protected void UploadButton_Click(object sender, EventArgs e)
{
try
{
if (!((FileUpload1.PostedFile.ContentType == "image/jpeg") ||
(FileUpload1.PostedFile.ContentType == "image/png") ||
(FileUpload1.PostedFile.ContentType == "image/gif") ||
(FileUpload1.PostedFile.ContentType == "image/bmp"))) throw new Exception("Неизвестный тип файла");
string PhotoFolder = Request.PhysicalApplicationPath + @"\photos\";
if (!Directory.Exists(PhotoFolder)) Directory.CreateDirectory(PhotoFolder);
string extention = Path.GetExtension(FileUpload1.FileName);
string uniqueName = Path.ChangeExtension(FileUpload1.FileName, DateTime.Now.Ticks.ToString());
string upFile = Path.Combine(PhotoFolder, uniqueName + extention);
FileUpload1.SaveAs(upFile);
//Распознование лиц
HaarCascade haarCascade = new HaarCascade(Request.PhysicalApplicationPath + @"\haarcascade_frontalface_alt2.xml");
Image<Bgr, Byte> image = new Image<Bgr, Byte>(upFile);
Image<Gray, Byte> grayImage = image.Convert<Gray, Byte>();
Bitmap srcImage = image.ToBitmap();
var detectedFaces = grayImage.DetectHaarCascade(haarCascade)[0];
foreach (var face in detectedFaces)
{
Image<Bgr, Byte> imFace = image.Copy(face.rect);
//Пикселизация (фактор подобран эмпирически)
//при данном факторе одиноково хорошо пикселизируются и большие и маленькие лица
double factor = 0.02 + (double)10 / (double)face.rect.Height;
imFace = imFace.Resize(factor, 0);
imFace = imFace.Resize(1 / factor, 0);
Bitmap faceBitmap = imFace.ToBitmap();
using (Graphics grD = Graphics.FromImage(srcImage))
{
grD.DrawImage(faceBitmap, new Point(face.rect.Left, face.rect.Top));
}
}
string uniqueName_processed = uniqueName + "_processed";
srcImage.Save(Path.Combine(PhotoFolder, uniqueName_processed + extention));
imgTitle.Visible = true;
Image1.ImageUrl = "photos/" + uniqueName_processed + extention;
}
catch (Exception ex)
{
Session["ErrorMsg"] = ex.Message;
Response.Redirect("~/error.aspx", true);
}
}
public EyesDetection(bool type)
{
this._image = null;
this._faces = new HaarCascade(@currentDirectory + @"\Resources\haarcascade_frontalface_alt2.xml");
this._eyes = new HaarCascade(@currentDirectory + @"\Resources\haarcascade_eye.xml");
}
private void frmCamShift_Load(object sender, EventArgs e)
{
cap = new Capture(0);
//haar = new HaarCascade("haarcascade_frontalface_alt.xml");
haar = new HaarCascade("haarcascade.xml");
cap.FlipHorizontal = true;
}
public static Image<Gray, byte> DetectAndTrimFace(int[] pixels, Size initialSize, Size outputSize, String haarcascadePath)
{
var inBitmap = ConvertToBitmap(pixels, initialSize.Width, initialSize.Width);
//for testing purposes I can the picture to a folder
//inBitmap.Save(@"E:\data\phototest\received.bmp");
var grayframe = new Image<Gray, byte>(inBitmap);
var haar = new HaarCascade(haarcascadePath);
var faces = haar.Detect(grayframe,
1.2,
3,
HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(30, 30));
if (faces.Count() != 1)
{
return null;
}
var face = faces[0];
var returnImage = grayframe.Copy(face.rect).Resize(outputSize.Width, outputSize.Height, INTER.CV_INTER_CUBIC);
//cleanup managed resources
haar.Dispose();
grayframe.Dispose();
return returnImage;
}
public MainForm()
{
InitializeComponent();
face = new HaarCascade("haarcascade_frontalface_default.xml");
// grabber = new Capture();
// grabber.QueryFrame();
// Application.Idle += new EventHandler(FrameGrabber);
this.WindowState = FormWindowState.Maximized;
_videoPacketDecoderWorker = new VideoPacketDecoderWorker(PixelFormat.BGR24, true, OnVideoPacketDecoded);
