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https://github.com/opencv/opencv.git
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Merge pull request #13823 from alalek:core_dispatch_countNonZero
This commit is contained in:
Alexander Alekhin
commit
3c70d966cb
@ -5,6 +5,7 @@ ocv_add_dispatched_file(stat SSE4_2 AVX2)
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ocv_add_dispatched_file(arithm SSE2 SSE4_1 AVX2 VSX3)
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ocv_add_dispatched_file(convert SSE2 AVX2)
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ocv_add_dispatched_file(convert_scale SSE2 AVX2)
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ocv_add_dispatched_file(count_non_zero SSE2 AVX2)
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ocv_add_dispatched_file(sum SSE2 AVX2)
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# dispatching for accuracy tests
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181
modules/core/src/count_non_zero.dispatch.cpp
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181
modules/core/src/count_non_zero.dispatch.cpp
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@ -0,0 +1,181 @@
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// 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 "stat.hpp"
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#include "count_non_zero.simd.hpp"
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#include "count_non_zero.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
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namespace cv {
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static CountNonZeroFunc getCountNonZeroTab(int depth)
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{
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CV_INSTRUMENT_REGION();
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CV_CPU_DISPATCH(getCountNonZeroTab, (depth),
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CV_CPU_DISPATCH_MODES_ALL);
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}
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#ifdef HAVE_OPENCL
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static bool ocl_countNonZero( InputArray _src, int & res )
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{
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int type = _src.type(), depth = CV_MAT_DEPTH(type), kercn = ocl::predictOptimalVectorWidth(_src);
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bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
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if (depth == CV_64F && !doubleSupport)
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return false;
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int dbsize = ocl::Device::getDefault().maxComputeUnits();
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size_t wgs = ocl::Device::getDefault().maxWorkGroupSize();
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int wgs2_aligned = 1;
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while (wgs2_aligned < (int)wgs)
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wgs2_aligned <<= 1;
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wgs2_aligned >>= 1;
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ocl::Kernel k("reduce", ocl::core::reduce_oclsrc,
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format("-D srcT=%s -D srcT1=%s -D cn=1 -D OP_COUNT_NON_ZERO"
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" -D WGS=%d -D kercn=%d -D WGS2_ALIGNED=%d%s%s",
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ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)),
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ocl::typeToStr(depth), (int)wgs, kercn,
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wgs2_aligned, doubleSupport ? " -D DOUBLE_SUPPORT" : "",
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_src.isContinuous() ? " -D HAVE_SRC_CONT" : ""));
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if (k.empty())
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return false;
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UMat src = _src.getUMat(), db(1, dbsize, CV_32SC1);
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k.args(ocl::KernelArg::ReadOnlyNoSize(src), src.cols, (int)src.total(),
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dbsize, ocl::KernelArg::PtrWriteOnly(db));
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size_t globalsize = dbsize * wgs;
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if (k.run(1, &globalsize, &wgs, true))
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return res = saturate_cast<int>(cv::sum(db.getMat(ACCESS_READ))[0]), true;
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return false;
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}
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#endif
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#if defined HAVE_IPP
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static bool ipp_countNonZero( Mat &src, int &res )
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{
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CV_INSTRUMENT_REGION_IPP();
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#if IPP_VERSION_X100 < 201801
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// Poor performance of SSE42
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if(cv::ipp::getIppTopFeatures() == ippCPUID_SSE42)
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return false;
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#endif
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Ipp32s count = 0;
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int depth = src.depth();
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if(src.dims <= 2)
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{
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IppStatus status;
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IppiSize size = {src.cols*src.channels(), src.rows};
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if(depth == CV_8U)
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status = CV_INSTRUMENT_FUN_IPP(ippiCountInRange_8u_C1R, (const Ipp8u *)src.ptr(), (int)src.step, size, &count, 0, 0);
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else if(depth == CV_32F)
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status = CV_INSTRUMENT_FUN_IPP(ippiCountInRange_32f_C1R, (const Ipp32f *)src.ptr(), (int)src.step, size, &count, 0, 0);
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else
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return false;
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if(status < 0)
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return false;
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res = size.width*size.height - count;
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}
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else
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{
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IppStatus status;
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const Mat *arrays[] = {&src, NULL};
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Mat planes[1];
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NAryMatIterator it(arrays, planes, 1);
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IppiSize size = {(int)it.size*src.channels(), 1};
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res = 0;
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for (size_t i = 0; i < it.nplanes; i++, ++it)
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{
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if(depth == CV_8U)
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status = CV_INSTRUMENT_FUN_IPP(ippiCountInRange_8u_C1R, it.planes->ptr<Ipp8u>(), (int)it.planes->step, size, &count, 0, 0);
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else if(depth == CV_32F)
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status = CV_INSTRUMENT_FUN_IPP(ippiCountInRange_32f_C1R, it.planes->ptr<Ipp32f>(), (int)it.planes->step, size, &count, 0, 0);
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else
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return false;
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if(status < 0 || (int)it.planes->total()*src.channels() < count)
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return false;
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res += (int)it.planes->total()*src.channels() - count;
