arithm.cpp 120.2 KB
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/*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.
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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.
//
// 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*/

/* ////////////////////////////////////////////////////////////////////
//
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//  Arithmetic and logical operations: +, -, *, /, &, |, ^, ~, abs ...
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//
// */

#include "precomp.hpp"
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#include "opencl_kernels.hpp"
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namespace cv
{

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#if ARITHM_USE_IPP
struct IPPArithmInitializer
{
    IPPArithmInitializer(void)
    {
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        ippStaticInit();
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    }
};
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IPPArithmInitializer ippArithmInitializer;
#endif
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struct NOP {};
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#if CV_SSE2

#define FUNCTOR_TEMPLATE(name)          \
    template<typename T> struct name {}

FUNCTOR_TEMPLATE(VLoadStore128);
FUNCTOR_TEMPLATE(VLoadStore64);
FUNCTOR_TEMPLATE(VLoadStore128Aligned);

#endif

template<typename T, class Op, class VOp>
void vBinOp(const T* src1, size_t step1, const T* src2, size_t step2, T* dst, size_t step, Size sz)
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{
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#if CV_SSE2
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    VOp vop;
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#endif
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    Op op;
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    for( ; sz.height--; src1 += step1/sizeof(src1[0]),
                        src2 += step2/sizeof(src2[0]),
                        dst += step/sizeof(dst[0]) )
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    {
        int x = 0;
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#if CV_SSE2
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        if( USE_SSE2 )
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        {
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            for( ; x <= sz.width - 32/(int)sizeof(T); x += 32/sizeof(T) )
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            {
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                typename VLoadStore128<T>::reg_type r0 = VLoadStore128<T>::load(src1 + x               );
                typename VLoadStore128<T>::reg_type r1 = VLoadStore128<T>::load(src1 + x + 16/sizeof(T));
                r0 = vop(r0, VLoadStore128<T>::load(src2 + x               ));
                r1 = vop(r1, VLoadStore128<T>::load(src2 + x + 16/sizeof(T)));
                VLoadStore128<T>::store(dst + x               , r0);
                VLoadStore128<T>::store(dst + x + 16/sizeof(T), r1);
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            }
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        }
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#endif
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#if CV_SSE2
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        if( USE_SSE2 )
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        {
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            for( ; x <= sz.width - 8/(int)sizeof(T); x += 8/sizeof(T) )
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            {
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                typename VLoadStore64<T>::reg_type r = VLoadStore64<T>::load(src1 + x);
                r = vop(r, VLoadStore64<T>::load(src2 + x));
                VLoadStore64<T>::store(dst + x, r);
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            }
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        }
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#endif
#if CV_ENABLE_UNROLLED
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        for( ; x <= sz.width - 4; x += 4 )
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        {
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            T v0 = op(src1[x], src2[x]);
            T v1 = op(src1[x+1], src2[x+1]);
            dst[x] = v0; dst[x+1] = v1;
            v0 = op(src1[x+2], src2[x+2]);
            v1 = op(src1[x+3], src2[x+3]);
            dst[x+2] = v0; dst[x+3] = v1;
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        }
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#endif
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        for( ; x < sz.width; x++ )
            dst[x] = op(src1[x], src2[x]);
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    }
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}
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template<typename T, class Op, class Op32>
void vBinOp32(const T* src1, size_t step1, const T* src2, size_t step2,
              T* dst, size_t step, Size sz)
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{
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#if CV_SSE2
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    Op32 op32;
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#endif
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    Op op;
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    for( ; sz.height--; src1 += step1/sizeof(src1[0]),
        src2 += step2/sizeof(src2[0]),
        dst += step/sizeof(dst[0]) )
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    {
        int x = 0;
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#if CV_SSE2
        if( USE_SSE2 )
        {
            if( (((size_t)src1|(size_t)src2|(size_t)dst)&15) == 0 )
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            {
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                for( ; x <= sz.width - 8; x += 8 )
                {
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                    typename VLoadStore128Aligned<T>::reg_type r0 = VLoadStore128Aligned<T>::load(src1 + x    );
                    typename VLoadStore128Aligned<T>::reg_type r1 = VLoadStore128Aligned<T>::load(src1 + x + 4);
                    r0 = op32(r0, VLoadStore128Aligned<T>::load(src2 + x    ));
                    r1 = op32(r1, VLoadStore128Aligned<T>::load(src2 + x + 4));
                    VLoadStore128Aligned<T>::store(dst + x    , r0);
                    VLoadStore128Aligned<T>::store(dst + x + 4, r1);
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                }
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            }
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        }
#endif
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#if CV_SSE2
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        if( USE_SSE2 )
        {
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            for( ; x <= sz.width - 8; x += 8 )
            {
                typename VLoadStore128<T>::reg_type r0 = VLoadStore128<T>::load(src1 + x    );
                typename VLoadStore128<T>::reg_type r1 = VLoadStore128<T>::load(src1 + x + 4);
                r0 = op32(r0, VLoadStore128<T>::load(src2 + x    ));
                r1 = op32(r1, VLoadStore128<T>::load(src2 + x + 4));
                VLoadStore128<T>::store(dst + x    , r0);
                VLoadStore128<T>::store(dst + x + 4, r1);
            }
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        }
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#endif
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#if CV_ENABLE_UNROLLED
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        for( ; x <= sz.width - 4; x += 4 )
        {
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            T v0 = op(src1[x], src2[x]);
            T v1 = op(src1[x+1], src2[x+1]);
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            dst[x] = v0; dst[x+1] = v1;
            v0 = op(src1[x+2], src2[x+2]);
            v1 = op(src1[x+3], src2[x+3]);
            dst[x+2] = v0; dst[x+3] = v1;
        }
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#endif
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        for( ; x < sz.width; x++ )
            dst[x] = op(src1[x], src2[x]);
    }
}

