//! find keypoints and compute it's response if _bNonMaxSupression is true
//! return count of detected keypoints
//return the # of keypoints, stored in _uCount;
//store Key point locations into _cvgmKeyPointLocation;
//store the corner strength into _cvgmScore;
int CFast::calcKeyPointsLocation(const cv::gpu::GpuMat& cvgmImg_, const cv::gpu::GpuMat& cvgmMask_)
{
//using namespace cv::gpu::device::fast;
CV_Assert(cvgmImg_.type() == CV_8UC1);
CV_Assert(cvgmMask_.empty() || (cvgmMask_.type() == CV_8UC1 && cvgmMask_.size() == cvgmImg_.size()));
if (!cv::gpu::TargetArchs::builtWith(cv::gpu::GLOBAL_ATOMICS) || !cv::gpu::DeviceInfo().supports(cv::gpu::GLOBAL_ATOMICS))
CV_Error(CV_StsNotImplemented, "The device doesn't support global atomics");
unsigned int uMaxKeypoints = static_cast<unsigned int>(_dKeyPointsRatio * cvgmImg_.size().area());
ensureSizeIsEnough(1, uMaxKeypoints, CV_16SC2, _cvgmKeyPointLocation);
if (_bNonMaxSupression)
{
ensureSizeIsEnough(cvgmImg_.size(), CV_32SC1, _cvgmScore);
_cvgmScore.setTo(cv::Scalar::all(0));
}
_uCount = btl::device::fast::cudaCalcKeypoints(cvgmImg_, cvgmMask_, uMaxKeypoints, _nThreshold, _cvgmKeyPointLocation.ptr<short2>(), _bNonMaxSupression ? &_cvgmScore : NULL);
_uCount = std::min(_uCount, uMaxKeypoints);
return _uCount;
}
void cv::gpu::MOG_GPU::operator()(const cv::gpu::GpuMat& frame, cv::gpu::GpuMat& fgmask, float learningRate, Stream& stream)
{
using namespace cv::gpu::cudev::mog;
CV_Assert(frame.depth() == CV_8U);
int ch = frame.channels();
int work_ch = ch;
if (nframes_ == 0 || learningRate >= 1.0 || frame.size() != frameSize_ || work_ch != mean_.channels())
initialize(frame.size(), frame.type());
fgmask.create(frameSize_, CV_8UC1);
++nframes_;
learningRate = learningRate >= 0.0f && nframes_ > 1 ? learningRate : 1.0f / std::min(nframes_, history);
CV_Assert(learningRate >= 0.0f);
mog_gpu(frame, ch, fgmask, weight_, sortKey_, mean_, var_, nmixtures_,
varThreshold, learningRate, backgroundRatio, noiseSigma,
StreamAccessor::getStream(stream));
}
