public static void UsingGPU(Image <Bgr, Byte> image, GpuCascadeClassifier face, GpuCascadeClassifier eye, List <Rectangle> faces, List <Rectangle> eyes, out long detectionTime)
{
watch = Stopwatch.StartNew();
using (GpuImage <Bgr, Byte> gpuImage = new GpuImage <Bgr, byte>(image))
using (GpuImage <Gray, Byte> gpuGray = gpuImage.Convert <Gray, Byte>())
{
Rectangle[] faceRegion = face.DetectMultiScale(gpuGray, 1.1, 10, Size.Empty);
faces.AddRange(faceRegion);
foreach (Rectangle f in faceRegion)
{
using (GpuImage <Gray, Byte> faceImg = gpuGray.GetSubRect(f))
{
//For some reason a clone is required.
//Might be a bug of GpuCascadeClassifier in opencv
using (GpuImage <Gray, Byte> clone = faceImg.Clone())
{
Rectangle[] eyeRegion = eye.DetectMultiScale(clone, 1.1, 10, Size.Empty);
foreach (Rectangle e in eyeRegion)
{
Rectangle eyeRect = e;
eyeRect.Offset(f.X, f.Y);
eyes.Add(eyeRect);
}
}
}
}
}
watch.Stop();
detectionTime = watch.ElapsedMilliseconds;
}
public static void Detect(Image <Bgr, Byte> image, String faceFileName, String eyeFileName, List <Rectangle> faces, List <Rectangle> eyes, out long detectionTime)
{
Stopwatch watch;
if (GpuInvoke.HasCuda)
{
using (GpuCascadeClassifier face = new GpuCascadeClassifier(faceFileName))
using (GpuCascadeClassifier eye = new GpuCascadeClassifier(eyeFileName))
{
watch = Stopwatch.StartNew();
using (GpuImage <Bgr, Byte> gpuImage = new GpuImage <Bgr, byte>(image))
using (GpuImage <Gray, Byte> gpuGray = gpuImage.Convert <Gray, Byte>())
{
Rectangle[] faceRegion = face.DetectMultiScale(gpuGray, 1.4, 4, Size.Empty);
faces.AddRange(faceRegion);
foreach (Rectangle f in faceRegion)
{
using (GpuImage <Gray, Byte> faceImg = gpuGray.GetSubRect(f))
{
//For some reason a clone is required.
//Might be a bug of GpuCascadeClassifier in opencv
using (GpuImage <Gray, Byte> clone = faceImg.Clone(null))
{
Rectangle[] eyeRegion = eye.DetectMultiScale(clone, 1.4, 4, Size.Empty);
foreach (Rectangle e in eyeRegion)
{
//Rectangle eyeRect = e;
//eyeRect.Offset(f.X, f.Y);
//eyes.Add(eyeRect);
}
}
}
}
}
watch.Stop();
}
}
else
{
//Read the HaarCascade objects
using (CascadeClassifier face = new CascadeClassifier(faceFileName))
using (CascadeClassifier eye = new CascadeClassifier(eyeFileName))
{
watch = Stopwatch.StartNew();
using (Image <Gray, Byte> gray = image.Convert <Gray, Byte>()) //Convert it to Grayscale
{
//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
Rectangle[] facesDetected = face.DetectMultiScale(
gray,
1.3,
4,
new Size(20, 20),
Size.Empty);
faces.AddRange(facesDetected);
foreach (Rectangle f in facesDetected)
{
//Set the region of interest on the faces
gray.ROI = f;
Rectangle[] eyesDetected = eye.DetectMultiScale(
gray,
1.4,
10,
new Size(20, 20),
Size.Empty);
gray.ROI = Rectangle.Empty;
foreach (Rectangle e in eyesDetected)
{
//Rectangle eyeRect = e;
//eyeRect.Offset(f.X, f.Y);
//eyes.Add(eyeRect);
}
}
}
watch.Stop();
}
}
detectionTime = watch.ElapsedMilliseconds;
}
static void Run()
{
Image <Bgr, Byte> image = new Image <Bgr, byte>("lena.jpg"); //Read the files as an 8-bit Bgr image
Stopwatch watch;
String faceFileName = "haarcascade_frontalface_default.xml";
String eyeFileName = "haarcascade_eye.xml";
if (GpuInvoke.HasCuda)
{
using (GpuCascadeClassifier face = new GpuCascadeClassifier(faceFileName))
using (GpuCascadeClassifier eye = new GpuCascadeClassifier(eyeFileName))
{
watch = Stopwatch.StartNew();
using (GpuImage <Bgr, Byte> gpuImage = new GpuImage <Bgr, byte>(image))
using (GpuImage <Gray, Byte> gpuGray = gpuImage.Convert <Gray, Byte>())
{
Rectangle[] faceRegion = face.DetectMultiScale(gpuGray, 1.1, 10, Size.Empty);
foreach (Rectangle f in faceRegion)
{
//draw the face detected in the 0th (gray) channel with blue color
image.Draw(f, new Bgr(Color.Blue), 2);
using (GpuImage <Gray, Byte> faceImg = gpuGray.GetSubRect(f))
{
//For some reason a clone is required.
