private void okBtn_Click(object sender, EventArgs e)
{
Application.Idle -= new EventHandler(FrameGrabber);
grabber.Dispose();
RibbonForm1 form2 = new RibbonForm1();
this.Hide();
form2.ShowDialog();
this.Close();
}
private void tileItem1_ItemClick(object sender, DevExpress.XtraEditors.TileItemEventArgs e)
{
if (f1 == null)
{
f1 = new RibbonForm1(yonghu); //将主窗体对象传递过去
f1.yonghu = yonghu;
f1.Show(); //显示窗体二
}
else
{
f1.Activate();
f1 = null;
}
}
private void FrameGrabber(object sender, EventArgs e)
{
Users.Add("");
//Recheck at this point
currentFrame = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
gray = currentFrame.Convert <Gray, Byte>();
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
foreach (MCvAvgComp f in facesDetected[0])
{
result = currentFrame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
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);
//Validation = name;
//Draw the label for each face detected and recognized
currentFrame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.BlueViolet));
}
Users.Add("");
}
cameraBox.Image = currentFrame;
if (!string.IsNullOrWhiteSpace(name) && name == "Lac")
{
Application.Idle -= new EventHandler(FrameGrabber);
grabber.Dispose();
RibbonForm1 form2 = new RibbonForm1();
this.Hide();
form2.ShowDialog();
this.Close();
}
names = "";
Users.Clear();
}