_videoPacketDecoderWorker.Start();
_droneClient = new DroneClient("192.168.1.1");
_droneClient.NavigationPacketAcquired += OnNavigationPacketAcquired;
_droneClient.VideoPacketAcquired += OnVideoPacketAcquired;
_droneClient.NavigationDataAcquired += data => _navigationData = data;
tmrStateUpdate.Enabled = true;
tmrVideoUpdate.Enabled = true;
_playerForms = new List<PlayerForm>();
_videoPacketDecoderWorker.UnhandledException += UnhandledException;
_droneClient.Start();
}
private void Window_Loaded(object sender, RoutedEventArgs e)
{
var sourceImage = new Bitmap("C:\\Steve_Wozniak.jpg");
string haarcascade = "haarcascade_frontalface_default.xml";
using (HaarCascade face = new HaarCascade(haarcascade))
{
var image = new Image<Rgb, Byte>(sourceImage);
using (var gray = image.Convert<Gray, Byte>())
{
var detectedFaces = face.Detect(
gray,
1.1,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new System.Drawing.Size(20, 20));
var firstFace = detectedFaces[0];
System.Drawing.Bitmap bmpImage = image.Bitmap;
System.Drawing.Bitmap bmpCrop = bmpImage.Clone(firstFace.rect,
bmpImage.PixelFormat);
var cropedImage = new Image<Rgb, Byte>(bmpCrop);
MainImage.Source = ToBitmapSource(sourceImage);
DetectedFaceImage.Source = ToBitmapSource(cropedImage.Bitmap);
}
}
}
public static Image<Bgr, byte> DetectAndDrawFaces(Image<Bgr, byte> image, HaarCascade face, HaarCascade eye)
{
Image<Gray, Byte> gray = image.Convert<Gray, Byte>(); //Convert it to Grayscale
gray._EqualizeHist();
//Detect the faces from the gray scale image and store the locations as rectangle
//The first dimensional is the channel
//The second dimension is the index of the rectangle in the specific channel
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(
face,
1.1,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
foreach (MCvAvgComp f in facesDetected[0])
{
//draw the face detected in the 0th (gray) channel with blue color
image.Draw(f.rect, new Bgr(Color.Blue), 2);
//Set the region of interest on the faces
if (eye != null)
DetectAndDrawEyes(image, gray, f, eye);
}
return image;
}
public Image<Bgr, Byte> FaceDetection(Image Image)
{
face = new HaarCascade("haarcascade_frontalface_default.xml");
Utility UTl = new Utility();
//Get the current frame form capture device
Image<Bgr, Byte> currentFrame = UTl.ImageToBgrByte(Image);
//Convert it to 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));
//Action for element detected
try
{
MCvAvgComp f = facesDetected[0][0];
result = currentFrame.Copy(f.rect).Convert<Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);
//draw the face detected in the 0th (gray) channel with blue color
currentFrame.Draw(f.rect, new Bgr(Color.White), 2);
}
catch (Exception ex)
{
MessageBox.Show("Camera Error: Empty frames arrived" + ex.Message.ToString(), "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
return currentFrame;
}
private void Form1_Load(object sender, EventArgs e)
{
capturar = new Capture(0);
haarCascade1 = new HaarCascade("haarcascade_frontalface_default.xml");
timer1.Interval = 40;
timer1.Enabled=true;
}
public Form1()
{
InitializeComponent();
face = new HaarCascade("haarcascade_frontalface_default.xml");
calcface = new HaarCascade("haarcascade_frontalface_default.xml");
eyeWithGlass = new CascadeClassifier("haarcascade_eye_tree_eyeglasses.xml");
nose = new CascadeClassifier("haarcascade_mcs_nose.xml");
mouth = new CascadeClassifier("haarcascade_mcs_mouth.xml");
mydb = new DBConn();
recogNameResult = new List<string>();
recogDistanceResult = new List<double>();
minEye = new Size(10, 10);