//Might be a bug of GpuCascadeClassifier in opencv
using (GpuImage <Gray, Byte> clone = faceImg.Clone())
{
Rectangle[] eyeRegion = eye.DetectMultiScale(clone, 1.1, 10, Size.Empty);
foreach (Rectangle e in eyeRegion)
{
Rectangle eyeRect = e;
eyeRect.Offset(f.X, f.Y);
image.Draw(eyeRect, new Bgr(Color.Red), 2);
}
}
}
}
}
watch.Stop();
}
}
else
{
//Read the HaarCascade objects
using (HaarCascade face = new HaarCascade(faceFileName))
using (HaarCascade eye = new HaarCascade(eyeFileName))
{
watch = Stopwatch.StartNew();
using (Image <Gray, Byte> gray = image.Convert <Gray, Byte>()) //Convert it to Grayscale
{
//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 Size(20, 20));
foreach (MCvAvgComp f in facesDetected)
{
//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
gray.ROI = f.rect;
MCvAvgComp[] eyesDetected = eye.Detect(
gray,
1.1,
10,
Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,
new Size(20, 20));
gray.ROI = Rectangle.Empty;
foreach (MCvAvgComp e in eyesDetected)
{
Rectangle eyeRect = e.rect;
eyeRect.Offset(f.rect.X, f.rect.Y);
image.Draw(eyeRect, new Bgr(Color.Red), 2);
}
}
}
watch.Stop();
}
}
//display the image
ImageViewer.Show(image, String.Format(
"Completed face and eye detection using {0} in {1} milliseconds",
GpuInvoke.HasCuda ? "GPU": "CPU",
watch.ElapsedMilliseconds));
}
private void DetectFaceAndEyes(Image <Bgr, Byte> image, List <Rectangle> faces, List <Rectangle> eyes)
{
#if !IOS
if (GpuInvoke.HasCuda)
{
using (GpuCascadeClassifier face = new GpuCascadeClassifier(_faceFileName))
using (GpuCascadeClassifier eye = new GpuCascadeClassifier(_eyeFileName))
{
using (GpuImage <Bgr, Byte> gpuImage = new GpuImage <Bgr, byte>(image))
using (GpuImage <Gray, Byte> gpuGray = gpuImage.Convert <Gray, Byte>())
{
Rectangle[] faceRegion = face.DetectMultiScale(gpuGray, 1.1, 10, Size.Empty);
faces.AddRange(faceRegion);
foreach (Rectangle f in faceRegion)
{
using (GpuImage <Gray, Byte> faceImg = gpuGray.GetSubRect(f))
{
//For some reason a clone is required.
//Might be a bug of GpuCascadeClassifier in opencv
using (GpuImage <Gray, Byte> clone = faceImg.Clone())
{
Rectangle[] eyeRegion = eye.DetectMultiScale(clone, 1.1, 10, Size.Empty);
foreach (Rectangle e in eyeRegion)
{
Rectangle eyeRect = e;
eyeRect.Offset(f.X, f.Y);
eyes.Add(eyeRect);
}
}
}
}
}
}
}
else
#endif
{
//Read the HaarCascade objects
using (CascadeClassifier face = new CascadeClassifier(_faceFileName))
using (CascadeClassifier eye = new CascadeClassifier(_eyeFileName))
{
using (Image <Gray, Byte> gray = image.Convert <Gray, Byte>()) //Convert it to Grayscale
{
//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
Rectangle[] facesDetected = face.DetectMultiScale(
gray,
1.1,
10,
new Size(20, 20),
Size.Empty);
faces.AddRange(facesDetected);
foreach (Rectangle f in facesDetected)
{
//Set the region of interest on the faces
gray.ROI = f;
Rectangle[] eyesDetected = eye.DetectMultiScale(
gray,
1.1,
10,
new Size(20, 20),
Size.Empty);
gray.ROI = Rectangle.Empty;
foreach (Rectangle e in eyesDetected)
{
Rectangle eyeRect = e;
eyeRect.Offset(f.X, f.Y);
eyes.Add(eyeRect);
}
}
}
}
}
}
