/// <summary>
/// Release all the unmanaged memory associated with this cascade classifier
/// </summary>
protected override void DisposeObject()
{
if (_ptr != IntPtr.Zero)
{
SoftCascadeInvoke.cudaSoftCascadeDetectorRelease(ref _ptr);
}
}
/// <summary>
/// Apply cascade to an input frame and return the array of decection objects.
/// </summary>
/// <param name="image">A frame on which detector will be applied.</param>
/// <param name="rois">A regions of interests mask generated by genRoi. Only the objects that fall into one of the regions will be returned.</param>
/// <param name="stream">Use a Stream to call the function asynchronously (non-blocking) or null to call the function synchronously (blocking).</param>
/// <returns>An array of decection objects</returns>
public GpuMat Detect(CudaImage <Bgr, Byte> image, GpuMat <int> rois, Emgu.CV.Cuda.Stream stream = null)
{
GpuMat result = new GpuMat();
SoftCascadeInvoke.cudaSoftCascadeDetectorDetect(_ptr, image, rois, result, stream);
return(result);
}
/// <summary>
/// Create a soft (stageless) cascaded detector.
/// </summary>
/// <param name="trainedCascadeFileName">File name of the trained soft cascade detector</param>
/// <param name="minScale">A minimum scale relative to the original size of the image on which cascade will be applied. Use 0.4 for default.</param>
/// <param name="maxScale">A maximum scale relative to the original size of the image on which cascade will be applied. Use 5.0 for default</param>
/// <param name="scales">Number of scales from minScale to maxScale. Use 55 for default</param>
/// <param name="flags">An extra tuning flags.</param>
public CudaSoftCascadeDetector(String trainedCascadeFileName,
double minScale = 0.4, double maxScale = 5, int scales = 55,
SoftCascadeDetector.RejectionCriteria flags = SoftCascadeDetector.RejectionCriteria.NoReject)
{
using (CvString s = new CvString(trainedCascadeFileName))
_ptr = SoftCascadeInvoke.cudaSoftCascadeDetectorCreate(s, minScale, maxScale, scales, flags);
}
/// <summary>
/// Apply cascade to an input frame and return the vector of Detection objects.
/// </summary>
/// <param name="image">A frame on which detector will be applied.</param>
/// <param name="rois">A vector of regions of interest. Only the objects that fall into one of the regions will be returned.</param>
/// <returns>An output array of Detections.</returns>
public Detection[] Detect(IInputArray image, Rectangle[] rois = null)
{
using (VectorOfRect roiRects = new VectorOfRect())
using (VectorOfRect regions = new VectorOfRect())
using (VectorOfFloat confidents = new VectorOfFloat())
{
IntPtr roisPtr;
if (rois == null || rois.Length == 0)
{
roisPtr = IntPtr.Zero;
}
else
{
roiRects.Push(rois);
roisPtr = roiRects.Ptr;
}
using (InputArray iaImage = image.GetInputArray())
SoftCascadeInvoke.cveSoftCascadeDetectorDetect(_ptr, iaImage, roisPtr, regions, confidents);
if (regions.Size == 0)
{
return(new Detection[0]);
}
else
{
Rectangle[] regionArr = regions.ToArray();
float[] confidentArr = confidents.ToArray();
Detection[] results = new Detection[regionArr.Length];
for (int i = 0; i < results.Length; i++)
{
results[i] = new Detection(regionArr[i], confidentArr[i]);
}
return(results);
}
}
}
/// <summary>
/// Create a soft (stageless) cascaded detector.
/// </summary>
/// <param name="trainedCascadeFileName">File name of the trained soft cascade detector</param>
/// <param name="minScale">A minimum scale relative to the original size of the image on which cascade will be applied.</param>
/// <param name="maxScale">A maximum scale relative to the original size of the image on which cascade will be applied.</param>
/// <param name="scales">Number of scales from minScale to maxScale.</param>
/// <param name="rejCriteria">Algorithm used for non maximum suppression.</param>
public SoftCascadeDetector(String trainedCascadeFileName, double minScale = 0.4, double maxScale = 5.0, int scales = 55, RejectionCriteria rejCriteria = RejectionCriteria.NoReject)
{
using (CvString s = new CvString(trainedCascadeFileName))
_ptr = SoftCascadeInvoke.cveSoftCascadeDetectorCreate(s, minScale, maxScale, scales, rejCriteria);
}