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template<typename T, class Op, class Op64>
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void vBinOp64(const T* src1, size_t step1, const T* src2, size_t step2,
               T* dst, size_t step, Size sz)
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{
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#if CV_SSE2
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    Op64 op64;
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#endif
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    Op op;
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    for( ; sz.height--; src1 += step1/sizeof(src1[0]),
        src2 += step2/sizeof(src2[0]),
        dst += step/sizeof(dst[0]) )
    {
        int x = 0;
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#if CV_SSE2
        if( USE_SSE2 )
        {
            if( (((size_t)src1|(size_t)src2|(size_t)dst)&15) == 0 )
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            {
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                for( ; x <= sz.width - 4; x += 4 )
                {
                    typename VLoadStore128Aligned<T>::reg_type r0 = VLoadStore128Aligned<T>::load(src1 + x    );
                    typename VLoadStore128Aligned<T>::reg_type r1 = VLoadStore128Aligned<T>::load(src1 + x + 2);
                    r0 = op64(r0, VLoadStore128Aligned<T>::load(src2 + x    ));
                    r1 = op64(r1, VLoadStore128Aligned<T>::load(src2 + x + 2));
                    VLoadStore128Aligned<T>::store(dst + x    , r0);
                    VLoadStore128Aligned<T>::store(dst + x + 2, r1);
                }
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            }
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        }
#endif

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        for( ; x <= sz.width - 4; x += 4 )
        {
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            T v0 = op(src1[x], src2[x]);
            T v1 = op(src1[x+1], src2[x+1]);
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            dst[x] = v0; dst[x+1] = v1;
            v0 = op(src1[x+2], src2[x+2]);
            v1 = op(src1[x+3], src2[x+3]);
            dst[x+2] = v0; dst[x+3] = v1;
        }
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        for( ; x < sz.width; x++ )
            dst[x] = op(src1[x], src2[x]);
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    }
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}
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#if CV_SSE2
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#define FUNCTOR_LOADSTORE_CAST(name, template_arg, register_type, load_body, store_body)\
    template <>                                                                                  \
    struct name<template_arg>{                                                                   \
        typedef register_type reg_type;                                                          \
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        static reg_type load(const template_arg * p) { return load_body ((const reg_type *)p); } \
        static void store(template_arg * p, reg_type v) { store_body ((reg_type *)p, v); }       \
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    }
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#define FUNCTOR_LOADSTORE(name, template_arg, register_type, load_body, store_body)\
    template <>                                                                \
    struct name<template_arg>{                                                 \
        typedef register_type reg_type;                                        \
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        static reg_type load(const template_arg * p) { return load_body (p); } \
        static void store(template_arg * p, reg_type v) { store_body (p, v); } \
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    }

