/// <summary>
/// Find the pedestrian in the image
/// </summary>
/// <param name="image">The image</param>
/// <param name="processingTime">The pedestrian detection time in milliseconds</param>
/// <returns>The region where pedestrians are detected</returns>
public static Rectangle[] Find(Mat image, bool tryUseCuda, bool tryUseOpenCL, out long processingTime)
{
Stopwatch watch;
Rectangle[] regions;
#if !(IOS || NETFX_CORE)
//check if there is a compatible Cuda device to run pedestrian detection
if (tryUseCuda && CudaInvoke.HasCuda)
{ //this is the Cuda version
using (CudaHOG des = new CudaHOG(new Size(64, 128), new Size(16, 16), new Size(8, 8), new Size(8, 8)))
{
des.SetSVMDetector(des.GetDefaultPeopleDetector());
watch = Stopwatch.StartNew();
using (GpuMat cudaBgr = new GpuMat(image))
using (GpuMat cudaBgra = new GpuMat())
using (VectorOfRect vr = new VectorOfRect())
{
CudaInvoke.CvtColor(cudaBgr, cudaBgra, ColorConversion.Bgr2Bgra);
des.DetectMultiScale(cudaBgra, vr);
regions = vr.ToArray();
}
}
}
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;
//this is the CPU/OpenCL version
using (HOGDescriptor des = new HOGDescriptor())
{
des.SetSVMDetector(HOGDescriptor.GetDefaultPeopleDetector());
//load the image to umat so it will automatically use opencl is available
UMat umat = image.ToUMat(AccessType.Read);
watch = Stopwatch.StartNew();
MCvObjectDetection[] results = des.DetectMultiScale(umat);
regions = new Rectangle[results.Length];
for (int i = 0; i < results.Length; i++)
regions[i] = results[i].Rect;
watch.Stop();
}
}
processingTime = watch.ElapsedMilliseconds;
return regions;
}
/// <summary>
/// Find the pedestrian in the image
/// </summary>
/// <param name="image">The image</param>
/// <param name="processingTime">The pedestrian detection time in milliseconds</param>
/// <returns>The region where pedestrians are detected</returns>
public static Rectangle[] Find(Mat image, bool tryUseCuda, out long processingTime)
{
Stopwatch watch;
Rectangle[] regions;
#if !(__IOS__ || NETFX_CORE)
//check if there is a compatible Cuda device to run pedestrian detection
if (tryUseCuda && CudaInvoke.HasCuda)
{ //this is the Cuda version
using (CudaHOG des = new CudaHOG(new Size(64, 128), new Size(16, 16), new Size(8,8), new Size(8,8)))
{
des.SetSVMDetector(des.GetDefaultPeopleDetector());
watch = Stopwatch.StartNew();
using (GpuMat cudaBgr = new GpuMat(image))
using (GpuMat cudaBgra = new GpuMat() )
using (VectorOfRect vr = new VectorOfRect())
{
CudaInvoke.CvtColor(cudaBgr, cudaBgra, ColorConversion.Bgr2Bgra);
des.DetectMultiScale(cudaBgra, vr);
regions = vr.ToArray();
}
}
}
else
#endif
{
//this is the CPU/OpenCL version
using (HOGDescriptor des = new HOGDescriptor())
{
des.SetSVMDetector(HOGDescriptor.GetDefaultPeopleDetector());
//load the image to umat so it will automatically use opencl is available
UMat umat = image.ToUMat(AccessType.Read);
watch = Stopwatch.StartNew();
MCvObjectDetection[] results = des.DetectMultiScale(umat);
regions = new Rectangle[results.Length];
for (int i = 0; i < results.Length; i++)
regions[i] = results[i].Rect;
watch.Stop();
}
}
processingTime = watch.ElapsedMilliseconds;
return regions;
}
/// <summary>
/// Find the pedestrian in the image
/// </summary>
/// <param name="image">The image</param>
/// <param name="processingTime">The processing time in milliseconds</param>
/// <returns>The region where pedestrians are detected</returns>
public static Rectangle[] Find(IInputArray image, out long processingTime)
{
Stopwatch watch;
Rectangle[] regions;
using (InputArray iaImage = image.GetInputArray())
{
#if !(__IOS__ || NETFX_CORE)
//if the input array is a GpuMat
//check if there is a compatible Cuda device to run pedestrian detection
if (iaImage.Kind == InputArray.Type.CudaGpuMat)
{
//this is the Cuda version
using (CudaHOG des = new CudaHOG(new Size(64, 128), new Size(16, 16), new Size(8, 8), new Size(8, 8)))
{
des.SetSVMDetector(des.GetDefaultPeopleDetector());
watch = Stopwatch.StartNew();
using (GpuMat cudaBgra = new GpuMat())
using (VectorOfRect vr = new VectorOfRect())
{
CudaInvoke.CvtColor(image, cudaBgra, ColorConversion.Bgr2Bgra);
des.DetectMultiScale(cudaBgra, vr);
regions = vr.ToArray();
}
