private Rectangle[] FindEyes(string eyeFileName, CudaImage<Gray, Byte> image)
{
using (CudaCascadeClassifier eye = new CudaCascadeClassifier(eyeFileName))
using (GpuMat eyeRegionMat = new GpuMat())
{
eye.DetectMultiScale(image, eyeRegionMat);
Rectangle[] eyeRegion = eye.Convert(eyeRegionMat);
return eyeRegion;
}
}
public static void Detect(
Mat image, String faceFileName, String eyeFileName,
List<Rectangle> faces, List<Rectangle> eyes,
bool tryUseCuda, bool tryUseOpenCL,
out long detectionTime)
{
Stopwatch watch;
#if !(IOS || NETFX_CORE)
if (tryUseCuda && CudaInvoke.HasCuda)
{
using (CudaCascadeClassifier face = new CudaCascadeClassifier(faceFileName))
using (CudaCascadeClassifier eye = new CudaCascadeClassifier(eyeFileName))
{
face.ScaleFactor = 1.1;
face.MinNeighbors = 10;
face.MinObjectSize = Size.Empty;
eye.ScaleFactor = 1.1;
eye.MinNeighbors = 10;
eye.MinObjectSize = Size.Empty;
watch = Stopwatch.StartNew();
using (CudaImage<Bgr, Byte> gpuImage = new CudaImage<Bgr, byte>(image))
using (CudaImage<Gray, Byte> gpuGray = gpuImage.Convert<Gray, Byte>())
using (GpuMat region = new GpuMat())
{
face.DetectMultiScale(gpuGray, region);
Rectangle[] faceRegion = face.Convert(region);
faces.AddRange(faceRegion);
foreach (Rectangle f in faceRegion)
{
using (CudaImage<Gray, Byte> faceImg = gpuGray.GetSubRect(f))
{
//For some reason a clone is required.
//Might be a bug of CudaCascadeClassifier in opencv
using (CudaImage<Gray, Byte> clone = faceImg.Clone(null))
using (GpuMat eyeRegionMat = new GpuMat())
{
eye.DetectMultiScale(clone, eyeRegionMat);
Rectangle[] eyeRegion = eye.Convert(eyeRegionMat);
foreach (Rectangle e in eyeRegion)
{
Rectangle eyeRect = e;
eyeRect.Offset(f.X, f.Y);
eyes.Add(eyeRect);
}
}
}
}
}
watch.Stop();
}
}
else
#endif
{
//Many opencl functions require opencl compatible gpu devices.
//As of opencv 3.0-alpha, opencv will crash if opencl is enable and only opencv compatible cpu device is presented
//So we need to call CvInvoke.HaveOpenCLCompatibleGpuDevice instead of CvInvoke.HaveOpenCL (which also returns true on a system that only have cpu opencl devices).
CvInvoke.UseOpenCL = tryUseOpenCL && CvInvoke.HaveOpenCLCompatibleGpuDevice;
//Read the HaarCascade objects
using (CascadeClassifier face = new CascadeClassifier(faceFileName))
//using (CascadeClassifier eye = new CascadeClassifier(eyeFileName))
{
watch = Stopwatch.StartNew();
using (UMat ugray = new UMat())
{
CvInvoke.CvtColor(image, ugray, Emgu.CV.CvEnum.ColorConversion.Bgr2Gray);
//normalizes brightness and increases contrast of the image
CvInvoke.EqualizeHist(ugray, ugray);
//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
Rectangle[] facesDetected = face.DetectMultiScale(
ugray,
1.1,
2);
faces.AddRange(facesDetected);
//foreach (Rectangle f in facesDetected)
//{
// //Get the region of interest on the faces
// using (UMat faceRegion = new UMat(ugray, f))
// {
// Rectangle[] eyesDetected = eye.DetectMultiScale(
// faceRegion,
// 1.1,
// 10,
// new Size(20, 20));
// foreach (Rectangle e in eyesDetected)
// {
// Rectangle eyeRect = e;
// eyeRect.Offset(f.X, f.Y);
// eyes.Add(eyeRect);
// }
// }
//}
}
watch.Stop();
}
}
detectionTime = watch.ElapsedMilliseconds;
}
public List<Face> FindFaces(Image<Bgr, byte> image, string faceFileName, string eyeFileName, double scale, int neighbors, int minSize)
{
List<Face> faces = new List<Face>();
List<Rectangle> facesRect = new List<Rectangle>();
List<Rectangle> eyesRect = new List<Rectangle>();
try
{
//Console.WriteLine(" FaceDetectGPU FindFaces faceFileName=" + faceFileName + " cuda = " + CudaInvoke.HasCuda);
using (CudaCascadeClassifier face = new CudaCascadeClassifier(faceFileName))
{
using (CudaImage<Bgr, Byte> CudaImage = new CudaImage<Bgr, byte>(image))
