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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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/* ////////////////////////////////////////////////////////////////////
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//
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// Mat basic operations: Copy, Set
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//
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// */
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#include "precomp.hpp"
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namespace cv
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{
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template<typename T> static void
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copyMask_(const uchar* _src, size_t sstep, const uchar* mask, size_t mstep, uchar* _dst, size_t dstep, Size size)
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{
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for( ; size.height--; mask += mstep, _src += sstep, _dst += dstep )
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{
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const T* src = (const T*)_src;
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T* dst = (T*)_dst;
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int x = 0;
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#if CV_ENABLE_UNROLLED
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for( ; x <= size.width - 4; x += 4 )
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{
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if( mask[x] )
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dst[x] = src[x];
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if( mask[x+1] )
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dst[x+1] = src[x+1];
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if( mask[x+2] )
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dst[x+2] = src[x+2];
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if( mask[x+3] )
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dst[x+3] = src[x+3];
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}
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#endif
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for( ; x < size.width; x++ )
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if( mask[x] )
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dst[x] = src[x];
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}
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}
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static void
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copyMaskGeneric(const uchar* _src, size_t sstep, const uchar* mask, size_t mstep, uchar* _dst, size_t dstep, Size size, void* _esz)
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{
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size_t k, esz = *(size_t*)_esz;
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for( ; size.height--; mask += mstep, _src += sstep, _dst += dstep )
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{
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const uchar* src = _src;
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uchar* dst = _dst;
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int x = 0;
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for( ; x < size.width; x++, src += esz, dst += esz )
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{
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if( !mask[x] )
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continue;
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for( k = 0; k < esz; k++ )
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dst[k] = src[k];
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}
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}
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}
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#define DEF_COPY_MASK(suffix, type) \
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static void copyMask##suffix(const uchar* src, size_t sstep, const uchar* mask, size_t mstep, \
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uchar* dst, size_t dstep, Size size, void*) \
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{ \
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copyMask_<type>(src, sstep, mask, mstep, dst, dstep, size); \
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}
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DEF_COPY_MASK(8u, uchar);
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DEF_COPY_MASK(16u, ushort);
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DEF_COPY_MASK(8uC3, Vec3b);
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DEF_COPY_MASK(32s, int);
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DEF_COPY_MASK(16uC3, Vec3s);
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DEF_COPY_MASK(32sC2, Vec2i);
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DEF_COPY_MASK(32sC3, Vec3i);
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DEF_COPY_MASK(32sC4, Vec4i);
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DEF_COPY_MASK(32sC6, Vec6i);
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DEF_COPY_MASK(32sC8, Vec8i);
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BinaryFunc copyMaskTab[] =
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{
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0,
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copyMask8u,
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copyMask16u,
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copyMask8uC3,
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copyMask32s,
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0,
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copyMask16uC3,
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0,
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copyMask32sC2,
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0, 0, 0,
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copyMask32sC3,
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0, 0, 0,
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copyMask32sC4,
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0, 0, 0, 0, 0, 0, 0,
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copyMask32sC6,
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0, 0, 0, 0, 0, 0, 0,
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copyMask32sC8
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};
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BinaryFunc getCopyMaskFunc(size_t esz)
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{
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return esz <= 32 && copyMaskTab[esz] ? copyMaskTab[esz] : copyMaskGeneric;
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}
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/* dst = src */
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void Mat::copyTo( OutputArray _dst ) const
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{
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int dtype = _dst.type();
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if( _dst.fixedType() && dtype != type() )
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{
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convertTo( _dst, dtype );
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return;
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}
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if( empty() )
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{
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_dst.release();
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return;
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}
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if( dims <= 2 )
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{
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_dst.create( rows, cols, type() );
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Mat dst = _dst.getMat();
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if( data == dst.data )
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return;
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if( rows > 0 && cols > 0 )
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{
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const uchar* sptr = data;
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uchar* dptr = dst.data;
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// to handle the copying 1xn matrix => nx1 std vector.
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Size sz = size() == dst.size() ?
