/// <summary>
/// Called when MainForm loads.
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void MainForm_Load(object sender, EventArgs e)
{
// activate the camera
SetCamera();
// set up a haar object detector to find the face
var faceCascade = new Accord.Vision.Detection.Cascades.FaceHaarCascade();
faceDetector = new HaarObjectDetector(faceCascade);
faceDetector.MinSize = new Size(150, 150);
faceDetector.ScalingFactor = 1.03f;
faceDetector.SearchMode = ObjectDetectorSearchMode.Single;
faceDetector.ScalingMode = ObjectDetectorScalingMode.SmallerToGreater;
// set up a new haar object detector to find the nose
var noseCascade = new Accord.Vision.Detection.Cascades.NoseHaarCascade();
noseDetector = new HaarObjectDetector(noseCascade);
noseDetector.SearchMode = ObjectDetectorSearchMode.Single;
noseDetector.ScalingMode = ObjectDetectorScalingMode.SmallerToGreater;
// load the mustache
mustache = Bitmap.FromFile(@"./mustache.png") as Bitmap;
// start the player
videoPlayer.Start();
}
private void faceDetect(ushort j)
{
cvsbmp = UtilFn.BitmapImage2Bitmap(images[j]);
var cascade = new Accord.Vision.Detection.Cascades.FaceHaarCascade();
var detector = new Accord.Vision.Detection.HaarObjectDetector(cascade, minSize: 50,
searchMode: Accord.Vision.Detection.ObjectDetectorSearchMode.Average);
System.Drawing.Rectangle[] rectangles = detector.ProcessFrame(cvsbmp);
List <Bitmap> listBitmap = new List <Bitmap>();
foreach (System.Drawing.Rectangle r in rectangles)
{
listBitmap.Add(UtilFn.CropImage(cvsbmp, r.X, r.Y, r.Width, r.Height));
}
if (rectangles.Count() == 0)
{
imageInfo.Text = "No faces detected!";
}
else
{
//imagesEdited[j] = (converter.Convert(UtilFn.MergeImages(listBitmap), Type.GetType("BitmapImage"), null, null) as BitmapImage).Clone();
foreach (var x in listBitmap)
{
imagesEdited.Add((converter.Convert(x, Type.GetType("BitmapImage"), null, null) as BitmapImage).Clone());
}
}
}
static void TestHaar()
{
if (Environment.Is64BitProcess)
{
throw new Exception("Run in 32-bits");
}
// Let's test the detector using a sample video from
// the collection of test videos in the framework:
TestVideos ds = new TestVideos();
string fileName = ds["crowd.mp4"];
// In this example, we will be creating a cascade for a Face detector:
var cascade = new Accord.Vision.Detection.Cascades.FaceHaarCascade();
// Now, create a new Haar object detector with the cascade:
var detector = new HaarObjectDetector(cascade, minSize: 25,
searchMode: ObjectDetectorSearchMode.Average,
scalingMode: ObjectDetectorScalingMode.SmallerToGreater,
scaleFactor: 1.1f)
{
Suppression = 5 // This should make sure we only report regions as faces if
// they have been detected at least 5 times within different cascade scales.
};
// Now, let's open the video using FFMPEG:
var video = new VideoFileReader();
video.Open(fileName);
Stopwatch sw = Stopwatch.StartNew();
// Now, for each frame of the video
for (int frameIndex = 0; frameIndex < video.FrameCount; frameIndex++)
{
// Read the current frame into the bitmap data
Bitmap bmp = video.ReadVideoFrame(frameIndex);
// Feed the frame to the tracker
Rectangle[] faces = detector.ProcessFrame(bmp);
Console.WriteLine(faces.Length);
Console.WriteLine(bmp.Flags);
}
sw.Stop();
Console.WriteLine(sw.Elapsed);
video.Close();
}
public void FindFace(PictureBox pb)
{
AForge.Video.DirectShow.VideoCaptureDevice FinalVideoSource;
AForge.Video.DirectShow.FilterInfoCollection VideoCaptuerDevices;
VideoCaptuerDevices = new AForge.Video.DirectShow.FilterInfoCollection(AForge.Video.DirectShow.FilterCategory.VideoInputDevice);
FinalVideoSource = new AForge.Video.DirectShow.VideoCaptureDevice(VideoCaptuerDevices[0].MonikerString);
FinalVideoSource.NewFrame += new AForge.Video.NewFrameEventHandler((sender, eventArgs) =>
{
Bitmap image = (Bitmap)eventArgs.Frame.Clone();
pb.Image = image;
});
FinalVideoSource.Start();
FinalVideoSource.NewFrame += new AForge.Video.NewFrameEventHandler((sender, eventArgs) =>
{
Bitmap image = (Bitmap)eventArgs.Frame.Clone();
//görüntüde yüz aranacağı belirtilir.
