private void button3_Click(object sender, EventArgs e)
{
this.Hide();
Painel painel = new Painel();
painel.label3.Text = nivellbl.Text;
painel.label4.Text = nomelbl.Text;
painel.Closed += (s, args) => this.Close();
painel.Show();
}
void FrameGrabber(object sender, EventArgs e)
{
label3.Text = "0";
//label4.Text = "";
NamePersons.Add("");
//Pega o frame para captura
currentFrame = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//Converte em Grayscale
gray = currentFrame.Convert <Gray, Byte>();
//Face Detector
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
//Ação para cada elemnto detectado
foreach (MCvAvgComp f in facesDetected[0])
{
t = t + 1;
result = currentFrame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//Desenha o quadrado na cara
currentFrame.Draw(f.rect, new Bgr(Color.Red), 2);
if (trainingImages.ToArray().Length != 0)
{
//TermCriteria for face recognition with numbers of trained images like maxIteration
MCvTermCriteria termCrit = new MCvTermCriteria(ContTrain, 0.001);
//Eigen face recognizer
EigenObjectRecognizer recognizer = new EigenObjectRecognizer(
trainingImages.ToArray(),
labels.ToArray(),
3000,
ref termCrit);
name = recognizer.Recognize(result);
//Escreve o nome para cada face
currentFrame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.LightGreen));
}
NamePersons[t - 1] = name;
NamePersons.Add("");
//Seta o numero de faces detectadas
label3.Text = facesDetected[0].Length.ToString();
/*
*
* //Le a quantidade de pessoas e atribui a variavel pessoas
* string Pessoas = facesDetected[0].Length.ToString();
* if (Pessoas != "0")
* {
* Application.Idle -= FrameGrabber;
* grabber.Dispose();
* this.Hide();
* Painel painel = new Painel();
* painel.label4.Text = names;
* painel.Closed += (s, args) => this.Close();
* painel.Show();
* }
*
* //Set the region of interest on the faces
*
* gray.ROI = f.rect;
* MCvAvgComp[][] eyesDetected = gray.DetectHaarCascade(
* eye,
* 1.1,
* 10,
* Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
* new Size(20, 20));
* gray.ROI = Rectangle.Empty;
*
* foreach (MCvAvgComp ey in eyesDetected[0])
* {
* Rectangle eyeRect = ey.rect;
* eyeRect.Offset(f.rect.X, f.rect.Y);
* currentFrame.Draw(eyeRect, new Bgr(Color.Blue), 2);
* }
*/
}
t = 0;
//Concatena o nome das pessoas
for (int nnn = 0; nnn < facesDetected[0].Length; nnn++)
{
names = names + NamePersons[nnn];
}
//Le a quantidade de pessoas e atribui a variavel pessoas
string Pessoas = facesDetected[0].Length.ToString();
if (Pessoas != "0")
{
Application.Idle -= FrameGrabber;
grabber.Dispose();
this.Hide();
Painel painel = new Painel();
//Faz a separação do nome pro nivel
char[] Separador = { '|' };
string NomeENivel = names;
string[] split = NomeENivel.Split(Separador, StringSplitOptions.None);
painel.label4.Text = split[0];
painel.label3.Text = split[1];
painel.Closed += (s, args) => this.Close();
painel.Show();
}
//Show the faces procesed and recognized
imageBoxFrameGrabber.Image = currentFrame;
label4.Text = names;
names = "";
//Clear the list(vector) of names
NamePersons.Clear();
}
