private void DetectFaces()
{
NamePersons.Add("");
Image <Gray, byte> grayframe = the_image_frame.Convert <Gray, byte>();
ImgCamera.Image = the_image_frame;
MCvAvgComp[][] facesDetected = grayframe.DetectHaarCascade(
face,
1.1,
2,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
lblTotalFacesDetected.Text = facesDetected[0].Length.ToString();
if (facesDetected[0].Length > 0)
{
foreach (MCvAvgComp f in facesDetected[0])
{
t = t + 1;
result = the_image_frame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
the_image_frame.Draw(f.rect, new Bgr(Color.Green), 3);
if (TrainingImages.ToArray().Length != 0)
{
MCvTermCriteria termCrit = new MCvTermCriteria(ContTrain, 0.01);
EigenFaceRecognizer recognizer = new EigenFaceRecognizer(
TrainingImages.ToArray(),
labels.ToArray(),
5000,
ref termCrit
);
name = recognizer.Recognize(result);
if (string.IsNullOrEmpty(name) == true)
{
name = "UNKNOWN";
}
the_image_frame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.Red));
}
//Now draw the rectangle on the detected image
NamePersons[t - 1] = name;
NamePersons.Add("");
}
lblTotalFacesDetected.Text = facesDetected[0].Length.ToString();
}
t = 0;
ImgTrainedFaces.Image = result;
for (int namelabel = 0; namelabel < facesDetected[0].Length; namelabel++)
{
names = names + NamePersons[namelabel] + ",";
}
string names_without_comma_at_the_end = names.Remove(names.Length - 1);
lblNamesExtracted.Text = names_without_comma_at_the_end;
names = "";
NamePersons.Clear();
}
private void DetectFaces()
{
NamePersons.Add("");
Image <Gray, byte> grayframe = ImageFrame.Convert <Gray, byte>();
MCvAvgComp[][] facesDetected = grayframe.DetectHaarCascade(
face,
1.2,
4,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
label3.Text = facesDetected[0].Length.ToString();
if (facesDetected[0].Length > 0)
{
foreach (MCvAvgComp f in facesDetected[0])
{
t = t + 1;
result = ImageFrame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
ImageFrame.Draw(f.rect, new Bgr(Color.Green), 3);
if (trainingImages.ToArray().Length != 0)
{
MCvTermCriteria termCrit = new MCvTermCriteria(ContTrain, 0.01);
EigenFaceRecognizer recognizer = new EigenFaceRecognizer(
trainingImages.ToArray(),
labels.ToArray(),
5000,
ref termCrit
);
name = recognizer.Recognize(result);
//Show recognized person's name
if (string.IsNullOrEmpty(name) == true)
{
name = "UNKNOWN";
}
ImageFrame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.Red));
}
NamePersons[t - 1] = name;
NamePersons.Add("");
}
}
label3.Text = facesDetected[0].Length.ToString();
NumberOfFacesDetected = facesDetected[0].Length;
t = 0;
for (int namelabel = 0; namelabel < facesDetected[0].Length; namelabel++)
{
names = names + NamePersons[namelabel] + ",";
}
if (is_in_grayscale == true)
{
Image <Gray, byte> displayed_image_in_grayscale = ImageFrame.Convert <Gray, byte>();
imageBoxFrameGrabber.Image = displayed_image_in_grayscale;
}
else if (is_in_grayscale == false)
{
imageBoxFrameGrabber.Image = ImageFrame;
}
else
{
}
string names_without_comma_at_the_end = names.Remove(names.Length - 1);
lblName.Text = names_without_comma_at_the_end;
names = "";
NamePersons.Clear();
}
void FrameGrabber(object sender, EventArgs e)
{
try
{
lblTotalFacesDetected.Text = "0";
No_Faces_Detected = 0;
NamePersons.Add("");
//Initialize grabber event
currentFrame = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
if (currentFrame != null)
{
//Obtain the captured frame in Bitmap
Bitmap ConvertedTobitmap = new Bitmap(grabber.QueryFrame().Bitmap);
//If the save menu strip item is being selected
if (saveToFileWithoutFaceRecognition)
{
//Save image frame in the desired location
SaveFileDialog save_Frame_Without_Face_Recognized = new SaveFileDialog();
save_Frame_Without_Face_Recognized.Filter = "Images|*.png;*.bmp;*.jpg";
ImageFormat format = ImageFormat.Png;
if (save_Frame_Without_Face_Recognized.ShowDialog() == System.Windows.Forms.DialogResult.OK)
{
string ext = System.IO.Path.GetExtension(save_Frame_Without_Face_Recognized.FileName);
switch (ext)
{
case ".jpg":
format = ImageFormat.Jpeg;
break;
case ".bmp":
format = ImageFormat.Bmp;
break;
}
ConvertedTobitmap.Save(save_Frame_Without_Face_Recognized.FileName, format);
}
saveToFileWithoutFaceRecognition = !saveToFileWithoutFaceRecognition;
}
else
{
}
if (enable_detection_and_recognition_of_faces == true)
{
gray = currentFrame.Convert <Gray, byte>();
//Face Detector
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
8,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
if (facesDetected[0].Length > 0)
{
foreach (MCvAvgComp f in facesDetected[0])
{
//If the face is found, increment t
t = t + 1;
currentFrame.Draw(f.rect, new Bgr(Color.Red), 2);
//Now see the result by copying the detected face in a frame name as result