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getContinuousSize(*this, dst) :
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getContinuousSize(*this);
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size_t len = sz.width*elemSize();
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for( ; sz.height--; sptr += step, dptr += dst.step )
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memcpy( dptr, sptr, len );
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}
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return;
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}
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_dst.create( dims, size, type() );
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Mat dst = _dst.getMat();
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if( data == dst.data )
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return;
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if( total() != 0 )
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{
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const Mat* arrays[] = { this, &dst };
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uchar* ptrs[2];
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NAryMatIterator it(arrays, ptrs, 2);
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size_t sz = it.size*elemSize();
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for( size_t i = 0; i < it.nplanes; i++, ++it )
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memcpy(ptrs[1], ptrs[0], sz);
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}
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}
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void Mat::copyTo( OutputArray _dst, InputArray _mask ) const
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{
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Mat mask = _mask.getMat();
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if( !mask.data )
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{
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copyTo(_dst);
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return;
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}
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int cn = channels(), mcn = mask.channels();
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CV_Assert( mask.depth() == CV_8U && (mcn == 1 || mcn == cn) );
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bool colorMask = mcn > 1;
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size_t esz = colorMask ? elemSize1() : elemSize();
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BinaryFunc copymask = getCopyMaskFunc(esz);
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uchar* data0 = _dst.getMat().data;
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_dst.create( dims, size, type() );
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Mat dst = _dst.getMat();
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if( dst.data != data0 ) // do not leave dst uninitialized
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dst = Scalar(0);
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if( dims <= 2 )
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{
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Size sz = getContinuousSize(*this, dst, mask, mcn);
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copymask(data, step, mask.data, mask.step, dst.data, dst.step, sz, &esz);
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return;
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}
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const Mat* arrays[] = { this, &dst, &mask, 0 };
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uchar* ptrs[3];
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NAryMatIterator it(arrays, ptrs);
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Size sz((int)(it.size*mcn), 1);
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for( size_t i = 0; i < it.nplanes; i++, ++it )
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copymask(ptrs[0], 0, ptrs[2], 0, ptrs[1], 0, sz, &esz);
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}
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Mat& Mat::operator = (const Scalar& s)
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{
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const Mat* arrays[] = { this };
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uchar* dptr;
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NAryMatIterator it(arrays, &dptr, 1);
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size_t elsize = it.size*elemSize();
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if( s[0] == 0 && s[1] == 0 && s[2] == 0 && s[3] == 0 )
