private void face_add_Click(object sender, RoutedEventArgs e)
{
try
{
//Trained face counter
ContTrain = ContTrain + 1;
//Get a gray frame from capture device
gray = grabber.QueryGrayFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//Face Detector
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new System.Drawing.Size(20, 20));
//Action for each element detected
foreach (MCvAvgComp f in facesDetected[0])
{
TrainedFace = currentFrame.Copy(f.rect).Convert <Gray, byte>();
break;
}
//resize face detected image for force to compare the same size with the
//test image with cubic interpolation type method
TrainedFace = result.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
trainingImages.Add(TrainedFace);
labels.Add(person_name.Text);
//Show face added in gray scale
train_image.Source = ImageSourceForBitmap(TrainedFace.ToBitmap());
//Write the number of triained faces in a file text for further load
File.WriteAllText(AppDomain.CurrentDomain.BaseDirectory + "/TrainedFaces/TrainedLabels.txt", trainingImages.ToArray().Length.ToString() + "%");
//Write the labels of triained faces in a file text for further load
for (int i = 1; i < trainingImages.ToArray().Length + 1; i++)
{
trainingImages.ToArray()[i - 1].Save(AppDomain.CurrentDomain.BaseDirectory + "/TrainedFaces/face" + i + ".bmp");
File.AppendAllText(AppDomain.CurrentDomain.BaseDirectory + "/TrainedFaces/TrainedLabels.txt", labels.ToArray()[i - 1] + "%");
}
MessageBox.Show(person_name.Text + "´s face detected and added :)", "Training OK");
}
catch
{
MessageBox.Show("Enable the face detection first", "Training Fail");
}
}
public void addEmp()
{
string query = "INSERT INTO train(empcode, empname, date, imagee) VALUES (@empcode, @empname, @date, @imagee)";
SqlCommand cmd = new SqlCommand(query, connect);
ImageConverter converter = new ImageConverter();
byte[] imagepic = (byte[])converter.ConvertTo(TrainedFace.ToBitmap(), typeof(byte[]));
cmd.Parameters.AddWithValue("@empcode", txbEmpCode.Text);
cmd.Parameters.AddWithValue("@empname", txbEmpName.Text);
cmd.Parameters.AddWithValue("@date", toolStripStatusLabel1.Text);
cmd.Parameters.AddWithValue("@imagee", imagepic);
cmd.ExecuteNonQuery();
}
public AddStudent()
{
//loading haarcascade file by file name and assining to haarcascade variable
//Load haarcascades for face detection
face = new HaarCascade("haarcascade-frontalface-default.xml");
//Load haarcascades for eye detection
eyes = new HaarCascade("haarcascade_mcs_eyepair_big.xml");
//Load haarcascades for mouth detection
mouth = new HaarCascade("mouth.xml");
//Load haarcascades for nose detection
nose = new HaarCascade("nose.xml");
InitializeComponent();
try
{
//Previous trained faces and labels for each image
string Labelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedNames.txt");
string[] Labels = Labelsinfo.Split('%');
NumLabels = Convert.ToInt16(Labels[0]); //total number of faces detected
ContTrain = NumLabels; //new images will be added to the previous set
string LoadFaces;
string LoadEyes;
string LoadMouth;
string LoadNose;
for (int tf = 1; tf < NumLabels + 1; tf++)
{
LoadFaces = "face" + tf + ".bmp";
LoadEyes = "eyes" + tf + ".bmp";
LoadMouth = "mouth" + tf + ".bmp";
LoadNose = "nose" + tf + ".bmp";
TrainedFace.Add(new Image <Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadFaces));
TrainedEyes.Add(new Image <Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadEyes));
TrainedMouth.Add(new Image <Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadMouth));
TrainedNose.Add(new Image <Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadNose));
labels.Add(Labels[tf]);
}
}
catch (Exception e)
{
MessageBox.Show("Press okay to continue");
}
}
public string SaveString(string inputpath, string label, ref int index)
{
try
{
ContTrain = ContTrain + 1;
bool detected = false;
gray = new Image <Gray, byte>(inputpath);
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])
{
TrainedFace = gray.Copy(f.rect).Convert <Gray, byte>();
detected = true;
break;
}
if (!detected)
{
return(string.Empty);
}
TrainedFace = TrainedFace.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
TrainedFace = new Image <Gray, byte>(ImageProcessing.ImagePreProcessing(TrainedFace.ToBitmap()));
trainingImages.Add(TrainedFace);
labels.Add(label);