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#define FUNCTOR_CLOSURE_2arg(name, template_arg, body)\
    template<>                                                                 \
    struct name<template_arg>                                                  \
    {                                                                          \
        VLoadStore128<template_arg>::reg_type operator()(                      \
                        const VLoadStore128<template_arg>::reg_type & a,       \
                        const VLoadStore128<template_arg>::reg_type & b) const \
        {                                                                      \
            body;                                                              \
        }                                                                      \
    }
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#define FUNCTOR_CLOSURE_1arg(name, template_arg, body)\
    template<>                                                                 \
    struct name<template_arg>                                                  \
    {                                                                          \
        VLoadStore128<template_arg>::reg_type operator()(                      \
                        const VLoadStore128<template_arg>::reg_type & a,       \
                        const VLoadStore128<template_arg>::reg_type &  ) const \
        {                                                                      \
            body;                                                              \
        }                                                                      \
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    }
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FUNCTOR_LOADSTORE_CAST(VLoadStore128,  uchar, __m128i, _mm_loadu_si128, _mm_storeu_si128);
FUNCTOR_LOADSTORE_CAST(VLoadStore128,  schar, __m128i, _mm_loadu_si128, _mm_storeu_si128);
FUNCTOR_LOADSTORE_CAST(VLoadStore128, ushort, __m128i, _mm_loadu_si128, _mm_storeu_si128);
FUNCTOR_LOADSTORE_CAST(VLoadStore128,  short, __m128i, _mm_loadu_si128, _mm_storeu_si128);
FUNCTOR_LOADSTORE_CAST(VLoadStore128,    int, __m128i, _mm_loadu_si128, _mm_storeu_si128);
FUNCTOR_LOADSTORE(     VLoadStore128,  float, __m128 , _mm_loadu_ps   , _mm_storeu_ps   );
FUNCTOR_LOADSTORE(     VLoadStore128, double, __m128d, _mm_loadu_pd   , _mm_storeu_pd   );

FUNCTOR_LOADSTORE_CAST(VLoadStore64,  uchar, __m128i, _mm_loadl_epi64, _mm_storel_epi64);
FUNCTOR_LOADSTORE_CAST(VLoadStore64,  schar, __m128i, _mm_loadl_epi64, _mm_storel_epi64);
FUNCTOR_LOADSTORE_CAST(VLoadStore64, ushort, __m128i, _mm_loadl_epi64, _mm_storel_epi64);
FUNCTOR_LOADSTORE_CAST(VLoadStore64,  short, __m128i, _mm_loadl_epi64, _mm_storel_epi64);

FUNCTOR_LOADSTORE_CAST(VLoadStore128Aligned,    int, __m128i, _mm_load_si128, _mm_store_si128);
FUNCTOR_LOADSTORE(     VLoadStore128Aligned,  float, __m128 , _mm_load_ps   , _mm_store_ps   );
FUNCTOR_LOADSTORE(     VLoadStore128Aligned, double, __m128d, _mm_load_pd   , _mm_store_pd   );

FUNCTOR_TEMPLATE(VAdd);
FUNCTOR_CLOSURE_2arg(VAdd,  uchar, return _mm_adds_epu8 (a, b));
FUNCTOR_CLOSURE_2arg(VAdd,  schar, return _mm_adds_epi8 (a, b));
FUNCTOR_CLOSURE_2arg(VAdd, ushort, return _mm_adds_epu16(a, b));
FUNCTOR_CLOSURE_2arg(VAdd,  short, return _mm_adds_epi16(a, b));
FUNCTOR_CLOSURE_2arg(VAdd,    int, return _mm_add_epi32 (a, b));
FUNCTOR_CLOSURE_2arg(VAdd,  float, return _mm_add_ps    (a, b));
FUNCTOR_CLOSURE_2arg(VAdd, double, return _mm_add_pd    (a, b));

FUNCTOR_TEMPLATE(VSub);
FUNCTOR_CLOSURE_2arg(VSub,  uchar, return _mm_subs_epu8 (a, b));
FUNCTOR_CLOSURE_2arg(VSub,  schar, return _mm_subs_epi8 (a, b));
FUNCTOR_CLOSURE_2arg(VSub, ushort, return _mm_subs_epu16(a, b));
FUNCTOR_CLOSURE_2arg(VSub,  short, return _mm_subs_epi16(a, b));
FUNCTOR_CLOSURE_2arg(VSub,    int, return _mm_sub_epi32 (a, b));
FUNCTOR_CLOSURE_2arg(VSub,  float, return _mm_sub_ps    (a, b));
FUNCTOR_CLOSURE_2arg(VSub, double, return _mm_sub_pd    (a, b));

FUNCTOR_TEMPLATE(VMin);
FUNCTOR_CLOSURE_2arg(VMin, uchar, return _mm_min_epu8(a, b));
FUNCTOR_CLOSURE_2arg(VMin, schar,
        __m128i m = _mm_cmpgt_epi8(a, b);
        return _mm_xor_si128(a, _mm_and_si128(_mm_xor_si128(a, b), m));
    );
FUNCTOR_CLOSURE_2arg(VMin, ushort, return _mm_subs_epu16(a, _mm_subs_epu16(a, b)));
FUNCTOR_CLOSURE_2arg(VMin,  short, return _mm_min_epi16(a, b));
FUNCTOR_CLOSURE_2arg(VMin,    int,
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        __m128i m = _mm_cmpgt_epi32(a, b);
        return _mm_xor_si128(a, _mm_and_si128(_mm_xor_si128(a, b), m));
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    );
FUNCTOR_CLOSURE_2arg(VMin,  float, return _mm_min_ps(a, b));
FUNCTOR_CLOSURE_2arg(VMin, double, return _mm_min_pd(a, b));