maxEye = new Size(225, 225);
minNose = new Size(10, 10);
maxNose = new Size(225, 225);
minMouth = new Size(10, 10);
maxMouth = new Size(225, 225);
font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.5d, 0.5d);
//log record
DateTime now = DateTime.Now;
logName = now.ToString();
logName = logName.Replace("/", "").Replace(":", "").Replace(" ", "");
}
public void ProcessFaces()
{
this._stopwatch.Reset();
this._stopwatch.Start();
// get the current frame from our webcam
Image<Bgr, Byte> frame = _capture.QueryFrame();
Image<Gray, Byte> gray;
//Read the HaarCascade objects
using (HaarCascade face = new HaarCascade(FACEFILENAME)) {
//Convert it to Grayscale
gray = frame.Convert<Gray, Byte>();
//normalizes brightness and increases contrast of the image
gray._EqualizeHist();
//Detect the faces from the gray scale image and store the locations as rectangle
//The first dimensional is the channel
//The second dimension is the index of the rectangle in the specific channel
MCvAvgComp[] facesDetected = face.Detect(
gray,
1.1,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new System.Drawing.Size(20, 20));
if (facesDetected != null && facesDetected.Length > 0) {
this.notifyIcon.ShowBalloonTip(5000, "Alert!", "Shoulder surfer detected!",ToolTipIcon.Warning);
Console.WriteLine("Shoulder surfer detected!");
}
}
this._stopwatch.Stop();
Console.WriteLine("Elapsed {0}s", this._stopwatch.Elapsed.TotalSeconds);
}
public App(Boolean cameraTurn)
{
InitializeComponent();
images = slider.Images();
pictureBox2.Image = images[0];
if (!cameraTurn)
{
cameraState = false;
pictureBox1.Hide();
}
else
{
pictureBox2.Hide();
}
timer = new DispatcherTimer();
timer.Tick += new EventHandler(timer1_Tick);
timer.Interval = new TimeSpan(0, 0, 0, 0, 1);
timer.Start();
timer2.Interval = 1000;
timer2.Start();
//picturebox jest rozciągany na cały screen
pictureBox1.Dock = DockStyle.Fill;
// a następnie zawartosc jest rozciagana na całego pictureboxa
fullScreen.EnterFullScreen(this);
//pictureBox1.Hide();
capture = new Capture();
haarCascade = new HaarCascade(@"haarcascade_frontalface_alt_tree.xml");
}
public FrmPrincipal()
{
InitializeComponent();
//Proses mendekteksi wajah
face = new HaarCascade("haarcascade_frontalface_default.xml");
try
{
//Prose label untuk setiap gambar
string Labelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt");
string[] Labels = Labelsinfo.Split('%');
NumLabels = Convert.ToInt16(Labels[0]);
ContTrain = NumLabels;
string LoadFaces;
for (int tf = 1; tf < NumLabels+1; tf++)
{
LoadFaces = "face" + tf + ".bmp";
trainingImages.Add(new Image<Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadFaces));
labels.Add(Labels[tf]);
}
}
catch(Exception e)
{
MessageBox.Show(" Database Masih Kosong !!! ", "Maaf", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
public FormManualTrain(Form1 frm1)
{
InitializeComponent();
browseImage = new OpenFileDialog();
_form1 = frm1;
eigenRecog = new Classifier_Train();
face = new HaarCascade("haarcascade_frontalface_default.xml");
eyeWithGlass = new CascadeClassifier("haarcascade_eye_tree_eyeglasses.xml");
mydb = new DBConn();
minEye = new Size(10, 10);
maxEye = new Size(225, 225);
font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.5d, 0.5d);
if (File.ReadAllText("setting.txt") != null)
{
folderPath = File.ReadAllText("setting.txt");
}
else
{
FolderBrowserDialog b = new FolderBrowserDialog();
b.Description = "Please select your installation path";
DialogResult r = b.ShowDialog();
if (r == DialogResult.OK) // Test result.
