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laplacian ocl kernel optimization

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This ocl kernel is 46%~171% faster than current laplacian 3x3
ocl kernel in the perf test, with image format "CV_8UC1".

Signed-off-by: Li Peng <peng.li@intel.com>
This commit is contained in:
Li Peng
2016-10-27 14:52:26 +08:00
parent c93fb14dd2
commit 6cb73356b1
3 changed files with 248 additions and 22 deletions
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modules/imgproc/src/deriv.cpp
+66
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@@ -807,8 +807,57 @@ static bool ocl_Laplacian5(InputArray _src, OutputArray _dst,
return k.run(2, globalsize, NULL, false);
}
static bool ocl_Laplacian3_8UC1(InputArray _src, OutputArray _dst, int ddepth,
InputArray _kernel, double delta, int borderType)
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if ( !(dev.isIntel() && (type == CV_8UC1) && (ddepth == CV_8U) &&
(borderType != BORDER_WRAP) &&
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
(_src.cols() % 16 == 0) && (_src.rows() % 2 == 0)) )
return false;
Mat kernel = _kernel.getMat().reshape(1, 1);
if (ddepth < 0)
ddepth = sdepth;
Size size = _src.size();
size_t globalsize[2] = { 0, 0 };
size_t localsize[2] = { 0, 0 };
globalsize[0] = size.width / 16;
globalsize[1] = size.height / 2;
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
char build_opts[1024];
sprintf(build_opts, "-D %s %s", borderMap[borderType],
ocl::kernelToStr(kernel, CV_32F, "KERNEL_MATRIX").c_str());
ocl::Kernel k("laplacian3_8UC1_cols16_rows2", cv::ocl::imgproc::laplacian3_oclsrc, build_opts);
if (k.empty())
return false;
UMat src = _src.getUMat();
_dst.create(size, CV_MAKETYPE(ddepth, cn));
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
return false;
UMat dst = _dst.getUMat();
int idxArg = k.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = k.set(idxArg, (int)src.step);
idxArg = k.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
idxArg = k.set(idxArg, (int)dst.step);
idxArg = k.set(idxArg, (int)dst.rows);
idxArg = k.set(idxArg, (int)dst.cols);
idxArg = k.set(idxArg, static_cast<float>(delta));
return k.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
}
}
#endif
#if defined(HAVE_IPP)
@@ -892,6 +941,22 @@ void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
ddepth = sdepth;
_dst.create( _src.size(), CV_MAKETYPE(ddepth, cn) );
if( ksize == 1 || ksize == 3 )
{
float K[2][9] =
{
{ 0, 1, 0, 1, -4, 1, 0, 1, 0 },
{ 2, 0, 2, 0, -8, 0, 2, 0, 2 }
};
Mat kernel(3, 3, CV_32F, K[ksize == 3]);
if( scale != 1 )
kernel *= scale;
CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2,
ocl_Laplacian3_8UC1(_src, _dst, ddepth, kernel, delta, borderType));
}
CV_IPP_RUN((ksize == 3 || ksize == 5) && ((borderType & BORDER_ISOLATED) != 0 || !_src.isSubmatrix()) &&
((stype == CV_8UC1 && ddepth == CV_16S) || (ddepth == CV_32F && stype == CV_32FC1)) && (!cv::ocl::useOpenCL()),
ipp_Laplacian(_src, _dst, ddepth, ksize, scale, delta, borderType));
@@ -920,6 +985,7 @@ void cv::Laplacian( InputArray _src, OutputArray _dst, int ddepth, int ksize,
Mat kernel(3, 3, CV_32F, K[ksize == 3]);
if( scale != 1 )
kernel *= scale;
filter2D( _src, _dst, ddepth, kernel, Point(-1, -1), delta, borderType );
}
else