FUNCTOR_TEMPLATE(VMax);
FUNCTOR_CLOSURE_2arg(VMax, uchar, return _mm_max_epu8(a, b));
FUNCTOR_CLOSURE_2arg(VMax, schar,
        __m128i m = _mm_cmpgt_epi8(b, a);
        return _mm_xor_si128(a, _mm_and_si128(_mm_xor_si128(a, b), m));
    );
FUNCTOR_CLOSURE_2arg(VMax, ushort, return _mm_adds_epu16(_mm_subs_epu16(a, b), b));
FUNCTOR_CLOSURE_2arg(VMax,  short, return _mm_max_epi16(a, b));
FUNCTOR_CLOSURE_2arg(VMax,    int,
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        __m128i m = _mm_cmpgt_epi32(b, a);
        return _mm_xor_si128(a, _mm_and_si128(_mm_xor_si128(a, b), m));
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    );
FUNCTOR_CLOSURE_2arg(VMax,  float, return _mm_max_ps(a, b));
FUNCTOR_CLOSURE_2arg(VMax, double, return _mm_max_pd(a, b));


static int CV_DECL_ALIGNED(16) v32f_absmask[] = { 0x7fffffff, 0x7fffffff, 0x7fffffff, 0x7fffffff };
static int CV_DECL_ALIGNED(16) v64f_absmask[] = { 0xffffffff, 0x7fffffff, 0xffffffff, 0x7fffffff };

FUNCTOR_TEMPLATE(VAbsDiff);
FUNCTOR_CLOSURE_2arg(VAbsDiff,  uchar,
        return _mm_add_epi8(_mm_subs_epu8(a, b), _mm_subs_epu8(b, a));
    );
FUNCTOR_CLOSURE_2arg(VAbsDiff,  schar,
        __m128i d = _mm_subs_epi8(a, b);
        __m128i m = _mm_cmpgt_epi8(b, a);
        return _mm_subs_epi8(_mm_xor_si128(d, m), m);
    );
FUNCTOR_CLOSURE_2arg(VAbsDiff, ushort,
        return _mm_add_epi16(_mm_subs_epu16(a, b), _mm_subs_epu16(b, a));
    );
FUNCTOR_CLOSURE_2arg(VAbsDiff,  short,
        __m128i M = _mm_max_epi16(a, b);
        __m128i m = _mm_min_epi16(a, b);
        return _mm_subs_epi16(M, m);
    );
FUNCTOR_CLOSURE_2arg(VAbsDiff,    int,
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        __m128i d = _mm_sub_epi32(a, b);
        __m128i m = _mm_cmpgt_epi32(b, a);
        return _mm_sub_epi32(_mm_xor_si128(d, m), m);
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    );
FUNCTOR_CLOSURE_2arg(VAbsDiff,  float,
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        return _mm_and_ps(_mm_sub_ps(a,b), *(const __m128*)v32f_absmask);
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    );
FUNCTOR_CLOSURE_2arg(VAbsDiff, double,
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        return _mm_and_pd(_mm_sub_pd(a,b), *(const __m128d*)v64f_absmask);
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    );

FUNCTOR_TEMPLATE(VAnd);
FUNCTOR_CLOSURE_2arg(VAnd, uchar, return _mm_and_si128(a, b));
FUNCTOR_TEMPLATE(VOr);
FUNCTOR_CLOSURE_2arg(VOr , uchar, return _mm_or_si128 (a, b));
FUNCTOR_TEMPLATE(VXor);
FUNCTOR_CLOSURE_2arg(VXor, uchar, return _mm_xor_si128(a, b));
FUNCTOR_TEMPLATE(VNot);
FUNCTOR_CLOSURE_1arg(VNot, uchar, return _mm_xor_si128(_mm_set1_epi32(-1), a));
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#endif
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#if CV_SSE2
#define IF_SIMD(op) op
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#else
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#define IF_SIMD(op) NOP
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#endif
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template<> inline uchar OpAdd<uchar>::operator ()(uchar a, uchar b) const
{ return CV_FAST_CAST_8U(a + b); }
template<> inline uchar OpSub<uchar>::operator ()(uchar a, uchar b) const
{ return CV_FAST_CAST_8U(a - b); }
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template<typename T> struct OpAbsDiff
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{
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    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()(T a, T b) const { return (T)std::abs(a - b); }
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};