{
folderPath = b.SelectedPath;
Console.WriteLine(folderPath);
File.WriteAllText(@"setting.txt", folderPath);
MessageBox.Show("Path is at " + folderPath);
}
}
}
public Admin()
{
InitializeComponent();
face = new HaarCascade("haarcascade_frontalface_default.xml");
Loaded += (s, e) =>
{
this.DataContext = CommonData.PicturesVM;
if (grabber == null)
{
CommonData.LoadSavedData();
//check how many faces we already have
_countFaces = CommonData.PicturesVM.Pictures.Count;
grabber = new Capture();
grabber.QueryFrame();
grabber.Start();
}
else
{
grabber.Start();
}
};
Unloaded += (s, e) =>
{
grabber.Stop();
};
CompositionTarget.Rendering += CompositionTarget_Rendering;
}
private Bitmap DetectFace(Bitmap faceImage)
{
var image = new Image<Bgr, byte>(faceImage);
var gray = image.Convert<Gray, Byte>();
var haarCascadeFilePath = _httpContext.Server.MapPath("haarcascade_frontalface_default.xml");
var face = new HaarCascade(haarCascadeFilePath);
MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(face, 1.1, 10, HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
Image<Gray, byte> result = null;
foreach (MCvAvgComp f in facesDetected[0])
{
//draw the face detected in the 0th (gray) channel with blue color
image.Draw(f.rect, new Bgr(Color.Blue), 2);
result = image.Copy(f.rect).Convert<Gray, byte>();
break;
}
if (result != null)
{
result = result.Resize(150, 150, INTER.CV_INTER_CUBIC);
return result.Bitmap;
}
return null;
}
public FrmPrincipal()
{
InitializeComponent();
//Load haarcascades for face detection
face = new HaarCascade("haarcascade_frontalface_default.xml");
//eye = new HaarCascade("haarcascade_eye.xml");
try
{
//Load of previus trainned faces and labels for each image
string Labelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt");
string[] Labels = Labelsinfo.Split('%');
NumLabels = Convert.ToInt16(Labels[0]);
ContTrain = NumLabels;
string LoadFaces;
for (int tf = 1; tf < NumLabels + 1; tf++)
{
LoadFaces = "face" + tf + ".bmp";
trainingImages.Add(new Image<Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadFaces));
labels.Add(Labels[tf]);
}
}
catch (Exception e)
{
//MessageBox.Show(e.ToString());
MessageBox.Show("Nothing in binary database, please add at least a face(Simply train the prototype with the Add Face Button).", "Triained faces load", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
public FrmPrincipal()
{
InitializeComponent();
//Load haarcascades for face detection
face = new HaarCascade("haarcascade_frontalface_default.xml");
try
{
//Load of previus trainned faces and labels for each image
var Labelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt");
var Labels = Labelsinfo.Split('%');
NumLabels = Convert.ToInt16(Labels[0]);
ContTrain = NumLabels;
string LoadFaces;
for (var tf = 1; tf < NumLabels + 1; tf++)
{
LoadFaces = "face" + tf + ".bmp";
trainingImages.Add(new Image<Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadFaces));
labels.Add(Labels[tf]);
}
}
catch (Exception)
{
//MessageBox.Show(e.ToString());
MessageBox.Show(@"Nu este nimic in baza de data, adauga cel putin o fata.", @"Triained faces load",
MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
public DaftarPeg()
{
InitializeComponent();
face = new HaarCascade("haarcascade_frontalface_default.xml");
eye = new HaarCascade("haarcascade_eye.xml");
try
{
//Load of previus trainned faces and labels for each image
string Labelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces2/TrainedLabelsAll.txt");
string[] Labels = Labelsinfo.Split('%');
NumLabels = Convert.ToInt16(Labels[0]);
ContTrain = NumLabels;
string LoadFaces;
for (int tf = 1; tf < NumLabels + 1; tf++)
{
LoadFaces = "face_1" + tf + ".bmp";
trainingImages.Add(new Image<Gray, byte>(Application.StartupPath + "/TrainedFaces2/" + LoadFaces));
labels.Add(Labels[tf]);
}
}
catch (Exception e)
{
MessageBox.Show(e.ToString());
//MessageBox.Show("Persiapan untuk memasukkan Data Wajah " + NIP_Enroll + ".", "Load Face Training", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
}
}
public Form1()
{
InitializeComponent();
face = new HaarCascade("haarcascade_frontalface_default.xml");