UpdateRecognizer();
return(BasicOperations.SaveImage(TrainedFace.ToBitmap(), ref index));;
}
catch
{
return(string.Empty);
}
}
private void btnVideoRecorder_Click(object sender, EventArgs e)
{
if (txbEmpCode.Text == "" || txbEmpName.Text == "")
{
MessageBox.Show("Null", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
else
{
try
{
faceRecProcess();
ImageConverter converter = new ImageConverter();
byte[] imagepic = (byte[])converter.ConvertTo(TrainedFace.ToBitmap(), typeof(byte[]));
connect.Open();
addEmp();
connect.Close();
totalclick++;
//btnVideoRecorder.Enabled = false;
txbEmpCode.Enabled = false;
txbEmpName.Enabled = false;
lbNotification.Text = "Successfully! *Name: " + txbEmpName.Text + " *Code: " + txbEmpCode.Text + " added " + totalclick.ToString() + "/5.";
if (totalclick == 5)
{
btnVideoRecorder.Enabled = false;
btnSave.Enabled = true;
videorecord = true;
}
}
catch
{
MessageBox.Show("Error");
}
}
}
private void btnFileImage_Click(object sender, EventArgs e)
{
OpenFileDialog openFileDialog = new OpenFileDialog();
//DialogResult dialogResult = openFileDialog.ShowDialog();
if (txbEmpName.Text == "" || txbEmpCode.Text == "" || statuscam == true)
{
MessageBox.Show("Null or Camera is running", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
else
{
if (openFileDialog.ShowDialog() == DialogResult.OK)
{
File.Copy(openFileDialog.FileName, Directory.GetCurrentDirectory() + "\\image\\" + openFileDialog.SafeFileName);
Image img = Image.FromFile(openFileDialog.FileName);
ImageBox ib = new ImageBox();
Bitmap masterImage = (Bitmap)img;
Image <Bgr, Byte> currentImage = new Image <Bgr, byte>(masterImage);
faceRecProcess();
ImageConverter converter = new ImageConverter();
byte[] imagepic = (byte[])converter.ConvertTo(TrainedFace.ToBitmap(), typeof(byte[]));
connect.Open();
addEmp();
connect.Close();
lbNotification.Text = "Successfully! *Name: " + txbEmpName.Text + " *Code: " + txbEmpCode.Text + " added!";
lbDailyCheck.Text = "";
txbEmpName.Text = "";
txbEmpCode.Text = "";
disPlayImage();
btnCorrection.Enabled = true;
}
}
}
private void SavePicture(object sender, EventArgs e)
{
try
{
TrainedFacesCounter++;
// Get a gray frame from capture device
Gray = Grabber.QueryGrayFrame().Resize(320, 240, INTER.CV_INTER_CUBIC);
// Face Detector
var scaleFactor = 1.2;
var minNeighbors = 10;
var detectionType = HAAR_DETECTION_TYPE.DO_CANNY_PRUNING;
MCvAvgComp[][] facesDetected = Gray.DetectHaarCascade(Face, scaleFactor, minNeighbors, detectionType, new Size(20, 20));
// Action for each element detected
foreach (MCvAvgComp f in facesDetected[0])
{
TrainedFace = CurrentFrame.Copy(f.rect).Convert <Gray, byte>();
break;
}
LogIt($"Handle frame - scaleFactor:{scaleFactor} minNeighbors:{minNeighbors} detectionType:{detectionType.ToString()}");
string labelName = textBox1.Text.Trim().Replace(" ", "_").ToLower();
// Resize face detected image in order to force to compare the same size with the
// Test image with cubic interpolation type method
TrainedFace = Result.Resize(100, 100, INTER.CV_INTER_CUBIC);
// Show face added in gray scale
imageBox1.Image = TrainedFace;
var imgPath = $"/TrainedFaces/{labelName}@face{DateTime.Now.ToString("yyyymmddhhmmssmm")}.bmp";
TrainedFace.Save(Application.StartupPath + imgPath);
}
catch { }
}
private void button1_Click(object sender, EventArgs e)
{
try
{
gray = grabber.QueryGrayFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//Face Detector
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
//Action for each element detected
foreach (MCvAvgComp f in facesDetected[0])
{
TrainedFace = currentFrame.Copy(f.rect).Convert <Gray, byte>();
break;
}
TrainedFace.Save(Application.StartupPath + "/face" + 1 + ".bmp");
if (SendIamge(Image.FromFile(Application.StartupPath + "/face" + 1 + ".bmp")))
{
File.Delete(Application.StartupPath + "/face" + 1 + ".bmp");
MessageBox.Show(UserLogin.Username + "´s face detected and added :)", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
else
{
MessageBox.Show("Some Thing Go Wrong Contact Support Now..", "Training Fail", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
catch
{
MessageBox.Show("Enable the face detection first", "Training Fail", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
private void btnCheckout_Click(object sender, EventArgs e)