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template<> inline short OpAbsDiff<short>::operator ()(short a, short b) const
{ return saturate_cast<short>(std::abs(a - b)); }
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template<> inline schar OpAbsDiff<schar>::operator ()(schar a, schar b) const
{ return saturate_cast<schar>(std::abs(a - b)); }
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template<typename T, typename WT=T> struct OpAbsDiffS
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{
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    typedef T type1;
    typedef WT type2;
    typedef T rtype;
    T operator()(T a, WT b) const { return saturate_cast<T>(std::abs(a - b)); }
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};

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template<typename T> struct OpAnd
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{
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    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T b ) const { return a & b; }
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};

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template<typename T> struct OpOr
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{
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    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T b ) const { return a | b; }
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};

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template<typename T> struct OpXor
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{
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    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T b ) const { return a ^ b; }
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};

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template<typename T> struct OpNot
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{
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    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T ) const { return ~a; }
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};
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static inline void fixSteps(Size sz, size_t elemSize, size_t& step1, size_t& step2, size_t& step)
{
    if( sz.height == 1 )
        step1 = step2 = step = sz.width*elemSize;
}
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static void add8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
{
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
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           ippiAdd_8u_C1RSfs(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz, 0),
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           (vBinOp<uchar, OpAdd<uchar>, IF_SIMD(VAdd<uchar>)>(src1, step1, src2, step2, dst, step, sz)));
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}
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static void add8s( const schar* src1, size_t step1,
                   const schar* src2, size_t step2,
                   schar* dst, size_t step, Size sz, void* )
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{
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    vBinOp<schar, OpAdd<schar>, IF_SIMD(VAdd<schar>)>(src1, step1, src2, step2, dst, step, sz);
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}
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static void add16u( const ushort* src1, size_t step1,
                    const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* )
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{
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    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
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           ippiAdd_16u_C1RSfs(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz, 0),
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           (vBinOp<ushort, OpAdd<ushort>, IF_SIMD(VAdd<ushort>)>(src1, step1, src2, step2, dst, step, sz)));
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}
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static void add16s( const short* src1, size_t step1,
                    const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* )
497
{
498
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
499
           ippiAdd_16s_C1RSfs(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz, 0),
500
           (vBinOp<short, OpAdd<short>, IF_SIMD(VAdd<short>)>(src1, step1, src2, step2, dst, step, sz)));
501
}
502

503 504 505
static void add32s( const int* src1, size_t step1,
                    const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* )
506
{
507
    vBinOp32<int, OpAdd<int>, IF_SIMD(VAdd<int>)>(src1, step1, src2, step2, dst, step, sz);
508
}
509

510 511 512
static void add32f( const float* src1, size_t step1,
                    const float* src2, size_t step2,
                    float* dst, size_t step, Size sz, void* )
513
{
514
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
515
           ippiAdd_32f_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz),
516
           (vBinOp32<float, OpAdd<float>, IF_SIMD(VAdd<float>)>(src1, step1, src2, step2, dst, step, sz)));
517
}
518

519 520 521
static void add64f( const double* src1, size_t step1,
                    const double* src2, size_t step2,
                    double* dst, size_t step, Size sz, void* )
522
{
523
    vBinOp64<double, OpAdd<double>, IF_SIMD(VAdd<double>)>(src1, step1, src2, step2, dst, step, sz);
524
}
525

526 527 528
static void sub8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
529
{
530
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
531
           ippiSub_8u_C1RSfs(src2, (int)step2, src1, (int)step1, dst, (int)step, (IppiSize&)sz, 0),
532
           (vBinOp<uchar, OpSub<uchar>, IF_SIMD(VSub<uchar>)>(src1, step1, src2, step2, dst, step, sz)));
533
}
534

535 536 537
static void sub8s( const schar* src1, size_t step1,
                   const schar* src2, size_t step2,
                   schar* dst, size_t step, Size sz, void* )
538
{
539
    vBinOp<schar, OpSub<schar>, IF_SIMD(VSub<schar>)>(src1, step1, src2, step2, dst, step, sz);
540
}
541

542 543 544
static void sub16u( const ushort* src1, size_t step1,
                    const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* )
545
{
546
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
547
           ippiSub_16u_C1RSfs(src2, (int)step2, src1, (int)step1, dst, (int)step, (IppiSize&)sz, 0),
548
           (vBinOp<ushort, OpSub<ushort>, IF_SIMD(VSub<ushort>)>(src1, step1, src2, step2, dst, step, sz)));
549
}
550