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{
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for( size_t i = 0; i < it.nplanes; i++, ++it )
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memset( dptr, 0, elsize );
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}
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else
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{
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if( it.nplanes > 0 )
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{
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double scalar[12];
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scalarToRawData(s, scalar, type(), 12);
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size_t blockSize = 12*elemSize1();
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for( size_t j = 0; j < elsize; j += blockSize )
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{
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size_t sz = MIN(blockSize, elsize - j);
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memcpy( dptr + j, scalar, sz );
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}
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}
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for( size_t i = 1; i < it.nplanes; i++ )
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{
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++it;
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memcpy( dptr, data, elsize );
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}
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}
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return *this;
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}
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Mat& Mat::setTo(InputArray _value, InputArray _mask)
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{
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if( !data )
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return *this;
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Mat value = _value.getMat(), mask = _mask.getMat();
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CV_Assert( checkScalar(value, type(), _value.kind(), _InputArray::MAT ));
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CV_Assert( mask.empty() || mask.type() == CV_8U );
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size_t esz = elemSize();
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BinaryFunc copymask = getCopyMaskFunc(esz);
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const Mat* arrays[] = { this, !mask.empty() ? &mask : 0, 0 };
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uchar* ptrs[2]={0,0};
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NAryMatIterator it(arrays, ptrs);
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int totalsz = (int)it.size, blockSize0 = std::min(totalsz, (int)((BLOCK_SIZE + esz-1)/esz));
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AutoBuffer<uchar> _scbuf(blockSize0*esz + 32);
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uchar* scbuf = alignPtr((uchar*)_scbuf, (int)sizeof(double));
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convertAndUnrollScalar( value, type(), scbuf, blockSize0 );
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for( size_t i = 0; i < it.nplanes; i++, ++it )
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{
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for( int j = 0; j < totalsz; j += blockSize0 )
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{
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Size sz(std::min(blockSize0, totalsz - j), 1);
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size_t blockSize = sz.width*esz;
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if( ptrs[1] )
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{
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copymask(scbuf, 0, ptrs[1], 0, ptrs[0], 0, sz, &esz);
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ptrs[1] += sz.width;
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}
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else
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memcpy(ptrs[0], scbuf, blockSize);
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ptrs[0] += blockSize;
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}
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}
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return *this;
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}
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static void
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flipHoriz( const uchar* src, size_t sstep, uchar* dst, size_t dstep, Size size, size_t esz )
