/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "precomp.hpp" namespace cv { /****************************************************************************************\ * split & merge * \****************************************************************************************/ template static void split_( const T* src, T** dst, int len, int cn ) { int k = cn % 4 ? cn % 4 : 4; int i, j; if( k == 1 ) { T* dst0 = dst[0]; for( i = j = 0; i < len; i++, j += cn ) dst0[i] = src[j]; } else if( k == 2 ) { T *dst0 = dst[0], *dst1 = dst[1]; for( i = j = 0; i < len; i++, j += cn ) { dst0[i] = src[j]; dst1[i] = src[j+1]; } } else if( k == 3 ) { T *dst0 = dst[0], *dst1 = dst[1], *dst2 = dst[2]; for( i = j = 0; i < len; i++, j += cn ) { dst0[i] = src[j]; dst1[i] = src[j+1]; dst2[i] = src[j+2]; } } else { T *dst0 = dst[0], *dst1 = dst[1], *dst2 = dst[2], *dst3 = dst[3]; for( i = j = 0; i < len; i++, j += cn ) { dst0[i] = src[j]; dst1[i] = src[j+1]; dst2[i] = src[j+2]; dst3[i] = src[j+3]; } } for( ; k < cn; k += 4 ) { T *dst0 = dst[k], *dst1 = dst[k+1], *dst2 = dst[k+2], *dst3 = dst[k+3]; for( i = 0, j = k; i < len; i++, j += cn ) { dst0[i] = src[j]; dst1[i] = src[j+1]; dst2[i] = src[j+2]; dst3[i] = src[j+3]; } } } template static void merge_( const T** src, T* dst, int len, int cn ) { int k = cn % 4 ? cn % 4 : 4; int i, j; if( k == 1 ) { const T* src0 = src[0]; for( i = j = 0; i < len; i++, j += cn ) dst[j] = src0[i]; } else if( k == 2 ) { const T *src0 = src[0], *src1 = src[1]; for( i = j = 0; i < len; i++, j += cn ) { dst[j] = src0[i]; dst[j+1] = src1[i]; } } else if( k == 3 ) { const T *src0 = src[0], *src1 = src[1], *src2 = src[2]; for( i = j = 0; i < len; i++, j += cn ) { dst[j] = src0[i]; dst[j+1] = src1[i]; dst[j+2] = src2[i]; } } else { const T *src0 = src[0], *src1 = src[1], *src2 = src[2], *src3 = src[3]; for( i = j = 0; i < len; i++, j += cn ) { dst[j] = src0[i]; dst[j+1] = src1[i]; dst[j+2] = src2[i]; dst[j+3] = src3[i]; } } for( ; k < cn; k += 4 ) { const T *src0 = src[k], *src1 = src[k+1], *src2 = src[k+2], *src3 = src[k+3]; for( i = 0, j = k; i < len; i++, j += cn ) { dst[j] = src0[i]; dst[j+1] = src1[i]; dst[j+2] = src2[i]; dst[j+3] = src3[i]; } } } static void split8u(const uchar* src, uchar** dst, int len, int cn ) { split_(src, dst, len, cn); } static void split16u(const ushort* src, ushort** dst, int len, int cn ) { split_(src, dst, len, cn); } static void split32s(const int* src, int** dst, int len, int cn ) { split_(src, dst, len, cn); } static void split64s(const int64* src, int64** dst, int len, int cn ) { split_(src, dst, len, cn); } static void merge8u(const uchar** src, uchar* dst, int len, int cn ) { merge_(src, dst, len, cn); } static void merge16u(const ushort** src, ushort* dst, int len, int cn ) { merge_(src, dst, len, cn); } static void merge32s(const int** src, int* dst, int len, int cn ) { merge_(src, dst, len, cn); } static void merge64s(const int64** src, int64* dst, int len, int cn ) { merge_(src, dst, len, cn); } typedef void (*SplitFunc)(const uchar* src, uchar** dst, int len, int cn); typedef void (*MergeFunc)(const uchar** src, uchar* dst, int len, int cn); static SplitFunc splitTab[] = { (SplitFunc)GET_OPTIMIZED(split8u), (SplitFunc)GET_OPTIMIZED(split8u), (SplitFunc)GET_OPTIMIZED(split16u), (SplitFunc)GET_OPTIMIZED(split16u), (SplitFunc)GET_OPTIMIZED(split32s), (SplitFunc)GET_OPTIMIZED(split32s), (SplitFunc)GET_OPTIMIZED(split64s), 0 }; static MergeFunc mergeTab[] = { (MergeFunc)GET_OPTIMIZED(merge8u), (MergeFunc)GET_OPTIMIZED(merge8u), (MergeFunc)GET_OPTIMIZED(merge16u), (MergeFunc)GET_OPTIMIZED(merge16u), (MergeFunc)GET_OPTIMIZED(merge32s), (MergeFunc)GET_OPTIMIZED(merge32s), (MergeFunc)GET_OPTIMIZED(merge64s), 0 }; } void cv::split(const Mat& src, Mat* mv) { int k, depth = src.depth(), cn = src.channels(); if( cn == 1 ) { src.copyTo(mv[0]); return; } SplitFunc func = splitTab[depth]; CV_Assert( func != 0 ); int esz = (int)src.elemSize(), esz1 = (int)src.elemSize1(); int blocksize0 = (BLOCK_SIZE + esz-1)/esz; AutoBuffer _buf((cn+1)*(sizeof(Mat*) + sizeof(uchar*)) + 16); const Mat** arrays = (const Mat**)(uchar*)_buf; uchar** ptrs = (uchar**)alignPtr(arrays + cn + 1, 16); arrays[0] = &src; for( k = 0; k < cn; k++ ) { mv[k].create(src.dims, src.size, depth); arrays[k+1] = &mv[k]; } NAryMatIterator it(arrays, ptrs, cn+1); int total = (int)it.size, blocksize = cn <= 4 ? total : std::min(total, blocksize0); for( size_t i = 0; i < it.nplanes; i++, ++it ) { for( int j = 0; j < total; j += blocksize ) { int bsz = std::min(total - j, blocksize); func( ptrs[0], &ptrs[1], bsz, cn ); if( j + blocksize < total ) { ptrs[0] += bsz*esz; for( k = 0; k < cn; k++ ) ptrs[k+1] += bsz*esz1; } } } } void cv::split(InputArray _m, OutputArrayOfArrays _mv) { Mat m = _m.getMat(); if( m.empty() ) { _mv.release(); return; } CV_Assert( !