}
}
else
#endif
{
//this is the CPU/OpenCL version
using (HOGDescriptor des = new HOGDescriptor())
{
des.SetSVMDetector(HOGDescriptor.GetDefaultPeopleDetector());
watch = Stopwatch.StartNew();
MCvObjectDetection[] results = des.DetectMultiScale(image);
regions = new Rectangle[results.Length];
for (int i = 0; i < results.Length; i++)
regions[i] = results[i].Rect;
watch.Stop();
}
}
processingTime = watch.ElapsedMilliseconds;
return regions;
}
}
/// <summary>
/// Find the pedestrian in the image
/// </summary>
/// <param name="image">The image</param>
/// <param name="processingTime">The pedestrian detection time in milliseconds</param>
/// <returns>The image with pedestrian highlighted.</returns>
public static Image<Bgr, Byte> Find(Image<Bgr, Byte> image, out long processingTime)
{
Stopwatch watch;
Rectangle[] regions;
//check if there is a compatible GPU to run pedestrian detection
if (CudaInvoke.HasCuda)
{ //this is the GPU version
using (CudaHOG des = new CudaHOG(new Size(64, 128), new Size(16, 16), new Size(8, 8), new Size(8, 8)))
{
des.SetSVMDetector(des.GetDefaultPeopleDetector());
watch = Stopwatch.StartNew();
using (CudaImage<Bgr, Byte> gpuImg = new CudaImage<Bgr, byte>(image))
using (CudaImage<Bgra, Byte> gpuBgra = gpuImg.Convert<Bgra, Byte>())
using (VectorOfRect vr = new VectorOfRect())
{
CudaInvoke.CvtColor(gpuBgra, gpuBgra, ColorConversion.Bgr2Bgra);
des.DetectMultiScale(gpuBgra,vr);
regions = vr.ToArray();
}
}
}
else
{ //this is the CPU version
using (HOGDescriptor des = new HOGDescriptor())
{
des.SetSVMDetector(HOGDescriptor.GetDefaultPeopleDetector());
//load the image to umat so it will automatically use opencl is available
UMat umat = image.ToUMat();
watch = Stopwatch.StartNew();
//regions = des.DetectMultiScale(image);
MCvObjectDetection[] results = des.DetectMultiScale(umat);
regions = new Rectangle[results.Length];
for (int i = 0; i < results.Length; i++)
regions[i] = results[i].Rect;
}
}
watch.Stop();
processingTime = watch.ElapsedMilliseconds;
foreach (Rectangle pedestrain in regions)
{
image.Draw(pedestrain, new Bgr(Color.Red), 1);
}
return image;
}
public void TestHOG2()
{
if (CudaInvoke.HasCuda)
{
using (CudaHOG hog = new CudaHOG(
new Size (48, 96), //winSize
new Size(16, 16), //blockSize
new Size(8,8), //blockStride
new Size(8, 8) //cellSize
))
using (Mat pedestrianDescriptor = hog.GetDefaultPeopleDetector())
using (Image<Bgr, Byte> image = new Image<Bgr, byte>("pedestrian.png"))
{
//float[] pedestrianDescriptor = CudaHOGDescriptor.GetPeopleDetector48x96();
hog.SetSVMDetector(pedestrianDescriptor);
Stopwatch watch = Stopwatch.StartNew();
Rectangle[] rects;
using (GpuMat cudaImage = new GpuMat(image))
using (GpuMat gpuBgra = new GpuMat())
using (VectorOfRect vRect = new VectorOfRect())
{
CudaInvoke.CvtColor(cudaImage, gpuBgra, ColorConversion.Bgr2Bgra);
hog.DetectMultiScale(gpuBgra, vRect);
rects = vRect.ToArray();
}
watch.Stop();
//Assert.AreEqual(1, rects.Length);
foreach (Rectangle rect in rects)
image.Draw(rect, new Bgr(Color.Red), 1);
Trace.WriteLine(String.Format("HOG detection time: {0} ms", watch.ElapsedMilliseconds));
//ImageViewer.Show(image, String.Format("Detection Time: {0}ms", watch.ElapsedMilliseconds));
}
}
}
public void TestHOG1()
{
if (CudaInvoke.HasCuda)
{
using (CudaHOG hog = new CudaHOG(new Size(64, 128), new Size(16, 16), new Size(8, 8), new Size(8,8), 9))
using (Mat pedestrianDescriptor = hog.GetDefaultPeopleDetector())
using (Image<Bgr, Byte> image = new Image<Bgr, byte>("pedestrian.png"))
{
hog.SetSVMDetector(pedestrianDescriptor);
//hog.GroupThreshold = 0;
Stopwatch watch = Stopwatch.StartNew();
Rectangle[] rects;
using (CudaImage<Bgr, Byte> CudaImage = new CudaImage<Bgr, byte>(image))
using (CudaImage<Bgra, Byte> gpuBgra = CudaImage.Convert<Bgra, Byte>())
using (VectorOfRect vRect = new VectorOfRect())
{
hog.DetectMultiScale(gpuBgra, vRect);
rects = vRect.ToArray();
}
watch.Stop();
Assert.AreEqual(1, rects.Length);
foreach (Rectangle rect in rects)
image.Draw(rect, new Bgr(Color.Red), 1);
Trace.WriteLine(String.Format("HOG detection time: {0} ms", watch.ElapsedMilliseconds));
//ImageViewer.Show(image, String.Format("Detection Time: {0}ms", watch.ElapsedMilliseconds));
}
}
}