void pyrUp(const cv::ocl::oclMat &src, cv::ocl::oclMat &dst)
{
dst.create(src.rows * 2, src.cols * 2, src.type());
Context *clCxt = src.clCxt;
const String kernelName = "pyrUp";
std::vector< std::pair<size_t, const void *> > args;
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&src.data));
args.push_back( std::make_pair( sizeof(cl_mem), (void *)&dst.data));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src.rows));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst.rows));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src.cols));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst.cols));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src.offset));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst.offset));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&src.step));
args.push_back( std::make_pair( sizeof(cl_int), (void *)&dst.step));
size_t globalThreads[3] = {dst.cols, dst.rows, 1};
size_t localThreads[3] = {16, 16, 1};
openCLExecuteKernel(clCxt, &pyr_up, kernelName, globalThreads, localThreads, args, src.oclchannels(), src.depth());
}
inline void argus_depth::refresh_frame(){
if(input_module->getFrame(mat_left,mat_right)){
remap(mat_left, rect_mat_left, rmap[0][0], rmap[0][1], CV_INTER_LINEAR);
remap(mat_right, rect_mat_right, rmap[1][0], rmap[1][1], CV_INTER_LINEAR);
}else{
input_module = new module_eye("left.mpg","right.mpg");
}
cvtColor(rect_mat_left,BW_rect_mat_left,CV_BGR2GRAY);
cvtColor(rect_mat_right,BW_rect_mat_right,CV_BGR2GRAY);
frame_counter++;
#if USE_GPU
cv::Mat local;
cv::cvtColor(rect_mat_left,local,CV_BGR2GRAY);
frame_ocl.upload(local);
#endif
}
void cv::ocl::MOG::operator()(const cv::ocl::oclMat& frame, cv::ocl::oclMat& fgmask, float learningRate)
{
using namespace cv::ocl::device::mog;
CV_Assert(frame.depth() == CV_8U);
int ch = frame.oclchannels();
int work_ch = ch;
if (nframes_ == 0 || learningRate >= 1.0 || frame.size() != frameSize_ || work_ch != mean_.oclchannels())
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_ocl(frame, ch, fgmask, weight_, sortKey_, mean_, var_, nmixtures_,
varThreshold, learningRate, backgroundRatio, noiseSigma);
}