_mv.fixedType() || CV_MAT_TYPE(_mv.flags) == m.depth() ); _mv.create(m.channels(), 1, m.depth()); Mat* dst = &_mv.getMatRef(0); split(m, dst); } void cv::merge(const Mat* mv, size_t n, OutputArray _dst) { CV_Assert( mv && n > 0 ); int depth = mv[0].depth(); bool allch1 = true; int k, cn = 0; size_t i; for( i = 0; i < n; i++ ) { CV_Assert(mv[i].size == mv[0].size && mv[i].depth() == depth); allch1 = allch1 && mv[i].channels() == 1; cn += mv[i].channels(); } CV_Assert( 0 < cn && cn <= CV_CN_MAX ); _dst.create(mv[0].dims, mv[0].size, CV_MAKETYPE(depth, cn)); Mat dst = _dst.getMat(); if( n == 1 ) { mv[0].copyTo(dst); return; } if( !allch1 ) { AutoBuffer pairs(cn*2); int j, ni=0; for( i = 0, j = 0; i < n; i++, j += ni ) { ni = mv[i].channels(); for( k = 0; k < ni; k++ ) { pairs[(j+k)*2] = j + k; pairs[(j+k)*2+1] = j + k; } } mixChannels( mv, n, &dst, 1, &pairs[0], cn ); return; } size_t esz = dst.elemSize(), esz1 = dst.elemSize1(); int blocksize0 = (int)((BLOCK_SIZE + esz-1)/esz); AutoBuffer _buf((cn+1)*(sizeof(Mat*) + sizeof(uchar*)) + 16); const Mat** arrays = (const Mat**)(uchar*)_buf; uchar** ptrs = (uchar**)alignPtr(arrays + cn + 1, 16); arrays[0] = &dst; for( k = 0; k < cn; k++ ) arrays[k+1] = &mv[k]; NAryMatIterator it(arrays, ptrs, cn+1); int total = (int)it.size, blocksize = cn <= 4 ? total : std::min(total, blocksize0); MergeFunc func = mergeTab[depth]; for( i = 0; i < it.nplanes; i++, ++it ) { for( int j = 0; j < total; j += blocksize ) { int bsz = std::min(total - j, blocksize); func( (const uchar**)&ptrs[1], ptrs[0], bsz, cn ); if( j + blocksize < total ) { ptrs[0] += bsz*esz; for( int t = 0; t < cn; t++ ) ptrs[t+1] += bsz*esz1; } } } } void cv::merge(InputArrayOfArrays _mv, OutputArray _dst) { vector mv; _mv.getMatVector(mv); merge(!mv.empty() ? &mv[0] : 0, mv.size(), _dst); } /****************************************************************************************\ * Generalized split/merge: mixing channels * \****************************************************************************************/ namespace cv { template static void mixChannels_( const T** src, const int* sdelta, T** dst, const int* ddelta, int len, int npairs ) { int i, k; for( k = 0; k < npairs; k++ ) { const T* s = src[k]; T* d = dst[k]; int ds = sdelta[k], dd = ddelta[k]; if( s ) { for( i = 0; i <= len - 2; i += 2, s += ds*2, d += dd*2 ) { T t0 = s[0], t1 = s[ds]; d[0] = t0; d[dd] = t1; } if( i < len ) d[0] = s[0]; } else { for( i = 0; i <= len - 2; i += 2, d += dd*2 ) d[0] = d[dd] = 0; if( i < len ) d[0] = 0; } } } static void mixChannels8u( const uchar** src, const int* sdelta, uchar** dst, const int* ddelta, int len, int npairs ) { mixChannels_(src, sdelta, dst, ddelta, len, npairs); } static void mixChannels16u( const ushort** src, const int* sdelta, ushort** dst, const int* ddelta, int len, int npairs ) { mixChannels_(src, sdelta, dst, ddelta, len, npairs); } static void mixChannels32s( const int** src, const int* sdelta, int** dst, const int* ddelta, int len, int npairs ) { mixChannels_(src, sdelta, dst, ddelta, len, npairs); } static void mixChannels64s( const int64** src, const int* sdelta, int64** dst, const int* ddelta, int len, int npairs ) { mixChannels_(src, sdelta, dst, ddelta, len, npairs); } typedef void (*MixChannelsFunc)( const uchar** src, const int* sdelta, uchar** dst, const int* ddelta, int len, int npairs ); static MixChannelsFunc mixchTab[] = { (MixChannelsFunc)mixChannels8u, (MixChannelsFunc)mixChannels8u, (MixChannelsFunc)mixChannels16u, (MixChannelsFunc)mixChannels16u, (MixChannelsFunc)mixChannels32s, (MixChannelsFunc)mixChannels32s, (MixChannelsFunc)mixChannels64s, 0 }; } void cv::mixChannels( const Mat* src, size_t nsrcs, Mat* dst, size_t ndsts, const int* fromTo, size_t npairs ) { if( npairs == 0 ) return; CV_Assert( src && nsrcs > 0 && dst && ndsts > 0 && fromTo && npairs > 0 ); size_t i, j, k, esz1 = dst[0].elemSize1(); int depth = dst[0].depth(); AutoBuffer buf((nsrcs + ndsts + 1)*(sizeof(Mat*) + sizeof(uchar*)) + npairs*(sizeof(uchar*)*2 + sizeof(int)*6)); const Mat** arrays = (const Mat**)(uchar*)buf; uchar** ptrs = (uchar**)(arrays + nsrcs + ndsts); const uchar** srcs = (const uchar**)(ptrs + nsrcs + ndsts + 1); uchar** dsts = (uchar**)(srcs + npairs); int* tab = (int*)(dsts + npairs); int *sdelta = (int*)(tab + npairs*4), *ddelta = sdelta + npairs; for( i = 0; i < nsrcs; i++ ) arrays[i] = &src[i]; for( i = 0; i < ndsts; i++ ) arrays[i + nsrcs] = &dst[i]; ptrs[nsrcs + ndsts] = 0; for( i = 0; i < npairs; i++ ) { int i0 = fromTo[i*2], i1 = fromTo[i*2+1]; if( i0 >= 0 ) { for( j = 0; j < nsrcs; i0 -= src[j].channels(), j++ ) if( i0 < src[j].channels() ) break; CV_Assert(j < nsrcs && src[j].depth() == depth); tab[i*4] = (int)j; tab[i*4+1] = (int)(i0*esz1); sdelta[i] = src[j].channels(); } else { tab[i*4] = (int)(nsrcs + ndsts); tab[i*4+1] = 0; sdelta[i] = 0; } for( j = 0; j < ndsts; i1 -= dst[j].channels(), j++ ) if( i1 < dst[j].channels() ) break; CV_Assert(i1 >= 0 && j < ndsts && dst[j].depth() == depth); tab[i*4+2] = (int)(j + nsrcs); tab[i*4+3] = (int)(i1*esz1); ddelta[i] = dst[j].channels(); } NAryMatIterator it(arrays, ptrs, (int)(nsrcs + ndsts)); int total = (int)it.size, blocksize = std::min(total, (int)((BLOCK_SIZE + esz1-1)/esz1)); MixChannelsFunc func = mixchTab[depth]; for( i = 0; i < it.nplanes; i++, ++it ) { for( k = 0; k < npairs; k++ ) { srcs[k] = ptrs[tab[k*4]] + tab[k*4+1]; dsts[k] = ptrs[tab[k*4+2]] + tab[k*4+3]; } for( int t = 0; t < total; t += blocksize ) { int bsz = std::min(total - t, blocksize); func( srcs, sdelta, dsts, ddelta, bsz, (int)npairs ); if( t + blocksize < total ) for( k = 0; k < npairs; k++ ) { srcs[k] += blocksize*sdelta[k]*esz1; dsts[k] += blocksize*ddelta[k]*esz1; } } } } void cv::mixChannels(const vector& src, vector& dst, const int* fromTo, size_t npairs) { mixChannels(!src.empty() ? &src[0] : 0, src.size(), !dst.empty() ? &dst[0] : 0, dst.size(), fromTo, npairs); } void cv::mixChannels(InputArrayOfArrays src, InputArrayOfArrays dst, const vector& fromTo) { if(fromTo.empty()) return; bool src_is_mat = src.kind() != _InputArray::STD_VECTOR_MAT && src.kind() != _InputArray::STD_VECTOR_VECTOR; bool dst_is_mat = dst.kind() != _InputArray::STD_VECTOR_MAT && dst.kind() != _InputArray::STD_VECTOR_VECTOR; int i; int nsrc = src_is_mat ? 1 : (int)src.total(); int ndst = dst_is_mat ? 1 : (int)dst.total(); CV_Assert(fromTo.size()%2 == 0 && nsrc > 0 && ndst > 0); cv::AutoBuffer _buf(nsrc + ndst); Mat* buf = _buf; for( i = 0; i < nsrc; i++ ) buf[i] = src.getMat(src_is_mat ? -1 : i); for( i = 0; i < ndst; i++ ) buf[nsrc + i] = dst.getMat(dst_is_mat ? -1 : i); mixChannels(&buf[0], nsrc, &buf[nsrc], ndst, &fromTo[0], fromTo.size()/2); } void cv::extractChannel(InputArray _src, OutputArray _dst, int coi) { Mat src = _src.getMat(); CV_Assert( 0 <= coi && coi < src.channels() ); _dst.create(src.dims, &src.size[0], src.depth()); Mat dst = _dst.getMat(); int ch[] = { coi, 0 }; mixChannels(&src, 1, &dst, 1, ch, 1); } void cv::insertChannel(InputArray _src, InputOutputArray _dst, int coi) { Mat src = _src.getMat(), dst = _dst.getMat(); CV_Assert( src.size == dst.size && src.depth() == dst.depth() ); CV_Assert( 0 <= coi && coi < dst.channels() && src.channels() == 1 ); int ch[] = { 0, coi }; mixChannels(&src, 1, &dst, 1, ch, 1); } /****************************************************************************************\ * convertScale[Abs] * \****************************************************************************************/ namespace cv { template static void cvtScaleAbs_( const T* src, size_t sstep, DT* dst, size_t dstep, Size size, WT scale, WT shift ) { sstep /= sizeof(src[0]); dstep /= sizeof(dst[0]); for( ; size.height--; src += sstep, dst += dstep ) { int x = 0; #if CV_ENABLE_UNROLLED for( ; x <= size.width - 4; x += 4 ) { DT t0, t1; t0 = saturate_cast
(std::abs(src[x]*scale + shift)); t1 = saturate_cast
(std::abs(src[x+1]*scale + shift)); dst[x] = t0; dst[x+1] = t1; t0 = saturate_cast
(std::abs(src[x+2]*scale + shift)); t1 = saturate_cast
(std::abs(src[x+3]*scale + shift)); dst[x+2] = t0; dst[x+3] = t1; } #endif for( ; x < size.width; x++ ) dst[x] = saturate_cast
(std::abs(src[x]*scale + shift)); } } template static void cvtScale_( const T* src, size_t sstep, DT* dst, size_t dstep, Size size, WT scale, WT shift ) { sstep /= sizeof(src[0]); dstep /= sizeof(dst[0]); for( ; size.height--; src += sstep, dst += dstep ) { int x = 0; #if CV_ENABLE_UNROLLED for( ; x <= size.width - 4; x += 4 ) { DT t0, t1; t0 = saturate_cast
(src[x]*scale + shift); t1 = saturate_cast