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}
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}
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return true;
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}
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#endif
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int countNonZero(InputArray _src)
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{
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CV_INSTRUMENT_REGION();
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int type = _src.type(), cn = CV_MAT_CN(type);
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CV_Assert( cn == 1 );
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#if defined HAVE_OPENCL || defined HAVE_IPP
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int res = -1;
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#endif
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#ifdef HAVE_OPENCL
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CV_OCL_RUN_(OCL_PERFORMANCE_CHECK(_src.isUMat()) && _src.dims() <= 2,
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ocl_countNonZero(_src, res),
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res)
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#endif
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Mat src = _src.getMat();
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CV_IPP_RUN_FAST(ipp_countNonZero(src, res), res);
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CountNonZeroFunc func = getCountNonZeroTab(src.depth());
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CV_Assert( func != 0 );
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const Mat* arrays[] = {&src, 0};
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uchar* ptrs[1] = {};
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NAryMatIterator it(arrays, ptrs);
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int total = (int)it.size, nz = 0;
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for( size_t i = 0; i < it.nplanes; i++, ++it )
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nz += func( ptrs[0], total );
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return nz;
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}
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void findNonZero(InputArray _src, OutputArray _idx)
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{
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CV_INSTRUMENT_REGION();
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Mat src = _src.getMat();
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CV_Assert( src.type() == CV_8UC1 );
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int n = countNonZero(src);
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if( n == 0 )
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{
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_idx.release();
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return;
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}
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if( _idx.kind() == _InputArray::MAT && !_idx.getMatRef().isContinuous() )
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_idx.release();
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_idx.create(n, 1, CV_32SC2);
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Mat idx = _idx.getMat();
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CV_Assert(idx.isContinuous());
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Point* idx_ptr = idx.ptr<Point>();
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for( int i = 0; i < src.rows; i++ )
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{
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const uchar* bin_ptr = src.ptr(i);
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for( int j = 0; j < src.cols; j++ )
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if( bin_ptr[j] )
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*idx_ptr++ = Point(j, i);
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}
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}
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} // namespace
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@ -2,13 +2,20 @@
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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 "stat.hpp"
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namespace cv {
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typedef int (*CountNonZeroFunc)(const uchar*, int);
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CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
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CountNonZeroFunc getCountNonZeroTab(int depth);
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#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
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template<typename T>
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static int countNonZero_(const T* src, int len )
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{
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@ -175,9 +182,7 @@ static int countNonZero64f( const double* src, int len )
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return countNonZero_(src, len);
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}
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typedef int (*CountNonZeroFunc)(const uchar*, int);
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static CountNonZeroFunc getCountNonZeroTab(int depth)
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CountNonZeroFunc getCountNonZeroTab(int depth)
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{
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static CountNonZeroFunc countNonZeroTab[] =
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{
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@ -190,164 +195,7 @@ static CountNonZeroFunc getCountNonZeroTab(int depth)
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return countNonZeroTab[depth];
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}
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#ifdef HAVE_OPENCL
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static bool ocl_countNonZero( InputArray _src, int & res )
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{
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int type = _src.type(), depth = CV_MAT_DEPTH(type), kercn = ocl::predictOptimalVectorWidth(_src);
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bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
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if (depth == CV_64F && !doubleSupport)
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return false;
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int dbsize = ocl::Device::getDefault().maxComputeUnits();
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size_t wgs = ocl::Device::getDefault().maxWorkGroupSize();
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int wgs2_aligned = 1;
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while (wgs2_aligned < (int)wgs)
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wgs2_aligned <<= 1;
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wgs2_aligned >>= 1;
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ocl::Kernel k("reduce", ocl::core::reduce_oclsrc,
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format("-D srcT=%s -D srcT1=%s -D cn=1 -D OP_COUNT_NON_ZERO"
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" -D WGS=%d -D kercn=%d -D WGS2_ALIGNED=%d%s%s",
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ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)),
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ocl::typeToStr(depth), (int)wgs, kercn,
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wgs2_aligned, doubleSupport ? " -D DOUBLE_SUPPORT" : "",
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_src.isContinuous() ? " -D HAVE_SRC_CONT" : ""));
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if (k.empty())
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return false;
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UMat src = _src.getUMat(), db(1, dbsize, CV_32SC1);
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k.args(ocl::KernelArg::ReadOnlyNoSize(src), src.cols, (int)src.total(),
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dbsize, ocl::KernelArg::PtrWriteOnly(db));
