opencv/modules/core/src/split.dispatch.cpp
Alexander Smorkalov 0044047782
Merge pull request #25598 from asmorkalov:as/tables_range_check_core
Check range for type-dependant function tables #25598

Address https://github.com/opencv/opencv/issues/24703

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-05-17 10:48:40 +03:00

246 lines
7.2 KiB
C++

// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "opencl_kernels_core.hpp"
#include "split.simd.hpp"
#include "split.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
namespace cv { namespace hal {
void split8u(const uchar* src, uchar** dst, int len, int cn )
{
CV_INSTRUMENT_REGION();
CALL_HAL(split8u, cv_hal_split8u, src,dst, len, cn)
CV_CPU_DISPATCH(split8u, (src, dst, len, cn),
CV_CPU_DISPATCH_MODES_ALL);
}
void split16u(const ushort* src, ushort** dst, int len, int cn )
{
CV_INSTRUMENT_REGION();
CALL_HAL(split16u, cv_hal_split16u, src,dst, len, cn)
CV_CPU_DISPATCH(split16u, (src, dst, len, cn),
CV_CPU_DISPATCH_MODES_ALL);
}
void split32s(const int* src, int** dst, int len, int cn )
{
CV_INSTRUMENT_REGION();
CALL_HAL(split32s, cv_hal_split32s, src,dst, len, cn)
CV_CPU_DISPATCH(split32s, (src, dst, len, cn),
CV_CPU_DISPATCH_MODES_ALL);
}
void split64s(const int64* src, int64** dst, int len, int cn )
{
CV_INSTRUMENT_REGION();
CALL_HAL(split64s, cv_hal_split64s, src,dst, len, cn)
CV_CPU_DISPATCH(split64s, (src, dst, len, cn),
CV_CPU_DISPATCH_MODES_ALL);
}
} // namespace cv::hal::
/****************************************************************************************\
* split & merge *
\****************************************************************************************/
typedef void (*SplitFunc)(const uchar* src, uchar** dst, int len, int cn);
static SplitFunc getSplitFunc(int depth)
{
static SplitFunc splitTab[CV_DEPTH_MAX] =
{
(SplitFunc)GET_OPTIMIZED(cv::hal::split8u), (SplitFunc)GET_OPTIMIZED(cv::hal::split8u),
(SplitFunc)GET_OPTIMIZED(cv::hal::split16u), (SplitFunc)GET_OPTIMIZED(cv::hal::split16u),
(SplitFunc)GET_OPTIMIZED(cv::hal::split32s), (SplitFunc)GET_OPTIMIZED(cv::hal::split32s),
(SplitFunc)GET_OPTIMIZED(cv::hal::split64s), (SplitFunc)GET_OPTIMIZED(cv::hal::split16u),
(SplitFunc)GET_OPTIMIZED(cv::hal::split16u), (SplitFunc)GET_OPTIMIZED(cv::hal::split8u),
(SplitFunc)GET_OPTIMIZED(cv::hal::split64s), (SplitFunc)GET_OPTIMIZED(cv::hal::split64s),
(SplitFunc)GET_OPTIMIZED(cv::hal::split32s), 0, 0, 0
};
return splitTab[depth];
}
#ifdef HAVE_IPP
static bool ipp_split(const Mat& src, Mat* mv, int channels)
{
#ifdef HAVE_IPP_IW_LL
CV_INSTRUMENT_REGION_IPP();
if(channels != 3 && channels != 4)
return false;
if(src.dims <= 2)
{
IppiSize size = ippiSize(src.size());
void *dstPtrs[4] = {NULL};
size_t dstStep = mv[0].step;
for(int i = 0; i < channels; i++)
{
dstPtrs[i] = mv[i].ptr();
if(dstStep != mv[i].step)
return false;
}
return CV_INSTRUMENT_FUN_IPP(llwiCopySplit, src.ptr(), (int)src.step, dstPtrs, (int)dstStep, size, (int)src.elemSize1(), channels, 0) >= 0;
}
else
{
const Mat *arrays[5] = {NULL};
uchar *ptrs[5] = {NULL};
arrays[0] = &src;
for(int i = 1; i < channels; i++)
{
arrays[i] = &mv[i-1];
}
NAryMatIterator it(arrays, ptrs);