(src[x+1]*scale + shift); dst[x] = t0; dst[x+1] = t1; t0 = saturate_cast
(src[x+2]*scale + shift); t1 = saturate_cast
(src[x+3]*scale + shift); dst[x+2] = t0; dst[x+3] = t1; } #endif for( ; x < size.width; x++ ) dst[x] = saturate_cast
(src[x]*scale + shift); } } //vz optimized template specialization template<> void cvtScale_( const short* src, size_t sstep, short* dst, size_t dstep, Size size, float scale, float shift ) { sstep /= sizeof(src[0]); dstep /= sizeof(dst[0]); for( ; size.height--; src += sstep, dst += dstep ) { int x = 0; #if CV_SSE2 if(USE_SSE2) { __m128 scale128 = _mm_set1_ps (scale); __m128 shift128 = _mm_set1_ps (shift); for(; x <= size.width - 8; x += 8 ) { __m128i r0 = _mm_loadl_epi64((const __m128i*)(src + x)); __m128i r1 = _mm_loadl_epi64((const __m128i*)(src + x + 4)); __m128 rf0 =_mm_cvtepi32_ps(_mm_srai_epi32(_mm_unpacklo_epi16(r0, r0), 16)); __m128 rf1 =_mm_cvtepi32_ps(_mm_srai_epi32(_mm_unpacklo_epi16(r1, r1), 16)); rf0 = _mm_add_ps(_mm_mul_ps(rf0, scale128), shift128); rf1 = _mm_add_ps(_mm_mul_ps(rf1, scale128), shift128); r0 = _mm_cvtps_epi32(rf0); r1 = _mm_cvtps_epi32(rf1); r0 = _mm_packs_epi32(r0, r1); _mm_storeu_si128((__m128i*)(dst + x), r0); } } #endif for(; x < size.width; x++ ) dst[x] = saturate_cast(src[x]*scale + shift); } } template<> void cvtScale_( const short* src, size_t sstep, int* dst, size_t dstep, Size size, float scale, float shift ) { sstep /= sizeof(src[0]); dstep /= sizeof(dst[0]); for( ; size.height--; src += sstep, dst += dstep ) { int x = 0; #if CV_SSE2 if(USE_SSE2)//~5X { __m128 scale128 = _mm_set1_ps (scale); __m128 shift128 = _mm_set1_ps (shift); for(; x <= size.width - 8; x += 8 ) { __m128i r0 = _mm_loadl_epi64((const __m128i*)(src + x)); __m128i r1 = _mm_loadl_epi64((const __m128i*)(src + x + 4)); __m128 rf0 =_mm_cvtepi32_ps(_mm_srai_epi32(_mm_unpacklo_epi16(r0, r0), 16)); __m128 rf1 =_mm_cvtepi32_ps(_mm_srai_epi32(_mm_unpacklo_epi16(r1, r1), 16)); rf0 = _mm_add_ps(_mm_mul_ps(rf0, scale128), shift128); rf1 = _mm_add_ps(_mm_mul_ps(rf1, scale128), shift128); r0 = _mm_cvtps_epi32(rf0); r1 = _mm_cvtps_epi32(rf1); _mm_storeu_si128((__m128i*)(dst + x), r0); _mm_storeu_si128((__m128i*)(dst + x + 4), r1); } } #endif //We will wait Haswell /* #if CV_AVX if(USE_AVX)//2X - bad variant { ////TODO:AVX implementation (optimization?) required __m256 scale256 = _mm256_set1_ps (scale); __m256 shift256 = _mm256_set1_ps (shift); for(; x <= size.width - 8; x += 8 ) { __m256i buf = _mm256_set_epi32((int)(*(src+x+7)),(int)(*(src+x+6)),(int)(*(src+x+5)),(int)(*(src+x+4)),(int)(*(src+x+3)),(int)(*(src+x+2)),(int)(*(src+x+1)),(int)(*(src+x))); __m256 r0 = _mm256_add_ps( _mm256_mul_ps(_mm256_cvtepi32_ps (buf), scale256), shift256); __m256i res = _mm256_cvtps_epi32(r0); _mm256_storeu_si256 ((__m256i*)(dst+x), res); } } #endif*/ for(; x < size.width; x++ ) dst[x] = saturate_cast(src[x]*scale + shift); } } template static void cvt_( const T* src, size_t sstep, DT* dst, size_t dstep, Size size ) { sstep /= sizeof(src[0]); dstep /= sizeof(dst[0]); for( ; size.height--; src += sstep, dst += dstep ) { int x = 0; #if CV_ENABLE_UNROLLED for( ; x <= size.width - 4; x += 4 ) { DT t0, t1; t0 = saturate_cast
(src[x]); t1 = saturate_cast
(src[x+1]); dst[x] = t0; dst[x+1] = t1; t0 = saturate_cast
(src[x+2]); t1 = saturate_cast
(src[x+3]); dst[x+2] = t0; dst[x+3] = t1; } #endif for( ; x < size.width; x++ ) dst[x] = saturate_cast
(src[x]); } } //vz optimized template specialization, test Core_ConvertScale/ElemWiseTest template<> void cvt_( const float* src, size_t sstep, short* dst, size_t dstep, Size size ) { sstep /= sizeof(src[0]); dstep /= sizeof(dst[0]); for( ; size.height--; src += sstep, dst += dstep ) { int x = 0; #if CV_SSE2 if(USE_SSE2){ for( ; x <= size.width - 8; x += 8 ) { __m128 src128 = _mm_loadu_ps (src + x); __m128i src_int128 = _mm_cvtps_epi32 (src128); src128 = _mm_loadu_ps (src + x + 4); __m128i src1_int128 = _mm_cvtps_epi32 (src128); src1_int128 = _mm_packs_epi32(src_int128, src1_int128); _mm_storeu_si128((__m128i*)(dst + x),src1_int128); } } #endif for( ; x < size.width; x++ ) dst[x] = saturate_cast(src[x]); } } template static void cpy_( const T* src, size_t sstep, T* dst, size_t dstep, Size size ) { sstep /= sizeof(src[0]); dstep /= sizeof(dst[0]); for( ; size.height--; src += sstep, dst += dstep ) memcpy(dst, src, size.width*sizeof(src[0])); } #define DEF_CVT_SCALE_ABS_FUNC(suffix, tfunc, stype, dtype, wtype) \ static void cvtScaleAbs##suffix( const stype* src, size_t sstep, const