mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
245 lines
7.2 KiB
245 lines
7.2 KiB
// 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
|
|
|