}
else
{
MessageBox.Show("Warning : Username only contain alphanumeric characters and must not be already regsitered!");
}
}
catch (Exception exp)
{
MessageBox.Show("Warning : Detect face first!");
}
}
else
{
MessageBox.Show("Age must be filled!");
}
}
else
{
MessageBox.Show("Name must be filled");
}
}
else
{
MessageBox.Show("Username must be filled");
}
}
/// <summary>
/// button event to delete all data from sqllite database and terminate the application
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void button1_Click(object sender, EventArgs e)
{
DBConnecttion.getInstance().deleteAll();
System.IO.DirectoryInfo di = new DirectoryInfo(Application.StartupPath + "/Faces");
foreach (FileInfo file in di.GetFiles())
{
file.Delete();
}
foreach (DirectoryInfo dir in di.GetDirectories())
{
dir.Delete(true);
}
Application.Exit();
}
/// <summary>
/// Constructor of this form
/// </summary>
public Form1()
{
InitializeComponent();
DBConnecttion.getInstance().openConnection(); //Establising connection with sqllite database
/*
*
* these are haarcascades for detecting face,eyes,nose,mouth.
* comment out with features you don't want to detect.
* if you comment from here you also have to comment related code from "FrameProcedure" function
*
*/
faceDetected = new HaarCascade("haar/haarcascade_frontalface_default.xml"); //HaarCascade is to detect face
eyesDetected = new HaarCascade("haar/eye.xml"); //HaarCascade is to detect eyes
//noseDetected = new HaarCascade("haar/nose.xml"); //HaarCascade is to detect eyes
// mouthDetected = new HaarCascade("haar/mouth.xml"); //HaarCascade is to detect eyes
try
{
//importing trained data from db file and adding to runtime list
string Labelsinf = File.ReadAllText(Application.StartupPath + "/Faces/Faces.txt");
List <string> Labels = Labelsinf.Split(',').Distinct().ToList <string>();
Numlabels = Labels.Count();
Count = Numlabels;
string FacesLoad;
foreach (string i in Labels)
{
trainingImages.Add(new Image <Gray, byte>(Application.StartupPath + $"/Faces/{i}.bmp"));
labels.Add(i);
}
}catch (Exception e)
{
}
}
/// <summary>
/// Functon to process captured frame and detection of face and also recognizing
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void FrameProcedure(object sender, EventArgs e)
{
try
{
Users.Add("");
Frame = camera.QueryFrame().Resize(480, 360, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
grayFace = Frame.Convert <Gray, byte>();
/*
* Face and face feactures detection data, if you don't want to detect of face feacture comment the line.
* this portion is releted to Haarcascade
*/
MCvAvgComp[][] facesDetectedNow = grayFace.DetectHaarCascade(faceDetected, 1.2, 10, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(10, 10));
//MCvAvgComp[][] eyesDetectedNow = grayFace.DetectHaarCascade(eyesDetected, 1.2, 10, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(5, 5));
//MCvAvgComp[][] noseDetectedNow = grayFace.DetectHaarCascade(noseDetected, 1.2, 10, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(5, 5));
//MCvAvgComp[][] mouthDetectedNow = grayFace.DetectHaarCascade(mouthDetected, 1.2, 10, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(5, 5));
foreach (MCvAvgComp f in facesDetectedNow[0])
{
result = Frame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
Frame.Draw(f.rect, new Bgr(Color.DarkViolet), 2);
if (trainingImages.ToArray().Length != 0)
{
MCvTermCriteria termCriteries = new MCvTermCriteria(Count, 0.001);
EigenObjectRecognizer recognizer = new EigenObjectRecognizer(trainingImages.ToArray(), labels.ToArray(), 1500, ref termCriteries);
name = recognizer.Recognize(result);
Frame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.Green)); //drawing box around the detect face
if (name != "")
{
if (monitorMode)
{
imageBoxFaceDetected.Image = new Image <Gray, byte>(Application.StartupPath + $"/Faces/{name}.bmp");
Person person = DBConnecttion.getInstance().personInfo(name);
labelName.Text = person.Name;
labelUserName.Text = name;
labelAge.Text = person.Age;
}
}
}
Users.Add("");
/*
* foreach(MCvAvgComp j in eyesDetectedNow[0])
* {
*
* Frame.Draw(j.rect, new Bgr(Color.Red), 2);
*
* }
*/
/*
*
* foreach (MCvAvgComp j in noseDetectedNow[0])
* {
*
* Frame.Draw(j.rect, new Bgr(Color.Red), 2);
*
* }
*/
/*
* foreach (MCvAvgComp j in mouthDetectedNow[0])
* {
* Frame.Draw(j.rect, new Bgr(Color.Red), 2);
*
* }
*/
}
liveCameraView.Image = Frame;
names = "";
Users.Clear();
}
catch (Exception ex)
{
//MessageBox.Show(ex.Message);
}
}