uchar*, size_t, \ dtype* dst, size_t dstep, Size size, double* scale) \ { \ tfunc(src, sstep, dst, dstep, size, (wtype)scale[0], (wtype)scale[1]); \ } #define DEF_CVT_SCALE_FUNC(suffix, stype, dtype, wtype) \ static void cvtScale##suffix( const stype* src, size_t sstep, const uchar*, size_t, \ dtype* dst, size_t dstep, Size size, double* scale) \ { \ cvtScale_(src, sstep, dst, dstep, size, (wtype)scale[0], (wtype)scale[1]); \ } #define DEF_CVT_FUNC(suffix, stype, dtype) \ static void cvt##suffix( const stype* src, size_t sstep, const uchar*, size_t, \ dtype* dst, size_t dstep, Size size, double*) \ { \ cvt_(src, sstep, dst, dstep, size); \ } #define DEF_CPY_FUNC(suffix, stype) \ static void cvt##suffix( const stype* src, size_t sstep, const uchar*, size_t, \ stype* dst, size_t dstep, Size size, double*) \ { \ cpy_(src, sstep, dst, dstep, size); \ } DEF_CVT_SCALE_ABS_FUNC(8u, cvtScaleAbs_, uchar, uchar, float); DEF_CVT_SCALE_ABS_FUNC(8s8u, cvtScaleAbs_, schar, uchar, float); DEF_CVT_SCALE_ABS_FUNC(16u8u, cvtScaleAbs_, ushort, uchar, float); DEF_CVT_SCALE_ABS_FUNC(16s8u, cvtScaleAbs_, short, uchar, float); DEF_CVT_SCALE_ABS_FUNC(32s8u, cvtScaleAbs_, int, uchar, float); DEF_CVT_SCALE_ABS_FUNC(32f8u, cvtScaleAbs_, float, uchar, float); DEF_CVT_SCALE_ABS_FUNC(64f8u, cvtScaleAbs_, double, uchar, float); DEF_CVT_SCALE_FUNC(8u, uchar, uchar, float); DEF_CVT_SCALE_FUNC(8s8u, schar, uchar, float); DEF_CVT_SCALE_FUNC(16u8u, ushort, uchar, float); DEF_CVT_SCALE_FUNC(16s8u, short, uchar, float); DEF_CVT_SCALE_FUNC(32s8u, int, uchar, float); DEF_CVT_SCALE_FUNC(32f8u, float, uchar, float); DEF_CVT_SCALE_FUNC(64f8u, double, uchar, float); DEF_CVT_SCALE_FUNC(8u8s, uchar, schar, float); DEF_CVT_SCALE_FUNC(8s, schar, schar, float); DEF_CVT_SCALE_FUNC(16u8s, ushort, schar, float); DEF_CVT_SCALE_FUNC(16s8s, short, schar, float); DEF_CVT_SCALE_FUNC(32s8s, int, schar, float); DEF_CVT_SCALE_FUNC(32f8s, float, schar, float); DEF_CVT_SCALE_FUNC(64f8s, double, schar, float); DEF_CVT_SCALE_FUNC(8u16u, uchar, ushort, float); DEF_CVT_SCALE_FUNC(8s16u, schar, ushort, float); DEF_CVT_SCALE_FUNC(16u, ushort, ushort, float); DEF_CVT_SCALE_FUNC(16s16u, short, ushort, float); DEF_CVT_SCALE_FUNC(32s16u, int, ushort, float); DEF_CVT_SCALE_FUNC(32f16u, float, ushort, float); DEF_CVT_SCALE_FUNC(64f16u, double, ushort, float); DEF_CVT_SCALE_FUNC(8u16s, uchar, short, float); DEF_CVT_SCALE_FUNC(8s16s, schar, short, float); DEF_CVT_SCALE_FUNC(16u16s, ushort, short, float); DEF_CVT_SCALE_FUNC(16s, short, short, float); DEF_CVT_SCALE_FUNC(32s16s, int, short, float); DEF_CVT_SCALE_FUNC(32f16s, float, short, float); DEF_CVT_SCALE_FUNC(64f16s, double, short, float); DEF_CVT_SCALE_FUNC(8u32s, uchar, int, float); DEF_CVT_SCALE_FUNC(8s32s, schar, int, float); DEF_CVT_SCALE_FUNC(16u32s, ushort, int, float); DEF_CVT_SCALE_FUNC(16s32s, short, int, float); DEF_CVT_SCALE_FUNC(32s, int, int, double); DEF_CVT_SCALE_FUNC(32f32s, float, int, float); DEF_CVT_SCALE_FUNC(64f32s, double, int, double); DEF_CVT_SCALE_FUNC(8u32f, uchar, float, float); DEF_CVT_SCALE_FUNC(8s32f, schar, float, float); DEF_CVT_SCALE_FUNC(16u32f, ushort, float, float); DEF_CVT_SCALE_FUNC(16s32f, short, float, float); DEF_CVT_SCALE_FUNC(32s32f, int, float, double); DEF_CVT_SCALE_FUNC(32f, float, float, float); DEF_CVT_SCALE_FUNC(64f32f, double, float, double); DEF_CVT_SCALE_FUNC(8u64f, uchar, double, double); DEF_CVT_SCALE_FUNC(8s64f, schar, double, double); DEF_CVT_SCALE_FUNC(16u64f, ushort, double, double); DEF_CVT_SCALE_FUNC(16s64f, short, double, double); DEF_CVT_SCALE_FUNC(32s64f, int, double, double); DEF_CVT_SCALE_FUNC(32f64f, float, double, double); DEF_CVT_SCALE_FUNC(64f, double, double, double); DEF_CPY_FUNC(8u, uchar); DEF_CVT_FUNC(8s8u, schar, uchar); DEF_CVT_FUNC(16u8u, ushort, uchar); DEF_CVT_FUNC(16s8u, short, uchar); DEF_CVT_FUNC(32s8u, int, uchar); DEF_CVT_FUNC(32f8u, float, uchar); DEF_CVT_FUNC(64f8u, double, uchar); DEF_CVT_FUNC(8u8s, uchar, schar); DEF_CVT_FUNC(16u8s, ushort, schar); DEF_CVT_FUNC(16s8s, short, schar); DEF_CVT_FUNC(32s8s, int, schar); DEF_CVT_FUNC(32f8s, float, schar); DEF_CVT_FUNC(64f8s, double, schar); DEF_CVT_FUNC(8u16u, uchar, ushort); DEF_CVT_FUNC(8s16u, schar, ushort); DEF_CPY_FUNC(16u, ushort); DEF_CVT_FUNC(16s16u, short, ushort); DEF_CVT_FUNC(32s16u, int, ushort); DEF_CVT_FUNC(32f16u, float, ushort); DEF_CVT_FUNC(64f16u, double, ushort); DEF_CVT_FUNC(8u16s, uchar, short); DEF_CVT_FUNC(8s16s, schar, short); DEF_CVT_FUNC(16u16s, ushort, short); DEF_CVT_FUNC(32s16s, int, short); DEF_CVT_FUNC(32f16s, float, short); DEF_CVT_FUNC(64f16s, double, short); DEF_CVT_FUNC(8u32s, uchar, int); DEF_CVT_FUNC(8s32s, schar, int); DEF_CVT_FUNC(16u32s, ushort, int); DEF_CVT_FUNC(16s32s, short, int); DEF_CPY_FUNC(32s, int); DEF_CVT_FUNC(32f32s, float, int); DEF_CVT_FUNC(64f32s, double, int); DEF_CVT_FUNC(8u32f, uchar, float); DEF_CVT_FUNC(8s32f, schar, float); DEF_CVT_FUNC(16u32f, ushort, float); DEF_CVT_FUNC(16s32f, short, float); DEF_CVT_FUNC(32s32f, int, float); DEF_CVT_FUNC(64f32f, double, float); DEF_CVT_FUNC(8u64f, uchar, double); DEF_CVT_FUNC(8s64f, schar, double); DEF_CVT_FUNC(16u64f, ushort, double); DEF_CVT_FUNC(16s64f, short, double); DEF_CVT_FUNC(32s64f, int, double); DEF_CVT_FUNC(32f64f, float, double); DEF_CPY_FUNC(64s, int64); static BinaryFunc cvtScaleAbsTab[] = { (BinaryFunc)cvtScaleAbs8u, (BinaryFunc)cvtScaleAbs8s8u, (BinaryFunc)cvtScaleAbs16u8u, (BinaryFunc)cvtScaleAbs16s8u, (BinaryFunc)cvtScaleAbs32s8u, (BinaryFunc)cvtScaleAbs32f8u, (BinaryFunc)cvtScaleAbs64f8u, 0 }; static BinaryFunc cvtScaleTab[][8] = { { (BinaryFunc)GET_OPTIMIZED(cvtScale8u), (BinaryFunc)GET_OPTIMIZED(cvtScale8s8u), (BinaryFunc)GET_OPTIMIZED(cvtScale16u8u), (BinaryFunc)GET_OPTIMIZED(cvtScale16s8u), (BinaryFunc)GET_OPTIMIZED(cvtScale32s8u), (BinaryFunc)GET_OPTIMIZED(cvtScale32f8u), (BinaryFunc)cvtScale64f8u, 0 }, { (BinaryFunc)GET_OPTIMIZED(cvtScale8u8s), (BinaryFunc)GET_OPTIMIZED(cvtScale8s), (BinaryFunc)GET_OPTIMIZED(cvtScale16u8s), (BinaryFunc)GET_OPTIMIZED(cvtScale16s8s), (BinaryFunc)GET_OPTIMIZED(cvtScale32s8s), (BinaryFunc)GET_OPTIMIZED(cvtScale32f8s), (BinaryFunc)cvtScale64f8s, 0 }, { (BinaryFunc)GET_OPTIMIZED(cvtScale8u16u), (BinaryFunc)GET_OPTIMIZED(cvtScale8s16u), (BinaryFunc)GET_OPTIMIZED(cvtScale16u), (BinaryFunc)GET_OPTIMIZED(cvtScale16s16u), (BinaryFunc)GET_OPTIMIZED(cvtScale32s16u), (BinaryFunc)GET_OPTIMIZED(cvtScale32f16u), (BinaryFunc)cvtScale64f16u, 0 }, { (BinaryFunc)GET_OPTIMIZED(cvtScale8u16s), (BinaryFunc)GET_OPTIMIZED(cvtScale8s16s), (BinaryFunc)GET_OPTIMIZED(cvtScale16u16s), (BinaryFunc)GET_OPTIMIZED(cvtScale16s), (BinaryFunc)GET_OPTIMIZED(cvtScale32s16s), (BinaryFunc)GET_OPTIMIZED(cvtScale32f16s), (BinaryFunc)cvtScale64f16s, 0 }, { (BinaryFunc)GET_OPTIMIZED(cvtScale8u32s), (BinaryFunc)GET_OPTIMIZED(cvtScale8s32s), (BinaryFunc)GET_OPTIMIZED(cvtScale16u32s), (BinaryFunc)GET_OPTIMIZED(cvtScale16s32s), (BinaryFunc)GET_OPTIMIZED(cvtScale32s), (BinaryFunc)GET_OPTIMIZED(cvtScale32f32s), (BinaryFunc)cvtScale64f32s, 0 }, { (BinaryFunc)GET_OPTIMIZED(cvtScale8u32f), (BinaryFunc)GET_OPTIMIZED(cvtScale8s32f), (BinaryFunc)GET_OPTIMIZED(cvtScale16u32f), (BinaryFunc)GET_OPTIMIZED(cvtScale16s32f), (BinaryFunc)GET_OPTIMIZED(cvtScale32s32f), (BinaryFunc)GET_OPTIMIZED(cvtScale32f), (BinaryFunc)cvtScale64f32f, 0 }, { (BinaryFunc)cvtScale8u64f, (BinaryFunc)cvtScale8s64f, (BinaryFunc)cvtScale16u64f, (BinaryFunc)cvtScale16s64f, (BinaryFunc)cvtScale32s64f, (BinaryFunc)cvtScale32f64f, (BinaryFunc)cvtScale64f, 0 }, { 0, 0, 0, 0, 0, 0, 0, 0 } }; static BinaryFunc cvtTab[][8] = { { (BinaryFunc)(cvt8u), (BinaryFunc)GET_OPTIMIZED(cvt8s8u), (BinaryFunc)GET_OPTIMIZED(cvt16u8u), (BinaryFunc)GET_OPTIMIZED(cvt16s8u), (BinaryFunc)GET_OPTIMIZED(cvt32s8u), (BinaryFunc)GET_OPTIMIZED(cvt32f8u), (BinaryFunc)GET_OPTIMIZED(cvt64f8u), 0 }, { (BinaryFunc)GET_OPTIMIZED(cvt8u8s), (BinaryFunc)cvt8u, (BinaryFunc)GET_OPTIMIZED(cvt16u8s), (BinaryFunc)GET_OPTIMIZED(cvt16s8s), (BinaryFunc)GET_OPTIMIZED(cvt32s8s), (BinaryFunc)GET_OPTIMIZED(cvt32f8s), (BinaryFunc)GET_OPTIMIZED(cvt64f8s), 0 }, { (BinaryFunc)GET_OPTIMIZED(cvt8u16u), (BinaryFunc)GET_OPTIMIZED(cvt8s16u), (BinaryFunc)cvt16u, (BinaryFunc)GET_OPTIMIZED(cvt16s16u), (BinaryFunc)GET_OPTIMIZED(cvt32s16u), (BinaryFunc)GET_OPTIMIZED(cvt32f16u), (BinaryFunc)GET_OPTIMIZED(cvt64f16u), 0 }, { (BinaryFunc)GET_OPTIMIZED(cvt8u16s), (BinaryFunc)GET_OPTIMIZED(cvt8s16s), (BinaryFunc)GET_OPTIMIZED(cvt16u16s), (BinaryFunc)cvt16u, (BinaryFunc)GET_OPTIMIZED(cvt32s16s), (BinaryFunc)GET_OPTIMIZED(cvt32f16s), (BinaryFunc)GET_OPTIMIZED(cvt64f16s), 0 }, { (BinaryFunc)GET_OPTIMIZED(cvt8u32s), (BinaryFunc)GET_OPTIMIZED(cvt8s32s), (BinaryFunc)GET_OPTIMIZED(cvt16u32s), (BinaryFunc)GET_OPTIMIZED(cvt16s32s), (BinaryFunc)cvt32s, (BinaryFunc)GET_OPTIMIZED(cvt32f32s), (BinaryFunc)GET_OPTIMIZED(cvt64f32s), 0 }, { (BinaryFunc)GET_OPTIMIZED(cvt8u32f), (BinaryFunc)GET_OPTIMIZED(cvt8s32f), (BinaryFunc)GET_OPTIMIZED(cvt16u32f), (BinaryFunc)GET_OPTIMIZED(cvt16s32f), (BinaryFunc)GET_OPTIMIZED(cvt32s32f), (BinaryFunc)cvt32s, (BinaryFunc)GET_OPTIMIZED(cvt64f32f), 