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0044047782
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
246 lines
7.2 KiB
C++
246 lines
7.2 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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#include "precomp.hpp"
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#include "opencl_kernels_core.hpp"
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#include "split.simd.hpp"
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#include "split.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
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namespace cv { namespace hal {
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void split8u(const uchar* src, uchar** dst, int len, int cn )
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{
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CV_INSTRUMENT_REGION();
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CALL_HAL(split8u, cv_hal_split8u, src,dst, len, cn)
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CV_CPU_DISPATCH(split8u, (src, dst, len, cn),
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CV_CPU_DISPATCH_MODES_ALL);
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}
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void split16u(const ushort* src, ushort** dst, int len, int cn )
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{
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CV_INSTRUMENT_REGION();
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CALL_HAL(split16u, cv_hal_split16u, src,dst, len, cn)
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CV_CPU_DISPATCH(split16u, (src, dst, len, cn),
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CV_CPU_DISPATCH_MODES_ALL);
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}
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void split32s(const int* src, int** dst, int len, int cn )
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{
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CV_INSTRUMENT_REGION();
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CALL_HAL(split32s, cv_hal_split32s, src,dst, len, cn)
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CV_CPU_DISPATCH(split32s, (src, dst, len, cn),
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CV_CPU_DISPATCH_MODES_ALL);
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}
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void split64s(const int64* src, int64** dst, int len, int cn )
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{
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CV_INSTRUMENT_REGION();
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CALL_HAL(split64s, cv_hal_split64s, src,dst, len, cn)
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CV_CPU_DISPATCH(split64s, (src, dst, len, cn),
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CV_CPU_DISPATCH_MODES_ALL);
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}
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} // namespace cv::hal::
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/****************************************************************************************\
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* split & merge *
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\****************************************************************************************/
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typedef void (*SplitFunc)(const uchar* src, uchar** dst, int len, int cn);
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static SplitFunc getSplitFunc(int depth)
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{
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static SplitFunc splitTab[CV_DEPTH_MAX] =
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{
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(SplitFunc)GET_OPTIMIZED(cv::hal::split8u), (SplitFunc)GET_OPTIMIZED(cv::hal::split8u),
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(SplitFunc)GET_OPTIMIZED(cv::hal::split16u), (SplitFunc)GET_OPTIMIZED(cv::hal::split16u),
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(SplitFunc)GET_OPTIMIZED(cv::hal::split32s), (SplitFunc)GET_OPTIMIZED(cv::hal::split32s),
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(SplitFunc)GET_OPTIMIZED(cv::hal::split64s), (SplitFunc)GET_OPTIMIZED(cv::hal::split16u),
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(SplitFunc)GET_OPTIMIZED(cv::hal::split16u), (SplitFunc)GET_OPTIMIZED(cv::hal::split8u),
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(SplitFunc)GET_OPTIMIZED(cv::hal::split64s), (SplitFunc)GET_OPTIMIZED(cv::hal::split64s),
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(SplitFunc)GET_OPTIMIZED(cv::hal::split32s), 0, 0, 0
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};
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return splitTab[depth];
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}
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#ifdef HAVE_IPP
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static bool ipp_split(const Mat& src, Mat* mv, int channels)
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{
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#ifdef HAVE_IPP_IW_LL
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CV_INSTRUMENT_REGION_IPP();
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if(channels != 3 && channels != 4)
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return false;
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if(src.dims <= 2)
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{
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IppiSize size = ippiSize(src.size());
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void *dstPtrs[4] = {NULL};
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size_t dstStep = mv[0].step;
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for(int i = 0; i < channels; i++)
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{
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dstPtrs[i] = mv[i].ptr();
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if(dstStep != mv[i].step)
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return false;
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}
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return CV_INSTRUMENT_FUN_IPP(llwiCopySplit, src.ptr(), (int)src.step, dstPtrs, (int)dstStep, size, (int)src.elemSize1(), channels, 0) >= 0;
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}
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else
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{
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const Mat *arrays[5] = {NULL};
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uchar *ptrs[5] = {NULL};
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arrays[0] = &src;
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for(int i = 1; i < channels; i++)
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{
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arrays[i] = &mv[i-1];
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}
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NAryMatIterator it(arrays, ptrs);
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IppiSize size = { (int)it.size, 1 };
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for( size_t i = 0; i < it.nplanes; i++, ++it )
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{
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if(CV_INSTRUMENT_FUN_IPP(llwiCopySplit, ptrs[0], 0, (void**)&ptrs[1], 0, size, (int)src.elemSize1(), channels, 0) < 0)
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return false;
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}
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return true;
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}
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#else
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CV_UNUSED(src); CV_UNUSED(mv); CV_UNUSED(channels);
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return false;