this.MouseWheel+=(a,b)=>{
if(textBox1.Focused)
{
double d = double.Parse(textBox1.Text);
d += b.Delta>0?0.01:-0.01;
textBox1.Text = d.ToString();
}
if (textBox2.Focused)
{
int d = int.Parse(textBox2.Text);
d += b.Delta > 0 ? 1 : -1;
textBox2.Text = d.ToString();
}
if (textBox3.Focused)
{
int d = int.Parse(textBox3.Text);
d += b.Delta > 0 ? 10 : -10;
textBox3.Text = d.ToString();
}
};
}
public Form1()
{
InitializeComponent();
//Cargar la detección de Rostros Metodo de Viola-Jones
face = new HaarCascade("haarcascade_frontalface_default.xml");
eye = new HaarCascade("haarcascade_eye.xml");
}
private void btnBrowseHAAR_Click(object sender, EventArgs e)
{
DialogResult result = openFileDialog1.ShowDialog();
if (result != DialogResult.OK) return;
txtCascadeFile.Text = openFileDialog1.FileName;
face = new HaarCascade(txtCascadeFile.Text);
}
public FaceDetection()
{
this._image = null;
this._gray = null;
this._egray = null;
this._processedImages = null;
this._faces = new HaarCascade(@currentDirectory + @"\Resources\haarcascade_frontalface_alt_tree.xml");
}
//indicates whether frame grabbing from the cameras has been successfull
//private bool sucessfull;
public LiveStreamFaceDetectingThread(Size frame_size)
: base()
{
haarcascade = new HaarCascade(FRONTAL_FACE_HAARCASCADE_FILE_PATH);
this.frame_width = frame_size.Width;
this.frame_height = frame_size.Height;
WORK_DONE = false;
}
private void Form1_Load(object sender, EventArgs e)
{
// passing 0 gets zeroth webcam
_cap = new Capture(0);
// adjust path to find your xml
_haar = new HaarCascade(
"haarcascade_frontalface_alt2.xml");
}
private void FrmPrincipal_Load(object sender, EventArgs e)
{
//Encender la camara
capturar = new Capture(0);
timer1.Interval = 40;
timer1.Enabled = true;
haar = new HaarCascade("haarcascade_frontalface_default.xml");
}
public FaceTrackingInstance(ImageRGB image, HaarCascade cascade)
{
FSource = image;
FHaarCascade = cascade;
FTrackingThread = new Thread(fnFindFacesThread);
FTrackingThread.Start();
IsRunning = true;
}
private void Window_Loaded(object sender, RoutedEventArgs e)
{
capture = new Capture();
haarCascade = new HaarCascade(@"haarcascade_frontalface_alt_tree.xml");
timer = new DispatcherTimer();
timer.Tick += new EventHandler(timer_Tick);
timer.Interval = new TimeSpan(0, 0, 0, 0, 1);
timer.Start();
}
public ReviewFaceDetectingThread(Size frame_size)
: base()
{
haarcascade = new HaarCascade(FRONTAL_FACE_HAARCASCADE_FILE_PATH);
its_time_to_pick_perpetrator_faces = false;
this.frame_size = frame_size;
WORK_DONE = false;
counter = 0;
previous_id = 0;
}
protected virtual MCvAvgComp[] GetFacesVector(Image<Gray, byte> grayImage)
{
var haarCascade = new HaarCascade(this.HaarCascadePath);
return haarCascade.Detect(grayImage,
this.ScanFactor, //the image where the object are to be detected from
this.Neighbours, //factor by witch the window is scaled in subsequent scans
HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, //min number of neighbour rectangles
Size.Empty,
Size.Empty);
}
public FrmFaceDetection()
{
try
{
InitializeComponent();
webcamVideo = new Capture();
//faceDetection = new HaarCascade(Application.StartupPath + "\\haarcascade_frontalface_default.xml");
faceDetection = new Emgu.CV.HaarCascade("haarcascade_frontalface_default.xml");
cascade = new FaceHaarCascade();
}
catch (Exception er)
{
MessageBox.Show(er.Message, "Face Detection and Recognition Failure", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
public static EmguCVFaceDetector Get(Bitmap image, string full_name_of_xml)
{
Image <Bgr, Byte> image1 = new Image <Bgr, Byte>(image);
Image <Gray, Byte> grayImage = image1.Convert <Gray, Byte>();
Emgu.CV.HaarCascade faceCascade;
if (full_name_of_xml == "\0")
{
faceCascade = new Emgu.CV.HaarCascade("haarcascade_frontalface_alt.xml");
}
else
{
faceCascade = new Emgu.CV.HaarCascade(full_name_of_xml);
}
return(new EmguCVFaceDetector(grayImage, image1, faceCascade));
}
public EmguCVFaceDetector(Image <Gray, Byte> grayimage1, Image <Bgr, Byte> image1, Emgu.CV.HaarCascade faceCascade1)
{
grayimage = grayimage1;
image = image1;
faceCascade = faceCascade1;
}