{
offCorrection();
btnOneFace.Enabled = true;
btnVideoRecorder.Enabled = true;
btnFileImage.Enabled = true;
btnSave.Enabled = false;
txbEmpCode.Text = "";
txbEmpName.Text = "";
if (statuscam == true)
{
try
{
faceRecProcess();
ImageConverter converter = new ImageConverter();
byte[] imagepic = (byte[])converter.ConvertTo(TrainedFace.ToBitmap(), typeof(byte[]));
connect.Open();
string query = "INSERT INTO Employee(empcode, empname, checkout, imagee) VALUES (@empcode, @empname, @checkout, @imagee)";
SqlCommand cmd = new SqlCommand(query, connect);
cmd.Parameters.AddWithValue("@empcode", displayEmpCode.Text);
cmd.Parameters.AddWithValue("@empname", displayEmpName.Text);
cmd.Parameters.AddWithValue("@checkout", toolStripStatusLabel1.Text);
cmd.Parameters.AddWithValue("@imagee", imagepic);
cmd.ExecuteNonQuery();
SqlCommand nameCmd = new SqlCommand("SELECT TOP 1 empname FROM Employee ORDER BY ID DESC", connect);
SqlCommand codeCmd = new SqlCommand("SELECT TOP 1 empcode FROM Employee ORDER BY ID DESC", connect);
string empname = (string)nameCmd.ExecuteScalar();
string empcode = (string)codeCmd.ExecuteScalar();
connect.Close();
txbCorrectName.Text = empname.ToString();
txbCorrectCode.Text = empcode.ToString();
displayCheckin.Text = "Null";
displayCheckout.Text = toolStripStatusLabel1.ToString();
disPlayImage();
lbDailyCheck.Text = "Successfully! *Name: " + empname + " *Code: " + empcode + " checked out!";
lbNotification.Text = "";
}
catch
{
MessageBox.Show("Error for check out", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
else
{
try
{
byte[] imagepic = msImage.ToArray();
Image img = Image.FromStream(msImage);
Bitmap masterImage = (Bitmap)img;
Image <Gray, Byte> graypic = new Image <Gray, Byte>(masterImage);
trainingImages.Add(graypic);
labels.Add(displayEmpName.Text);
codes.Add(displayEmpCode.Text);
connect.Open();
string query = "INSERT INTO Employee(empcode, empname, checkout, imagee) VALUES (@empcode, @empname, @checkout, @imagee)";
SqlCommand cmd = new SqlCommand(query, connect);
cmd.Parameters.AddWithValue("@empcode", displayEmpCode.Text);
cmd.Parameters.AddWithValue("@empname", displayEmpName.Text);
cmd.Parameters.AddWithValue("@checkout", toolStripStatusLabel1.Text);
cmd.Parameters.AddWithValue("@imagee", imagepic);
cmd.ExecuteNonQuery();
SqlCommand nameCmd = new SqlCommand("SELECT TOP 1 empname FROM Employee ORDER BY ID DESC", connect);
SqlCommand codeCmd = new SqlCommand("SELECT TOP 1 empcode FROM Employee ORDER BY ID DESC", connect);
string empname = (string)nameCmd.ExecuteScalar();
string empcode = (string)codeCmd.ExecuteScalar();
connect.Close();
txbCorrectName.Text = empname.ToString();
txbCorrectCode.Text = empcode.ToString();
displayCheckin.Text = "Null";
displayCheckout.Text = toolStripStatusLabel1.ToString();
disPlayImage();
lbDailyCheck.Text = "Successfully! *Name: " + empname + " *Code: " + empcode + " checked out!";
lbNotification.Text = "";
}
catch
{
MessageBox.Show("Error for check out", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
}
private void btnBroweImg_Click(object sender, EventArgs e)
{
if (frmLogin.admin == false)
{
frmLogin loginForm = new frmLogin();
loginForm.Show();
return;
}
if (txtName.Text == "")
{
MessageBox.Show("Please enter name first.");
return;
}
openFileDialog1.FileName = String.Empty;
openFileDialog1.Filter = "JPEG Files (*.jpeg)|*.jpeg|PNG Files (*.png)|*.png|JPG Files (*.jpg)|*.jpg|GIF Files (*.gif)|*.gif";
openFileDialog1.Title = "Please select an image file to training.";
if (openFileDialog1.ShowDialog() == DialogResult.OK)
{
grabber = new Capture(openFileDialog1.FileName);
currentFrame = grabber.QueryFrame().Resize(473, 355, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//Trained face counter
ContTrain = ContTrain + 1;
//Get a gray frame from capture device
gray = currentFrame.Convert <Gray, Byte>();
//gray = grabber.QueryGrayFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//Face Detector
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
//Action for each element detected
foreach (MCvAvgComp f in facesDetected[0])
{
TrainedFace = currentFrame.Copy(f.rect).Convert <Gray, byte>();
break;
}
//resize face detected image for force to compare the same size with the
//test image with cubic interpolation type method