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#endif
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}
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#endif
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void split(const Mat& src, Mat* mv)
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{
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CV_INSTRUMENT_REGION();
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int k, depth = src.depth(), cn = src.channels();
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if( cn == 1 )
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{
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src.copyTo(mv[0]);
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return;
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}
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for( k = 0; k < cn; k++ )
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{
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mv[k].create(src.dims, src.size, depth);
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}
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CV_IPP_RUN_FAST(ipp_split(src, mv, cn));
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SplitFunc func = getSplitFunc(depth);
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CV_Assert( func != 0 );
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size_t esz = src.elemSize(), esz1 = src.elemSize1();
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size_t blocksize0 = (BLOCK_SIZE + esz-1)/esz;
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AutoBuffer<uchar> _buf((cn+1)*(sizeof(Mat*) + sizeof(uchar*)) + 16);
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const Mat** arrays = (const Mat**)_buf.data();
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uchar** ptrs = (uchar**)alignPtr(arrays + cn + 1, 16);
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arrays[0] = &src;
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for( k = 0; k < cn; k++ )
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{
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arrays[k+1] = &mv[k];
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}
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NAryMatIterator it(arrays, ptrs, cn+1);
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size_t total = it.size;
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size_t blocksize = std::min((size_t)CV_SPLIT_MERGE_MAX_BLOCK_SIZE(cn), cn <= 4 ? total : std::min(total, blocksize0));
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for( size_t i = 0; i < it.nplanes; i++, ++it )
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{
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for( size_t j = 0; j < total; j += blocksize )
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{
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size_t bsz = std::min(total - j, blocksize);
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func( ptrs[0], &ptrs[1], (int)bsz, cn );
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if( j + blocksize < total )
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{
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ptrs[0] += bsz*esz;
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for( k = 0; k < cn; k++ )
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ptrs[k+1] += bsz*esz1;
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}
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}
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}
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}
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#ifdef HAVE_OPENCL
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static bool ocl_split( InputArray _m, OutputArrayOfArrays _mv )
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{
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int type = _m.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type),
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rowsPerWI = ocl::Device::getDefault().isIntel() ? 4 : 1;
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String dstargs, processelem, indexdecl;
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for (int i = 0; i < cn; ++i)
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{
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dstargs += format("DECLARE_DST_PARAM(%d)", i);
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indexdecl += format("DECLARE_INDEX(%d)", i);
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processelem += format("PROCESS_ELEM(%d)", i);
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}
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ocl::Kernel k("split", ocl::core::split_merge_oclsrc,
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format("-D T=%s -D OP_SPLIT -D cn=%d -D DECLARE_DST_PARAMS=%s"
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" -D PROCESS_ELEMS_N=%s -D DECLARE_INDEX_N=%s",
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ocl::memopTypeToStr(depth), cn, dstargs.c_str(),
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processelem.c_str(), indexdecl.c_str()));
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if (k.empty())
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return false;
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Size size = _m.size();
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_mv.create(cn, 1, depth);
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for (int i = 0; i < cn; ++i)
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_mv.create(size, depth, i);
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std::vector<UMat> dst;
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_mv.getUMatVector(dst);
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int argidx = k.set(0, ocl::KernelArg::ReadOnly(_m.getUMat()));
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for (int i = 0; i < cn; ++i)
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argidx = k.set(argidx, ocl::KernelArg::WriteOnlyNoSize(dst[i]));
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k.set(argidx, rowsPerWI);
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size_t globalsize[2] = { (size_t)size.width, ((size_t)size.height + rowsPerWI - 1) / rowsPerWI };
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return k.run(2, globalsize, NULL, false);
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}
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#endif
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void split(InputArray _m, OutputArrayOfArrays _mv)
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{
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CV_INSTRUMENT_REGION();
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CV_OCL_RUN(_m.dims() <= 2 && _mv.isUMatVector(),
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ocl_split(_m, _mv))
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Mat m = _m.getMat();
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if( m.empty() )
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{
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_mv.release();
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return;
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}
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CV_Assert( !_mv.fixedType() || _mv.empty() || _mv.type() == m.depth() );
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int depth = m.depth(), cn = m.channels();
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_mv.create(cn, 1, depth);
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for (int i = 0; i < cn; ++i)
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_mv.create(m.dims, m.size.p, depth, i);
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std::vector<Mat> dst;
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_mv.getMatVector(dst);
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split(m, &dst[0]);
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}
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} // namespace
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