551 552 553
static void sub16s( const short* src1, size_t step1,
                    const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* )
554
{
555
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
556
           ippiSub_16s_C1RSfs(src2, (int)step2, src1, (int)step1, dst, (int)step, (IppiSize&)sz, 0),
557
           (vBinOp<short, OpSub<short>, IF_SIMD(VSub<short>)>(src1, step1, src2, step2, dst, step, sz)));
558
}
559

560 561 562
static void sub32s( const int* src1, size_t step1,
                    const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* )
563
{
564
    vBinOp32<int, OpSub<int>, IF_SIMD(VSub<int>)>(src1, step1, src2, step2, dst, step, sz);
565
}
566

567 568 569
static void sub32f( const float* src1, size_t step1,
                   const float* src2, size_t step2,
                   float* dst, size_t step, Size sz, void* )
570
{
571
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
572
           ippiSub_32f_C1R(src2, (int)step2, src1, (int)step1, dst, (int)step, (IppiSize&)sz),
573
           (vBinOp32<float, OpSub<float>, IF_SIMD(VSub<float>)>(src1, step1, src2, step2, dst, step, sz)));
574
}
575

576 577 578
static void sub64f( const double* src1, size_t step1,
                    const double* src2, size_t step2,
                    double* dst, size_t step, Size sz, void* )
579
{
580
    vBinOp64<double, OpSub<double>, IF_SIMD(VSub<double>)>(src1, step1, src2, step2, dst, step, sz);
581
}
582

583 584
template<> inline uchar OpMin<uchar>::operator ()(uchar a, uchar b) const { return CV_MIN_8U(a, b); }
template<> inline uchar OpMax<uchar>::operator ()(uchar a, uchar b) const { return CV_MAX_8U(a, b); }
585

586 587 588
static void max8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
589
{
590 591 592 593 594 595 596 597 598 599 600 601 602 603 604
#if (ARITHM_USE_IPP == 1)
  {
    uchar* s1 = (uchar*)src1;
    uchar* s2 = (uchar*)src2;
    uchar* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    for(int i = 0; i < sz.height; i++)
    {
      ippsMaxEvery_8u(s1, s2, d, sz.width);
      s1 += step1;
      s2 += step2;
      d  += step;
    }
  }
#else
605
  vBinOp<uchar, OpMax<uchar>, IF_SIMD(VMax<uchar>)>(src1, step1, src2, step2, dst, step, sz);
606 607 608 609 610
#endif

//    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
//           ippiMaxEvery_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (IppiSize&)sz),
//           (vBinOp8<uchar, OpMax<uchar>, IF_SIMD(_VMax8u)>(src1, step1, src2, step2, dst, step, sz)));
611
}
612

613 614 615
static void max8s( const schar* src1, size_t step1,
                   const schar* src2, size_t step2,
                   schar* dst, size_t step, Size sz, void* )
616
{
617
    vBinOp<schar, OpMax<schar>, IF_SIMD(VMax<schar>)>(src1, step1, src2, step2, dst, step, sz);
618
}
619

620 621 622
static void max16u( const ushort* src1, size_t step1,
                    const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* )
623
{
624 625 626 627 628 629 630 631 632 633 634 635 636 637 638
#if (ARITHM_USE_IPP == 1)
  {
    ushort* s1 = (ushort*)src1;
    ushort* s2 = (ushort*)src2;
    ushort* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    for(int i = 0; i < sz.height; i++)
    {
      ippsMaxEvery_16u(s1, s2, d, sz.width);
      s1 = (ushort*)((uchar*)s1 + step1);
      s2 = (ushort*)((uchar*)s2 + step2);
      d  = (ushort*)((uchar*)d + step);
    }
  }
#else
639
  vBinOp<ushort, OpMax<ushort>, IF_SIMD(VMax<ushort>)>(src1, step1, src2, step2, dst, step, sz);
640 641 642 643 644
#endif

//    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
//           ippiMaxEvery_16u_C1R(src1, (int)step1, src2, (int)step2, dst, (IppiSize&)sz),
//           (vBinOp16<ushort, OpMax<ushort>, IF_SIMD(_VMax16u)>(src1, step1, src2, step2, dst, step, sz)));
645
}
646

647 648 649
static void max16s( const short* src1, size_t step1,
                    const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* )
650
{
651
    vBinOp<short, OpMax<short>, IF_SIMD(VMax<short>)>(src1, step1, src2, step2, dst, step, sz);
652
}
653

654 655 656
static void max32s( const int* src1, size_t step1,
                    const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* )
657
{
658
    vBinOp32<int, OpMax<int>, IF_SIMD(VMax<int>)>(src1, step1, src2, step2, dst, step, sz);
659
}
660