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|
{
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|
int i, j, limit = (int)(((size.width + 1)/2)*esz);
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AutoBuffer<int> _tab(size.width*esz);
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int* tab = _tab;
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for( i = 0; i < size.width; i++ )
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for( size_t k = 0; k < esz; k++ )
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tab[i*esz + k] = (int)((size.width - i - 1)*esz + k);
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|
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for( ; size.height--; src += sstep, dst += dstep )
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|
{
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|
for( i = 0; i < limit; i++ )
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|
{
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|
j = tab[i];
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|
uchar t0 = src[i], t1 = src[j];
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|
dst[i] = t1; dst[j] = t0;
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|
}
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|
}
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|
}
|
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|
|
|
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|
|
static void
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|
|
flipVert( const uchar* src0, size_t sstep, uchar* dst0, size_t dstep, Size size, size_t esz )
|
|
|
|
{
|
|
|
|
const uchar* src1 = src0 + (size.height - 1)*sstep;
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|
|
uchar* dst1 = dst0 + (size.height - 1)*dstep;
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|
|
size.width *= (int)esz;
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|
|
|
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|
for( int y = 0; y < (size.height + 1)/2; y++, src0 += sstep, src1 -= sstep,
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|
|
dst0 += dstep, dst1 -= dstep )
|
|
|
|
{
|
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|
|
int i = 0;
|
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|
|
if( ((size_t)src0|(size_t)dst0|(size_t)src1|(size_t)dst1) % sizeof(int) == 0 )
|
|
|
|
{
|
|
|
|
for( ; i <= size.width - 16; i += 16 )
|
|
|
|
{
|
|
|
|
int t0 = ((int*)(src0 + i))[0];
|
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|
|
int t1 = ((int*)(src1 + i))[0];
|
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|
|
|
|
|
|
((int*)(dst0 + i))[0] = t1;
|
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|
|
((int*)(dst1 + i))[0] = t0;
|
|
|
|
|
|
|
|
t0 = ((int*)(src0 + i))[1];
|
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|
|
t1 = ((int*)(src1 + i))[1];
|
|
|
|
|
|
|
|
((int*)(dst0 + i))[1] = t1;
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|
|
((int*)(dst1 + i))[1] = t0;
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|
|
|
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|
|
t0 = ((int*)(src0 + i))[2];
|
|
|
|
t1 = ((int*)(src1 + i))[2];
|
|
|
|
|
|
|
|
((int*)(dst0 + i))[2] = t1;
|
|
|
|
((int*)(dst1 + i))[2] = t0;
|
|
|
|
|
|
|
|
t0 = ((int*)(src0 + i))[3];
|
|
|
|
t1 = ((int*)(src1 + i))[3];
|
|
|
|
|
|
|
|
((int*)(dst0 + i))[3] = t1;
|
|
|
|
((int*)(dst1 + i))[3] = t0;
|
|
|
|
}
|
|
|
|
|
|
|
|
for( ; i <= size.width - 4; i += 4 )
|
|
|
|
{
|
|
|
|
int t0 = ((int*)(src0 + i))[0];
|
|
|
|
int t1 = ((int*)(src1 + i))[0];
|
|
|
|
|
|
|
|
((int*)(dst0 + i))[0] = t1;
|
|
|
|
((int*)(dst1 + i))[0] = t0;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
for( ; i < size.width; i++ )
|
|
|
|
{
|
|
|
|
uchar t0 = src0[i];
|
|
|
|
uchar t1 = src1[i];
|
|
|
|
|
|
|
|
dst0[i] = t1;
|
|
|
|
dst1[i] = t0;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void flip( InputArray _src, OutputArray _dst, int flip_mode )
|
|
|
|
{
|
|
|
|
Mat src = _src.getMat();
|
|
|
|
|
|
|
|
CV_Assert( src.dims <= 2 );
|
|
|
|
_dst.create( src.size(), src.type() );
|
|
|
|
Mat dst = _dst.getMat();
|
|
|
|
size_t esz = src.elemSize();
|
|
|
|
|
|
|
|
if( flip_mode <= 0 )
|
|
|
|
flipVert( src.data, src.step, dst.data, dst.step, src.size(), esz );
|
|
|
|
else
|
|
|
|
flipHoriz( src.data, src.step, dst.data, dst.step, src.size(), esz );
|
|
|
|
|
|
|
|
if( flip_mode < 0 )
|
|
|
|
flipHoriz( dst.data, dst.step, dst.data, dst.step, dst.size(), esz );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void repeat(InputArray _src, int ny, int nx, OutputArray _dst)
|
|
|
|
{
|
|
|
|
Mat src = _src.getMat();
|
|
|
|
CV_Assert( src.dims <= 2 );
|
|
|
|
|
|
|
|
_dst.create(src.rows*ny, src.cols*nx, src.type());