IppiSize size = { (int)it.size, 1 };
for( size_t i = 0; i < it.nplanes; i++, ++it )
{
if(CV_INSTRUMENT_FUN_IPP(llwiCopySplit, ptrs[0], 0, (void**)&ptrs[1], 0, size, (int)src.elemSize1(), channels, 0) < 0)
return false;
}
return true;
}
#else
CV_UNUSED(src); CV_UNUSED(mv); CV_UNUSED(channels);
return false;
#endif
}
#endif
void split(const Mat& src, Mat* mv)
{
CV_INSTRUMENT_REGION();
int k, depth = src.depth(), cn = src.channels();
if( cn == 1 )
{
src.copyTo(mv[0]);
return;
}
for( k = 0; k < cn; k++ )
{
mv[k].create(src.dims, src.size, depth);
}
CV_IPP_RUN_FAST(ipp_split(src, mv, cn));
SplitFunc func = getSplitFunc(depth);
CV_Assert( func != 0 );
size_t esz = src.elemSize(), esz1 = src.elemSize1();
size_t blocksize0 = (BLOCK_SIZE + esz-1)/esz;
AutoBuffer<uchar> _buf((cn+1)*(sizeof(Mat*) + sizeof(uchar*)) + 16);
const Mat** arrays = (const Mat**)_buf.data();
uchar** ptrs = (uchar**)alignPtr(arrays + cn + 1, 16);
arrays[0] = &src;
for( k = 0; k < cn; k++ )
{
arrays[k+1] = &mv[k];
}
NAryMatIterator it(arrays, ptrs, cn+1);
size_t total = it.size;
size_t blocksize = std::min((size_t)CV_SPLIT_MERGE_MAX_BLOCK_SIZE(cn), cn <= 4 ? total : std::min(total, blocksize0));
for( size_t i = 0; i < it.nplanes; i++, ++it )
{
for( size_t j = 0; j < total; j += blocksize )
{
size_t bsz = std::min(total - j, blocksize);
func( ptrs[0], &ptrs[1], (int)bsz, cn );
if( j + blocksize < total )
{
ptrs[0] += bsz*esz;
for( k = 0; k < cn; k++ )
ptrs[k+1] += bsz*esz1;
}
}
}
}
#ifdef HAVE_OPENCL
static bool ocl_split( InputArray _m, OutputArrayOfArrays _mv )
{
int type = _m.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type),
rowsPerWI = ocl::Device::getDefault().isIntel() ? 4 : 1;
String dstargs, processelem, indexdecl;
for (int i = 0; i < cn; ++i)
{
dstargs += format("DECLARE_DST_PARAM(%d)", i);
indexdecl += format("DECLARE_INDEX(%d)", i);
processelem += format("PROCESS_ELEM(%d)", i);
}
ocl::Kernel k("split", ocl::core::split_merge_oclsrc,
format("-D T=%s -D OP_SPLIT -D cn=%d -D DECLARE_DST_PARAMS=%s"
" -D PROCESS_ELEMS_N=%s -D DECLARE_INDEX_N=%s",
ocl::memopTypeToStr(depth), cn, dstargs.c_str(),
processelem.c_str(), indexdecl.c_str()));
if (k.empty())
return false;
Size size = _m.size();
_mv.create(cn, 1, depth);
for (int i = 0; i < cn; ++i)
_mv.create(size, depth, i);
std::vector<UMat> dst;
_mv.getUMatVector(dst);
int argidx = k.set(0, ocl::KernelArg::ReadOnly(_m.getUMat()));
for (int i = 0; i < cn; ++i)
argidx = k.set(argidx, ocl::KernelArg::WriteOnlyNoSize(dst[i]));
k.set(argidx, rowsPerWI);
size_t globalsize[2] = { (size_t)size.width, ((size_t)size.height + rowsPerWI - 1) / rowsPerWI };
return k.run(2, globalsize, NULL, false);
}
#endif
void split(InputArray _m, OutputArrayOfArrays _mv)
{
CV_INSTRUMENT_REGION();
CV_OCL_RUN(_m.dims() <= 2 && _mv.isUMatVector(),
ocl_split(_m, _mv))
Mat m = _m.getMat();
if( m.empty() )
{
_mv.release();
return;
}
CV_Assert( !_mv.fixedType() || _mv.empty() || _mv.type() == m.depth() );
int depth = m.depth(), cn = m.channels();
_mv.create(cn, 1, depth);
for (int i = 0; i < cn; ++i)
_mv.create(m.dims, m.size.p, depth, i);
std::vector<Mat> dst;
_mv.getMatVector(dst);
split(m, &dst[0]);
}
} // namespace