0 }, { (BinaryFunc)GET_OPTIMIZED(cvt8u64f), (BinaryFunc)GET_OPTIMIZED(cvt8s64f), (BinaryFunc)GET_OPTIMIZED(cvt16u64f), (BinaryFunc)GET_OPTIMIZED(cvt16s64f), (BinaryFunc)GET_OPTIMIZED(cvt32s64f), (BinaryFunc)GET_OPTIMIZED(cvt32f64f), (BinaryFunc)(cvt64s), 0 }, { 0, 0, 0, 0, 0, 0, 0, 0 } }; BinaryFunc getConvertFunc(int sdepth, int ddepth) { return cvtTab[CV_MAT_DEPTH(ddepth)][CV_MAT_DEPTH(sdepth)]; } BinaryFunc getConvertScaleFunc(int sdepth, int ddepth) { return cvtScaleTab[CV_MAT_DEPTH(ddepth)][CV_MAT_DEPTH(sdepth)]; } } void cv::convertScaleAbs( InputArray _src, OutputArray _dst, double alpha, double beta ) { Mat src = _src.getMat(); int cn = src.channels(); double scale[] = {alpha, beta}; _dst.create( src.dims, src.size, CV_8UC(cn) ); Mat dst = _dst.getMat(); BinaryFunc func = cvtScaleAbsTab[src.depth()]; CV_Assert( func != 0 ); if( src.dims <= 2 ) { Size sz = getContinuousSize(src, dst, cn); func( src.data, src.step, 0, 0, dst.data, dst.step, sz, scale ); } else { const Mat* arrays[] = {&src, &dst, 0}; uchar* ptrs[2]; NAryMatIterator it(arrays, ptrs); Size sz((int)it.size*cn, 1); for( size_t i = 0; i < it.nplanes; i++, ++it ) func( ptrs[0], 0, 0, 0, ptrs[1], 0, sz, scale ); } } void cv::Mat::convertTo(OutputArray _dst, int _type, double alpha, double beta) const { bool noScale = fabs(alpha-1) < DBL_EPSILON && fabs(beta) < DBL_EPSILON; if( _type < 0 ) _type = _dst.fixedType() ? _dst.type() : type(); else _type = CV_MAKETYPE(CV_MAT_DEPTH(_type), channels()); int sdepth = depth(), ddepth = CV_MAT_DEPTH(_type); if( sdepth == ddepth && noScale ) { copyTo(_dst); return; } Mat src = *this; BinaryFunc func = noScale ? getConvertFunc(sdepth, ddepth) : getConvertScaleFunc(sdepth, ddepth); double scale[] = {alpha, beta}; int cn = channels(); CV_Assert( func != 0 ); if( dims <= 2 ) { _dst.create( size(), _type ); Mat dst = _dst.getMat(); Size sz = getContinuousSize(src, dst, cn); func( src.data, src.step, 0, 0, dst.data, dst.step, sz, scale ); } else { _dst.create( dims, size, _type ); Mat dst = _dst.getMat(); const Mat* arrays[] = {&src, &dst, 0}; uchar* ptrs[2]; NAryMatIterator it(arrays, ptrs); Size sz((int)(it.size*cn), 1); for( size_t i = 0; i < it.nplanes; i++, ++it ) func(ptrs[0], 0, 0, 0, ptrs[1], 0, sz, scale); } } /****************************************************************************************\ * LUT Transform * \****************************************************************************************/ namespace cv { template static void LUT8u_( const uchar* src, const T* lut, T* dst, int len, int cn, int lutcn ) { if( lutcn == 1 ) { for( int i = 0; i < len*cn; i++ ) dst[i] = lut[src[i]]; } else { for( int i = 0; i < len*cn; i += cn ) for( int k = 0; k < cn; k++ ) dst[i+k] = lut[src[i+k]*cn+k]; } } static void LUT8u_8u( const uchar* src, const uchar* lut, uchar* dst, int len, int cn, int lutcn ) { LUT8u_( src, lut, dst, len, cn, lutcn ); } static void LUT8u_8s( const uchar* src, const schar* lut, schar* dst, int len, int cn, int lutcn ) { LUT8u_( src, lut, dst, len, cn, lutcn ); } static void LUT8u_16u( const uchar* src, const ushort* lut, ushort* dst, int len, int cn, int lutcn ) { LUT8u_( src, lut, dst, len, cn, lutcn ); } static void LUT8u_16s( const uchar* src, const short* lut, short* dst, int len, int cn, int lutcn ) { LUT8u_( src, lut, dst, len, cn, lutcn ); } static void LUT8u_32s( const uchar* src, const int* lut, int* dst, int len, int cn, int lutcn ) { LUT8u_( src, lut, dst, len, cn, lutcn ); } static void LUT8u_32f( const uchar* src, const float* lut, float* dst, int len, int cn, int lutcn ) { LUT8u_( src, lut, dst, len, cn, lutcn ); } static void LUT8u_64f( const uchar* src, const double* lut, double* dst, int len, int cn, int lutcn ) { LUT8u_( src, lut, dst, len, cn, lutcn ); } typedef void (*LUTFunc)( const uchar* src, const uchar* lut, uchar* dst, int len, int cn, int lutcn ); static LUTFunc lutTab[] = { (LUTFunc)LUT8u_8u, (LUTFunc)LUT8u_8s, (LUTFunc)LUT8u_16u, (LUTFunc)LUT8u_16s, (LUTFunc)LUT8u_32s, (LUTFunc)LUT8u_32f, (LUTFunc)LUT8u_64f, 0 }; } void cv::LUT( InputArray _src, InputArray _lut, OutputArray _dst, int interpolation ) { Mat src = _src.getMat(), lut = _lut.getMat(); CV_Assert( interpolation == 0 ); int cn = src.channels(); int lutcn = lut.channels(); CV_Assert( (lutcn == cn || lutcn == 1) && lut.total() == 256 && lut.isContinuous() && (src.depth() == CV_8U || src.depth() == CV_8S) ); _dst.create( src.dims, src.size, CV_MAKETYPE(lut.depth(), cn)); Mat dst = _dst.getMat(); LUTFunc func = lutTab[lut.depth()]; CV_Assert( func != 0 ); const Mat* arrays[] = {&src, &dst, 0}; uchar* ptrs[2]; NAryMatIterator it(arrays, ptrs); int len = (int)it.size; for( size_t i = 0; i < it.nplanes; i++, ++it ) func(ptrs[0], lut.data, ptrs[1], len, cn, lutcn); } void cv::normalize( InputArray _src, OutputArray _dst, double a, double b, int norm_type, int rtype, InputArray _mask ) { Mat src = _src.getMat(), mask = _mask.getMat(); double scale = 1, shift = 0; if( norm_type == CV_MINMAX ) { double smin = 0, smax = 0; double dmin = MIN( a, b ), dmax = MAX( a, b ); minMaxLoc( _src, &smin, &smax, 0, 0, mask ); scale = (dmax - dmin)*(smax - smin > DBL_EPSILON ? 1./(smax - smin) : 0); shift = dmin - smin*scale; } else if( norm_type == CV_L2 || norm_type == CV_L1 || norm_type == CV_C ) { scale = norm( src, norm_type, mask ); scale = scale > DBL_EPSILON ? a/scale : 0.; shift = 0; } else CV_Error( CV_StsBadArg, "Unknown/unsupported norm type" ); if( rtype < 0 ) rtype = _dst.fixedType() ? _dst.depth() : src.depth(); _dst.create(src.dims, src.size, CV_MAKETYPE(rtype, src.channels())); Mat dst = _dst.getMat(); if( !mask.data ) src.convertTo( dst, rtype, scale, shift ); else { Mat temp; src.convertTo( temp, rtype, scale, shift ); temp.copyTo( dst, mask ); } } CV_IMPL void cvSplit( const void* srcarr, void* dstarr0, void* dstarr1, void* dstarr2, void* dstarr3 ) { void* dptrs[] = { dstarr0, dstarr1, dstarr2, dstarr3 }; cv::Mat src = cv::cvarrToMat(srcarr); int i, j, nz = 0; for( i = 0; i < 4; i++ ) nz += dptrs[i] != 0; CV_Assert( nz > 0 ); cv::vector dvec(nz); cv::vector pairs(nz*2); for( i = j = 0; i < 4; i++ ) { if( dptrs[i] != 0 ) { dvec[j] = cv::cvarrToMat(dptrs[i]); CV_Assert( dvec[j].size() == src.size() ); CV_Assert( dvec[j].depth() == src.depth() ); CV_Assert( dvec[j].channels() == 1 ); CV_Assert( i < src.channels() ); pairs[j*2] = i; pairs[j*2+1] = j; j++; } } if( nz == src.channels() ) cv::split( src, dvec ); else { cv::mixChannels( &src, 1, &dvec[0], nz, &pairs[0], nz ); } } CV_IMPL void cvMerge( const void* srcarr0, const void* srcarr1, const void* srcarr2, const void* srcarr3, void* dstarr ) { const void* sptrs[] = { srcarr0, srcarr1, srcarr2, srcarr3 }; cv::Mat dst = cv::cvarrToMat(dstarr); int i, j, nz = 0; for( i = 0; i < 4; i++ ) nz += sptrs[i] != 0; CV_Assert( nz > 0 ); cv::vector svec(nz); cv::vector pairs(nz*2); for( i = j = 0; i < 4; i++ ) { if( sptrs[i] != 0 ) { svec[j] = cv::cvarrToMat(sptrs[i]); CV_Assert( svec[j].size == dst.size && svec[j].depth() == dst.depth() && svec[j].channels() == 1 && i < dst.channels() ); pairs[j*2] = j; pairs[j*2+1] = i; j++; } } if( nz == dst.channels() ) cv::merge( svec, dst ); else { cv::mixChannels( &svec[0], nz, &dst, 1, &pairs[0], nz ); } } CV_IMPL void cvMixChannels( const CvArr** src, int src_count, CvArr** dst, int dst_count, const int* from_to, int pair_count ) { cv::AutoBuffer buf(src_count + dst_count); int i; for( i = 0; i < src_count; i++ ) buf[i] = cv::cvarrToMat(src[i]); for( i = 0; i < dst_count; i++ ) buf[i+src_count] = cv::cvarrToMat(dst[i]); cv::mixChannels(&buf[0], src_count, &buf[src_count], dst_count, from_to, pair_count); } CV_IMPL void cvConvertScaleAbs( const void* srcarr, void* dstarr, double scale, double shift ) { cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr); CV_Assert( src.size == dst.size && dst.type() == CV_8UC(src.channels())); cv::convertScaleAbs( src, dst, scale, shift ); } CV_IMPL void cvConvertScale( const void* srcarr, void* dstarr, double scale, double shift ) { cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr); CV_Assert( src.size == dst.size && src.channels() == dst.channels() ); src.convertTo(dst, dst.type(), scale, shift); } CV_IMPL void cvLUT( const void* srcarr, void* dstarr, const void* lutarr ) { cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), lut = cv::cvarrToMat(lutarr); CV_Assert( dst.size() == src.size() && dst.type() == CV_MAKETYPE(lut.depth(), src.channels()) ); cv::LUT( src, lut, dst ); } CV_IMPL void cvNormalize( const CvArr* srcarr, CvArr* dstarr, double a, double b, int norm_type, const CvArr* maskarr ) { cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), mask; if( maskarr ) mask = cv::cvarrToMat(maskarr); CV_Assert( dst.size() == src.size() && src.channels() == dst.channels() ); cv::normalize( src, dst, a, b, norm_type, dst.type(), mask ); } /* End of file. */