661 662 663
static void max32f( const float* src1, size_t step1,
                    const float* src2, size_t step2,
                    float* dst, size_t step, Size sz, void* )
664
{
665 666 667 668 669 670 671 672 673 674 675 676 677 678 679
#if (ARITHM_USE_IPP == 1)
  {
    float* s1 = (float*)src1;
    float* s2 = (float*)src2;
    float* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    for(int i = 0; i < sz.height; i++)
    {
      ippsMaxEvery_32f(s1, s2, d, sz.width);
      s1 = (float*)((uchar*)s1 + step1);
      s2 = (float*)((uchar*)s2 + step2);
      d  = (float*)((uchar*)d + step);
    }
  }
#else
680
  vBinOp32<float, OpMax<float>, IF_SIMD(VMax<float>)>(src1, step1, src2, step2, dst, step, sz);
681 682 683 684
#endif
//    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
//           ippiMaxEvery_32f_C1R(src1, (int)step1, src2, (int)step2, dst, (IppiSize&)sz),
//           (vBinOp32f<OpMax<float>, IF_SIMD(_VMax32f)>(src1, step1, src2, step2, dst, step, sz)));
685
}
686

687 688 689
static void max64f( const double* src1, size_t step1,
                    const double* src2, size_t step2,
                    double* dst, size_t step, Size sz, void* )
690
{
691
    vBinOp64<double, OpMax<double>, IF_SIMD(VMax<double>)>(src1, step1, src2, step2, dst, step, sz);
692
}
693

694 695 696
static void min8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
697
{
698 699 700 701 702 703 704 705 706 707 708 709 710 711 712
#if (ARITHM_USE_IPP == 1)
  {
    uchar* s1 = (uchar*)src1;
    uchar* s2 = (uchar*)src2;
    uchar* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    for(int i = 0; i < sz.height; i++)
    {
      ippsMinEvery_8u(s1, s2, d, sz.width);
      s1 += step1;
      s2 += step2;
      d  += step;
    }
  }
#else
713
  vBinOp<uchar, OpMin<uchar>, IF_SIMD(VMin<uchar>)>(src1, step1, src2, step2, dst, step, sz);
714 715 716 717 718
#endif

//    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
//           ippiMinEvery_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (IppiSize&)sz),
//           (vBinOp8<uchar, OpMin<uchar>, IF_SIMD(_VMin8u)>(src1, step1, src2, step2, dst, step, sz)));
719
}
720

721 722 723 724
static void min8s( const schar* src1, size_t step1,
                   const schar* src2, size_t step2,
                   schar* dst, size_t step, Size sz, void* )
{
725
    vBinOp<schar, OpMin<schar>, IF_SIMD(VMin<schar>)>(src1, step1, src2, step2, dst, step, sz);
726
}
727

728 729 730 731
static void min16u( const ushort* src1, size_t step1,
                    const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* )
{
732 733 734 735 736 737 738 739 740 741 742 743 744 745 746
#if (ARITHM_USE_IPP == 1)
  {
    ushort* s1 = (ushort*)src1;
    ushort* s2 = (ushort*)src2;
    ushort* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    for(int i = 0; i < sz.height; i++)
    {
      ippsMinEvery_16u(s1, s2, d, sz.width);
      s1 = (ushort*)((uchar*)s1 + step1);
      s2 = (ushort*)((uchar*)s2 + step2);
      d  = (ushort*)((uchar*)d + step);
    }
  }
#else
747
  vBinOp<ushort, OpMin<ushort>, IF_SIMD(VMin<ushort>)>(src1, step1, src2, step2, dst, step, sz);
748 749 750 751 752
#endif

//    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
//           ippiMinEvery_16u_C1R(src1, (int)step1, src2, (int)step2, dst, (IppiSize&)sz),
//           (vBinOp16<ushort, OpMin<ushort>, IF_SIMD(_VMin16u)>(src1, step1, src2, step2, dst, step, sz)));
753
}
754

755 756 757 758
static void min16s( const short* src1, size_t step1,
                    const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* )
{
759
    vBinOp<short, OpMin<short>, IF_SIMD(VMin<short>)>(src1, step1, src2, step2, dst, step, sz);
760
}
761

762 763 764
static void min32s( const int* src1, size_t step1,
                    const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* )
765
{
766
    vBinOp32<int, OpMin<int>, IF_SIMD(VMin<int>)>(src1, step1, src2, step2, dst, step, sz);
767
}
768