|
|
|
|
Mat dst = _dst.getMat();
|
|
|
|
Size ssize = src.size(), dsize = dst.size();
|
|
|
|
int esz = (int)src.elemSize();
|
|
|
|
int x, y;
|
|
|
|
ssize.width *= esz; dsize.width *= esz;
|
|
|
|
|
|
|
|
for( y = 0; y < ssize.height; y++ )
|
|
|
|
{
|
|
|
|
for( x = 0; x < dsize.width; x += ssize.width )
|
|
|
|
memcpy( dst.data + y*dst.step + x, src.data + y*src.step, ssize.width );
|
|
|
|
}
|
|
|
|
|
|
|
|
for( ; y < dsize.height; y++ )
|
|
|
|
memcpy( dst.data + y*dst.step, dst.data + (y - ssize.height)*dst.step, dsize.width );
|
|
|
|
}
|
|
|
|
|
|
|
|
Mat repeat(const Mat& src, int ny, int nx)
|
|
|
|
{
|
|
|
|
if( nx == 1 && ny == 1 )
|
|
|
|
return src;
|
|
|
|
Mat dst;
|
|
|
|
repeat(src, ny, nx, dst);
|
|
|
|
return dst;
|
|
|
|
}
|
|
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
/* dst = src */
|
|
|
|
CV_IMPL void
|
|
|
|
cvCopy( const void* srcarr, void* dstarr, const void* maskarr )
|
|
|
|
{
|
|
|
|
if( CV_IS_SPARSE_MAT(srcarr) && CV_IS_SPARSE_MAT(dstarr))
|
|
|
|
{
|
|
|
|
CV_Assert( maskarr == 0 );
|
|
|
|
CvSparseMat* src1 = (CvSparseMat*)srcarr;
|
|
|
|
CvSparseMat* dst1 = (CvSparseMat*)dstarr;
|
|
|
|
CvSparseMatIterator iterator;
|
|
|
|
CvSparseNode* node;
|
|
|
|
|
|
|
|
dst1->dims = src1->dims;
|
|
|
|
memcpy( dst1->size, src1->size, src1->dims*sizeof(src1->size[0]));
|
|
|
|
dst1->valoffset = src1->valoffset;
|
|
|
|
dst1->idxoffset = src1->idxoffset;
|
|
|
|
cvClearSet( dst1->heap );
|
|
|
|
|
|
|
|
if( src1->heap->active_count >= dst1->hashsize*CV_SPARSE_HASH_RATIO )
|
|
|
|
{
|
|
|
|
cvFree( &dst1->hashtable );
|
|
|
|
dst1->hashsize = src1->hashsize;
|
|
|
|
dst1->hashtable =
|
|
|
|
(void**)cvAlloc( dst1->hashsize*sizeof(dst1->hashtable[0]));
|
|
|
|
}
|
|
|
|
|
|
|
|
memset( dst1->hashtable, 0, dst1->hashsize*sizeof(dst1->hashtable[0]));
|
|
|
|
|
|
|
|
for( node = cvInitSparseMatIterator( src1, &iterator );
|
|
|
|
node != 0; node = cvGetNextSparseNode( &iterator ))
|
|
|
|
{
|
|
|
|
CvSparseNode* node_copy = (CvSparseNode*)cvSetNew( dst1->heap );
|
|
|
|
int tabidx = node->hashval & (dst1->hashsize - 1);
|
|
|
|
memcpy( node_copy, node, dst1->heap->elem_size );
|
|
|
|
node_copy->next = (CvSparseNode*)dst1->hashtable[tabidx];
|
|
|
|
dst1->hashtable[tabidx] = node_copy;
|
|
|
|
}
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
cv::Mat src = cv::cvarrToMat(srcarr, false, true, 1), dst = cv::cvarrToMat(dstarr, false, true, 1);
|
|
|
|
CV_Assert( src.depth() == dst.depth() && src.size == dst.size );
|
|
|
|
|
|
|
|
int coi1 = 0, coi2 = 0;
|
|
|
|
if( CV_IS_IMAGE(srcarr) )
|
|
|
|
coi1 = cvGetImageCOI((const IplImage*)srcarr);
|
|
|
|
if( CV_IS_IMAGE(dstarr) )
|
|
|
|
coi2 = cvGetImageCOI((const IplImage*)dstarr);
|
|
|
|
|
|
|
|
if( coi1 || coi2 )
|
|
|
|
{
|
|
|
|
CV_Assert( (coi1 != 0 || src.channels() == 1) &&
|
|
|
|
(coi2 != 0 || dst.channels() == 1) );
|
|
|
|
|
|
|
|
int pair[] = { std::max(coi1-1, 0), std::max(coi2-1, 0) };
|
|
|
|
cv::mixChannels( &src, 1, &dst, 1, pair, 1 );
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
else
|
|
|
|
CV_Assert( src.channels() == dst.channels() );
|
|
|
|
|
|
|
|
if( !maskarr )
|
|
|
|
src.copyTo(dst);
|
|
|
|
else
|
|
|
|
src.copyTo(dst, cv::cvarrToMat(maskarr));
|
|
|
|
}
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvSet( void* arr, CvScalar value, const void* maskarr )
|
|
|
|
{
|
|
|
|
cv::Mat m = cv::cvarrToMat(arr);
|
|
|
|
if( !maskarr )
|
|
|
|
m = value;
|
|
|
|
else
|
|
|
|
m.setTo(cv::Scalar(value), cv::cvarrToMat(maskarr));
|
|
|
|
}
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvSetZero( CvArr* arr )
|
|
|
|
{
|
|
|
|
if( CV_IS_SPARSE_MAT(arr) )
|
|
|
|
{
|
|
|
|
CvSparseMat* mat1 = (CvSparseMat*)arr;
|
|
|
|
cvClearSet( mat1->heap );
|
|
|
|
if( mat1->hashtable )
|
|
|
|
memset( mat1->hashtable, 0, mat1->hashsize*sizeof(mat1->hashtable[0]));
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
cv::Mat m = cv::cvarrToMat(arr);
|
|
|
|
m = cv::Scalar(0);
|
|
|
|
}
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvFlip( const CvArr* srcarr, CvArr* dstarr, int flip_mode )
|
|
|
|
{
|
|
|
|
cv::Mat src = cv::cvarrToMat(srcarr);
|
|
|
|
cv::Mat dst;
|
|
|
|
|
|
|
|
if (!dstarr)
|
|
|
|
dst = src;
|
|
|
|
else
|
|
|
|
dst = cv::cvarrToMat(dstarr);
|
|
|
|
|
|
|
|
CV_Assert( src.type() == dst.type() && src.size() == dst.size() );
|
|
|
|
cv::flip( src, dst, flip_mode );
|
|
|
|
}
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvRepeat( const CvArr* srcarr, CvArr* dstarr )
|
|
|
|
{
|
|
|
|
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
|
|
|
|
CV_Assert( src.type() == dst.type() &&
|
|
|
|
dst.rows % src.rows == 0 && dst.cols % src.cols == 0 );
|
|
|
|
cv::repeat(src, dst.rows/src.rows, dst.cols/src.cols, dst);
|
|
|
|
}
|
|
|
|
|
|
|
|
/* End of file. */
|