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size_t globalsize = dbsize * wgs;
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if (k.run(1, &globalsize, &wgs, true))
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return res = saturate_cast<int>(cv::sum(db.getMat(ACCESS_READ))[0]), true;
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return false;
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}
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#endif
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#if defined HAVE_IPP
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static bool ipp_countNonZero( Mat &src, int &res )
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{
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CV_INSTRUMENT_REGION_IPP();
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#if IPP_VERSION_X100 < 201801
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// Poor performance of SSE42
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if(cv::ipp::getIppTopFeatures() == ippCPUID_SSE42)
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return false;
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#endif
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Ipp32s count = 0;
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int depth = src.depth();
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if(src.dims <= 2)
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{
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IppStatus status;
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IppiSize size = {src.cols*src.channels(), src.rows};
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if(depth == CV_8U)
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status = CV_INSTRUMENT_FUN_IPP(ippiCountInRange_8u_C1R, (const Ipp8u *)src.ptr(), (int)src.step, size, &count, 0, 0);
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else if(depth == CV_32F)
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status = CV_INSTRUMENT_FUN_IPP(ippiCountInRange_32f_C1R, (const Ipp32f *)src.ptr(), (int)src.step, size, &count, 0, 0);
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else
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return false;
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if(status < 0)
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return false;
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res = size.width*size.height - count;
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}
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else
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{
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IppStatus status;
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const Mat *arrays[] = {&src, NULL};
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Mat planes[1];
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NAryMatIterator it(arrays, planes, 1);
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IppiSize size = {(int)it.size*src.channels(), 1};
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res = 0;
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for (size_t i = 0; i < it.nplanes; i++, ++it)
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{
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if(depth == CV_8U)
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status = CV_INSTRUMENT_FUN_IPP(ippiCountInRange_8u_C1R, it.planes->ptr<Ipp8u>(), (int)it.planes->step, size, &count, 0, 0);
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else if(depth == CV_32F)
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status = CV_INSTRUMENT_FUN_IPP(ippiCountInRange_32f_C1R, it.planes->ptr<Ipp32f>(), (int)it.planes->step, size, &count, 0, 0);
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else
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return false;
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if(status < 0 || (int)it.planes->total()*src.channels() < count)
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return false;
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res += (int)it.planes->total()*src.channels() - count;
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}
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}
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return true;
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}
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#endif
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} // cv::
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int cv::countNonZero( InputArray _src )
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{
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CV_INSTRUMENT_REGION();
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int type = _src.type(), cn = CV_MAT_CN(type);
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CV_Assert( cn == 1 );
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#if defined HAVE_OPENCL || defined HAVE_IPP
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int res = -1;
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#endif
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#ifdef HAVE_OPENCL
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CV_OCL_RUN_(OCL_PERFORMANCE_CHECK(_src.isUMat()) && _src.dims() <= 2,
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ocl_countNonZero(_src, res),
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res)
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#endif
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Mat src = _src.getMat();
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CV_IPP_RUN_FAST(ipp_countNonZero(src, res), res);
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CountNonZeroFunc func = getCountNonZeroTab(src.depth());
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CV_Assert( func != 0 );
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const Mat* arrays[] = {&src, 0};
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uchar* ptrs[1] = {};
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NAryMatIterator it(arrays, ptrs);
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int total = (int)it.size, nz = 0;
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for( size_t i = 0; i < it.nplanes; i++, ++it )
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nz += func( ptrs[0], total );
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return nz;
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}
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void cv::findNonZero( InputArray _src, OutputArray _idx )
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{
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CV_INSTRUMENT_REGION();
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Mat src = _src.getMat();
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CV_Assert( src.type() == CV_8UC1 );
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int n = countNonZero(src);
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if( n == 0 )
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{
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_idx.release();
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return;
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}
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if( _idx.kind() == _InputArray::MAT && !_idx.getMatRef().isContinuous() )
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_idx.release();
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_idx.create(n, 1, CV_32SC2);
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Mat idx = _idx.getMat();
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CV_Assert(idx.isContinuous());
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Point* idx_ptr = idx.ptr<Point>();
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for( int i = 0; i < src.rows; i++ )
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{
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const uchar* bin_ptr = src.ptr(i);
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for( int j = 0; j < src.cols; j++ )
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if( bin_ptr[j] )
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*idx_ptr++ = Point(j, i);
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}
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}
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CV_CPU_OPTIMIZATION_NAMESPACE_END
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} // namespace
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