FilterEngine::apply
void FilterEngine::apply(const Mat& src, Mat& dst,
const Rect& srcRoi, Point dstOfs, bool isolated)
{
// check matrix types
CV_Assert( src.type() == srcType && dst.type() == dstType );
// handle the "whole image" case
Rect _srcRoi = srcRoi;
if( _srcRoi == Rect(0,0,-1,-1) )
_srcRoi = Rect(0,0,src.cols,src.rows);
// check if the destination ROI is inside dst.
// and FilterEngine::start will check if the source ROI is inside src.
CV_Assert( dstOfs.x >= 0 && dstOfs.y >= 0 &&
dstOfs.x + _srcRoi.width <= dst.cols &&
dstOfs.y + _srcRoi.height <= dst.rows );
// start filtering
int y = start(src, _srcRoi, isolated);
// process the whole ROI. Note that "endY - startY" is the total number
// of the source rows to process
// (including the possible rows outside of srcRoi but inside the source image)
proceed( src.data + y*src.step,
(int)src.step, endY - startY,
dst.data + dstOfs.y*dst.step +
dstOfs.x*dst.elemSize(), (int)dst.step );
}
//////////////////////////////////////////////////////////
Key codes:
// start filtering
int y = start(src, _srcRoi, isolated);//only a init;
So it calls "start" to proceed. We want to know , where convolution happens, See start
proceed is the core.
proceed( src.data + y*src.step,
(int)src.step, endY - startY,
dst.data + dstOfs.y*dst.step +
dstOfs.x*dst.elemSize(), (int)dst.step );