result = currentFrame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//The face detected in channel 0 (grey) is drawn with a red rectangle of thickness 2
if (TrainingImages.ToArray().Length != 0)
{
//termcriteria against each image to find a match with it to perform different iterations
MCvTermCriteria termCrit = new MCvTermCriteria(ContTrain, 0.001);
//Call class by creating object and pass parameters
EigenFaceRecognizer recognizer = new EigenFaceRecognizer(
TrainingImages.ToArray(),
labels.ToArray(),
5000,
ref termCrit
);
//100 - needs to be in the same orientation but increasing it to 2000 or 3000 is otherwise
//Next step is to name find for recognized face
name = recognizer.Recognize(result);
if (string.IsNullOrEmpty(name) == true)
{
name = "UNKNOWN";
}
currentFrame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.LightGreen));
}
//Now draw the rectangle on the detected image
NamePersons[t - 1] = name;
NamePersons.Add("");
lblTotalFacesDetected.Text = facesDetected[0].Length.ToString();
ImgTrainedFaces.Image = result;
}
}
else if (facesDetected[0].Length == 0)
{
ImgTrainedFaces.Image = null;
}
else
{
}
t = 0;
ImgCamera.Image = currentFrame;
if (facesDetected[0].Length < 1)
{
lblNamesExtracted.Text = "";
names = "";
NamePersons.Clear();
}
else if (facesDetected[0].Length >= 1)
{
for (int namelabel = 0; namelabel < facesDetected[0].Length; namelabel++)
{
names = names + NamePersons[namelabel] + ",";
}
//Show the faces procesed and recognized
string names_without_comma_at_the_end = names.Remove(names.Length - 1);
lblNamesExtracted.Text = names_without_comma_at_the_end;
names = "";
//Clear the list(vector) of names
NamePersons.Clear();
}
}
else if (enable_detection_and_recognition_of_faces == false)
{
ImgCamera.Image = currentFrame;
}
else
{
}
}
}
catch (Exception)
{
}
}
void FrameGrabber(object sender, EventArgs e)
{
if (is_camera_on == true)
{
try
{
label3.Text = "0";
NumberOfFacesDetected = 0;
//=========We use NamePersons as a list of names since we do not know the size of NamePersons====//
NamePersons.Add("");
//Get the current frame form capture device
currentFrame = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
if (currentFrame != null)
{
//Convert the current frame captured to Grayscale
gray = currentFrame.Convert <Gray, Byte>();
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
8,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
MCvAvgComp[][] EyesDetected = gray.DetectHaarCascade(
eye,
1.2,
8,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
//=================If at least one face has been detected==================//
if (facesDetected[0].Length > 0)
{
//====================================================================//
foreach (MCvAvgComp f in facesDetected[0])
{
//Increase the number of training images by 1
t = t + 1;
if (detect_both_face_and_eyes == true)
{
foreach (MCvAvgComp ey in EyesDetected[0])
{
currentFrame.Draw(ey.rect, new Bgr(Color.Yellow), 2);
//Set the size of the empty box(Extracted face) which will later contain the extracted faces
}
}
else
{
}
currentFrame.Draw(f.rect, new Bgr(color_of_rectangle), 3);
//==============================================================
result = currentFrame.Copy(f.rect).Convert <Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//The face detected in channel 0 (grey) is drawn with a red rectangle of thickness 3
btnSubmitAttendance.Enabled = true;
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
EigenFaceRecognizer recognizer = new EigenFaceRecognizer(
trainingImages.ToArray(),
labels.ToArray(),
5000,
ref termCrit);
name = recognizer.Recognize(result);
if (string.IsNullOrEmpty(name) == true)
{
name = "UNKNOWN";
}
//Draw the label for each face detected and recognized
currentFrame.Draw(name, ref font, new Point(f.rect.X + 10, f.rect.Y - 2), new Bgr(color_of_name_above_recognized_face));
}
NamePersons[t - 1] = name;
NamePersons.Add("");
//Set the number of faces detected on the scene
}
}
label3.Text = facesDetected[0].Length.ToString();
NumberOfFacesDetected = facesDetected[0].Length;
t = 0;
if (name == "UNKNOWN")
{
btnSubmitAttendance.Enabled = false;
}
if (facesDetected[0].Length < 1)
{
names = "";
NamePersons.Clear();
lblName.Text = "";
}
else if (facesDetected[0].Length >= 1)
{
for (int namelabel = 0; namelabel < facesDetected[0].Length; namelabel++)
{
names = names + NamePersons[namelabel] + ",";
}
foreach (var en in NamePersons)
{
lblName.Text = en.ToString();
}
//Show the faces processed and recognized
string names_without_comma_at_the_end = names.Remove(names.Length - 1);
lblName.Text = names_without_comma_at_the_end;
names = "";
NamePersons.Clear();
}
else
{
}
if (is_in_grayscale == true)
{
Image <Gray, Byte> grayImage = currentFrame.Convert <Gray, Byte>();
imageBoxFrameGrabber.Image = grayImage;
}
else
{
imageBoxFrameGrabber.Image = currentFrame;
}
}
}
catch (Exception)
{
}
}
}