TrainedFace = TrainedFace.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
trainingImages.Add(TrainedFace);
labels.Add(txtName.Text + "|" + (ContTrain).ToString());
//Show face added in gray scale
imageBox1.Image = TrainedFace;
//Write the number of triained faces in a file text for further load
File.WriteAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", trainingImages.ToArray().Length.ToString() + "%");
//Write the labels of triained faces in a file text for further load
for (int i = 1; i < trainingImages.ToArray().Length + 1; i++)
{
trainingImages.ToArray()[i - 1].Save(Application.StartupPath + "/TrainedFaces/face" + i + ".bmp");
File.AppendAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", labels.ToArray()[i - 1] + "%");
}
MessageBox.Show(txtName.Text + "´s face detected and added :)", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information);
txtName.Text = "";
}
}
private void trainBtn_Click(object sender, EventArgs e)
{
try
{
//Trained face counter
ContTrain = ContTrain + 1;
//Get a gray frame from capture device
gray = grabber.QueryGrayFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//Face Detector
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
//Action for each element detected
foreach (MCvAvgComp f in facesDetected[0])
{
TrainedFace = currentFrame.Copy(f.rect).Convert <Gray, byte>();
break;
}
//resize face detected image for force to compare the same size with the
//test image with cubic interpolation type method
TrainedFace = result.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
trainingImages.Add(TrainedFace);
labels.Add(rollnoBox.Text);
//Show face added in gray scale
pictureBox2.Image = TrainedFace.ToBitmap();
//Write the number of triained faces in a file text for further load
File.WriteAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", trainingImages.ToArray().Length.ToString() + "%");
//Write the labels of triained faces in a file text for further load
for (int i = 1; i < trainingImages.ToArray().Length + 1; i++)
{
trainingImages.ToArray()[i - 1].Save(Application.StartupPath + "/TrainedFaces/face" + i + ".bmp");
File.AppendAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", labels.ToArray()[i - 1] + "%");
}
Student student = new Student(nameBox.Text, rollnoBox.Text);
foreach (var index in courseListBox.CheckedIndices)
{
ListNode <Course> temp = loadcourses.getHead();
for (int i = 0; temp != null; i++, temp = temp.next)
{
if (i == (int)index)
{
break;
}
}
student.studentcourses.Add(temp.val);
}
student_list.Add(student);
string studentfile = "student_file.bin";
//serialize
using (Stream stream = File.Open(studentfile, FileMode.Create))
{
var bformatter = new BinaryFormatter();
bformatter.Serialize(stream, student_list);
}
MessageBox.Show(nameBox.ToString() + "Student registered", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
catch (Exception exc)
{
MessageBox.Show("Failed To Register " + exc.Message, "Error", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
this.Hide();
Form1 form1 = new Form1();
form1.ShowDialog();
}
public bool CatchFace(string label, PictureBox pcb)
{
try
{
bool detected = false;
//Trained face counter
//Get a gray frame from capture device
gray = grabber.QueryGrayFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//Face Detector
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.2,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
//Action for each element detected
foreach (MCvAvgComp f in facesDetected[0])
{
TrainedFace = currentFrame.Copy(f.rect).Convert <Gray, byte>();
detected = true;
break;
}
if (!detected)
{
return(false);
}
//resize face detected image for force to compare the same size with the
//test image with cubic interpolation type method
TrainedFace = result.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
TrainedFace = new Image <Gray, byte>(ImageProcessing.ImagePreProcessing(TrainedFace.ToBitmap()));
//Show face added in gray scale
pcb.Image = TrainedFace.ToBitmap();
UpdateRecognizer();
MessageBox.Show(label + "´s face detected and added :)", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information);
return(true);
}
catch
{
MessageBox.Show("Enable the face detection first", "Training Fail", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
return(false);
}
}