Accord.Vision.Detection.Cascades.FaceHaarCascade cascade = new Accord.Vision.Detection.Cascades.FaceHaarCascade();
//görüntü üzerinde arama yapar. İkinci parametresi minimum arama alanıdır.
Accord.Vision.Detection.HaarObjectDetector detector = new Accord.Vision.Detection.HaarObjectDetector(cascade, 1);
detector.SearchMode = Accord.Vision.Detection.ObjectDetectorSearchMode.Single;
detector.ScalingFactor = 1.5f;
detector.ScalingMode = Accord.Vision.Detection.ObjectDetectorScalingMode.GreaterToSmaller;
detector.UseParallelProcessing = true;
detector.Suppression = 3;
Rectangle[] faces = detector.ProcessFrame(image);
Graphics g = Graphics.FromImage(image);
foreach (var face in faces)
{
Pen p = new Pen(Color.Red, 10f);
g.DrawRectangle(p, face);
}
g.Dispose();
pb.Image = image;
});
}
public static bool HasFace(string imagePath)
{
var cascade = new Accord.Vision.Detection.Cascades.FaceHaarCascade();
var detector = new HaarObjectDetector(cascade, minSize: 50,
searchMode: ObjectDetectorSearchMode.NoOverlap);
using (Image image = Image.FromFile(imagePath))
using (Bitmap bmp = new Bitmap(image))
{
detector.UseParallelProcessing = true;
Rectangle[] result = detector.ProcessFrame(bmp);
if (result != null && result.Length > 0)
{
return(true);
}
else
{
return(false);
}
}
}
/// <summary>
/// This method helps to face detection
/// </summary>
/// <param name="image">Original image</param>
/// <returns>Face detection result</returns>
public static FaceDetectionResult FaceDetection(Bitmap image)
{
// Creating an face detection instance
var result = new FaceDetectionResult();
var cascade = new Accord.Vision.Detection.Cascades.FaceHaarCascade();
// set min size in the picture to detect faces
var detector = new HaarObjectDetector(cascade, minSize: 100, searchMode: ObjectDetectorSearchMode.NoOverlap);
var bmp = Accord.Imaging.Image.Clone(image);
// execute detection
var faces = detector.ProcessFrame(bmp);
// set rectangle color
var objectMarker = new RectanglesMarker(Color.Red)
{
Rectangles = faces
};
// apply filter and get a new image
var resultImage = objectMarker.Apply(image); // overwrite the frame
result.ImageResult = resultImage;
// set result parameters
result.TotalFacesDetected = faces?.Length ?? 0;
result.Rectangles = faces;
return(result);
}
private Bitmap ProcessImage(Bitmap image)
{
// convert to grayscale
var gray = new GrayscaleBT709();
var frame = gray.Apply(image);
// boost contrast
var contrast = new ContrastCorrection();
contrast.ApplyInPlace(frame);
// set up a haar object detector to find faces
var cascade = new Accord.Vision.Detection.Cascades.FaceHaarCascade();
var detector = new HaarObjectDetector(cascade);
detector.MinSize = new Size(150, 150);
detector.ScalingFactor = 1.03f;
detector.SearchMode = ObjectDetectorSearchMode.Average;
detector.ScalingMode = ObjectDetectorScalingMode.SmallerToGreater;
// scan the image
var faces = detector.ProcessFrame(frame);
// create thumbnails for each face
var resizer = new ResizeNearestNeighbor(128, 128);
foreach (var rect in faces)
{
// zoom out a bit
var r = rect;
r.Inflate(50, 50);
r.X = r.X < 0 ? 0 : r.X;
r.Y = r.Y < 0 ? 0 : r.Y;
// copy the face into a new picturebox
using (var face = image.Clone(r, PixelFormat.Format24bppRgb))
{
var smallFace = resizer.Apply(face);
var thumbnail = new PictureBox()
{
Image = smallFace,
SizeMode = PictureBoxSizeMode.Zoom,
Width = 62,
Height = 62
};
imagesPanel.Controls.Add(thumbnail);
}
}
// highlight all detected faces in the main image
using (Graphics g = Graphics.FromImage(image))
{
var pen = new Pen(Color.LightGreen, 4);
foreach (var face in faces)
{
g.DrawRectangle(pen, face);
}
}
return(image);
}