using (CudaImage<Gray, Byte> CudaGray = CudaImage.Convert<Gray, Byte>())
using (GpuMat region = new GpuMat())
{
face.DetectMultiScale(CudaGray, region);
Rectangle[] faceRegion = face.Convert(region);
facesRect.AddRange(faceRegion);
foreach (Rectangle f in faceRegion)
{
using (CudaImage<Gray, Byte> faceImg = CudaGray.GetSubRect(f))
{
using (CudaImage<Gray, Byte> clone = faceImg.Clone(null))
{
Face facemodel = new Face();
eyesRect = new List<Rectangle>(FindEyes(eyeFileName, clone));
if (eyesRect != null)
{
facemodel.EyesRects = eyesRect;
facemodel.EyesCount = eyesRect.Count;
}
else
{
continue;
}
facemodel.FaceImage = clone.Bitmap;
facemodel.Height = facemodel.FaceImage.Height;
facemodel.Width = facemodel.FaceImage.Width;
facemodel.FaceRect = f;
facemodel.FramePosX = f.X;
facemodel.FramePosY = f.Y;
facemodel.ImageFrameSize = image.Size;
Gray avgf = new Gray();
MCvScalar avstd = new MCvScalar();
clone.ToImage().AvgSdv(out avgf, out avstd);
facemodel.StdDev = avstd.V0;
faces.Add(facemodel);
if (facemodel.FaceScore > 39)
Console.WriteLine("FaceDetect USING gpuCUDA Add faceModel" + facemodel.FaceScore);
break;
}
}
}
}
}
}
catch (Exception cudaerrJones)
{
Console.WriteLine("cudaerrJones = " + cudaerrJones);
}
return faces;
}
public static void Detect(
IInputArray image, String faceFileName, String eyeFileName,
List<Rectangle> faces, List<Rectangle> eyes,
out long detectionTime)
{
Stopwatch watch;
using (InputArray iaImage = image.GetInputArray())
{
#if !(__IOS__ || NETFX_CORE)
if (iaImage.Kind == InputArray.Type.CudaGpuMat && CudaInvoke.HasCuda)
{
using (CudaCascadeClassifier face = new CudaCascadeClassifier(faceFileName))
using (CudaCascadeClassifier eye = new CudaCascadeClassifier(eyeFileName))
{
face.ScaleFactor = 1.1;
face.MinNeighbors = 10;
face.MinObjectSize = Size.Empty;
eye.ScaleFactor = 1.1;
eye.MinNeighbors = 10;
eye.MinObjectSize = Size.Empty;
watch = Stopwatch.StartNew();
using (CudaImage<Bgr, Byte> gpuImage = new CudaImage<Bgr, byte>(image))
using (CudaImage<Gray, Byte> gpuGray = gpuImage.Convert<Gray, Byte>())
using (GpuMat region = new GpuMat())
{
face.DetectMultiScale(gpuGray, region);
Rectangle[] faceRegion = face.Convert(region);
faces.AddRange(faceRegion);
foreach (Rectangle f in faceRegion)
{
using (CudaImage<Gray, Byte> faceImg = gpuGray.GetSubRect(f))
{
//For some reason a clone is required.
//Might be a bug of CudaCascadeClassifier in opencv
using (CudaImage<Gray, Byte> clone = faceImg.Clone(null))
using (GpuMat eyeRegionMat = new GpuMat())
{
eye.DetectMultiScale(clone, eyeRegionMat);
Rectangle[] eyeRegion = eye.Convert(eyeRegionMat);
foreach (Rectangle e in eyeRegion)
{
Rectangle eyeRect = e;
eyeRect.Offset(f.X, f.Y);
eyes.Add(eyeRect);
}
}
}
}
}
watch.Stop();
}
}
else
#endif
{
//Read the HaarCascade objects
using (CascadeClassifier face = new CascadeClassifier(faceFileName))
using (CascadeClassifier eye = new CascadeClassifier(eyeFileName))
{
watch = Stopwatch.StartNew();
using (UMat ugray = new UMat())
{
CvInvoke.CvtColor(image, ugray, Emgu.CV.CvEnum.ColorConversion.Bgr2Gray);
//normalizes brightness and increases contrast of the image
CvInvoke.EqualizeHist(ugray, ugray);
//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
Rectangle[] facesDetected = face.DetectMultiScale(
ugray,
1.1,
10,
new Size(20, 20));
faces.AddRange(facesDetected);
foreach (Rectangle f in facesDetected)
{
//Get the region of interest on the faces
using (UMat faceRegion = new UMat(ugray, f))
{
Rectangle[] eyesDetected = eye.DetectMultiScale(
faceRegion,
1.1,
10,
new Size(20, 20));
foreach (Rectangle e in eyesDetected)
{
Rectangle eyeRect = e;
eyeRect.Offset(f.X, f.Y);
eyes.Add(eyeRect);
}
}
}
}
watch.Stop();
}
}
detectionTime = watch.ElapsedMilliseconds;
}
}