769 770 771
static void min32f( const float* src1, size_t step1,
                    const float* src2, size_t step2,
                    float* dst, size_t step, Size sz, void* )
772
{
773 774 775 776 777 778 779 780 781 782 783 784 785 786 787
#if (ARITHM_USE_IPP == 1)
  {
    float* s1 = (float*)src1;
    float* s2 = (float*)src2;
    float* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    for(int i = 0; i < sz.height; i++)
    {
      ippsMinEvery_32f(s1, s2, d, sz.width);
      s1 = (float*)((uchar*)s1 + step1);
      s2 = (float*)((uchar*)s2 + step2);
      d  = (float*)((uchar*)d + step);
    }
  }
#else
788
  vBinOp32<float, OpMin<float>, IF_SIMD(VMin<float>)>(src1, step1, src2, step2, dst, step, sz);
789 790 791 792
#endif
//    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
//           ippiMinEvery_32f_C1R(src1, (int)step1, src2, (int)step2, dst, (IppiSize&)sz),
//           (vBinOp32f<OpMin<float>, IF_SIMD(_VMin32f)>(src1, step1, src2, step2, dst, step, sz)));
793
}
794

795 796 797
static void min64f( const double* src1, size_t step1,
                    const double* src2, size_t step2,
                    double* dst, size_t step, Size sz, void* )
798
{
799
    vBinOp64<double, OpMin<double>, IF_SIMD(VMin<double>)>(src1, step1, src2, step2, dst, step, sz);
800
}
801

802 803 804
static void absdiff8u( const uchar* src1, size_t step1,
                       const uchar* src2, size_t step2,
                       uchar* dst, size_t step, Size sz, void* )
805
{
806
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
807
           ippiAbsDiff_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz),
808
           (vBinOp<uchar, OpAbsDiff<uchar>, IF_SIMD(VAbsDiff<uchar>)>(src1, step1, src2, step2, dst, step, sz)));
809
}
810

811 812 813 814
static void absdiff8s( const schar* src1, size_t step1,
                       const schar* src2, size_t step2,
                       schar* dst, size_t step, Size sz, void* )
{
815
    vBinOp<schar, OpAbsDiff<schar>, IF_SIMD(VAbsDiff<schar>)>(src1, step1, src2, step2, dst, step, sz);
816
}
817

818 819 820 821 822
static void absdiff16u( const ushort* src1, size_t step1,
                        const ushort* src2, size_t step2,
                        ushort* dst, size_t step, Size sz, void* )
{
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
823
           ippiAbsDiff_16u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz),
824
           (vBinOp<ushort, OpAbsDiff<ushort>, IF_SIMD(VAbsDiff<ushort>)>(src1, step1, src2, step2, dst, step, sz)));
825
}
826

827 828 829 830
static void absdiff16s( const short* src1, size_t step1,
                        const short* src2, size_t step2,
                        short* dst, size_t step, Size sz, void* )
{
831
    vBinOp<short, OpAbsDiff<short>, IF_SIMD(VAbsDiff<short>)>(src1, step1, src2, step2, dst, step, sz);
832
}
833

834 835 836 837
static void absdiff32s( const int* src1, size_t step1,
                        const int* src2, size_t step2,
                        int* dst, size_t step, Size sz, void* )
{
838
    vBinOp32<int, OpAbsDiff<int>, IF_SIMD(VAbsDiff<int>)>(src1, step1, src2, step2, dst, step, sz);
839
}
840

841 842 843 844 845
static void absdiff32f( const float* src1, size_t step1,
                        const float* src2, size_t step2,
                        float* dst, size_t step, Size sz, void* )
{
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
846
           ippiAbsDiff_32f_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz),
847
           (vBinOp32<float, OpAbsDiff<float>, IF_SIMD(VAbsDiff<float>)>(src1, step1, src2, step2, dst, step, sz)));
848
}
849

850 851 852 853
static void absdiff64f( const double* src1, size_t step1,
                        const double* src2, size_t step2,
                        double* dst, size_t step, Size sz, void* )
{
854
    vBinOp64<double, OpAbsDiff<double>, IF_SIMD(VAbsDiff<double>)>(src1, step1, src2, step2, dst, step, sz);
855 856
}

857

858 859 860 861 862
static void and8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
{
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
863
           ippiAnd_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz),
864
           (vBinOp<uchar, OpAnd<uchar>, IF_SIMD(VAnd<uchar>)>(src1, step1, src2, step2, dst, step, sz)));
865 866 867 868 869 870 871
}

static void or8u( const uchar* src1, size_t step1,
                  const uchar* src2, size_t step2,
                  uchar* dst, size_t step, Size sz, void* )
{
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
872
           ippiOr_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz),
873
           (vBinOp<uchar, OpOr<uchar>, IF_SIMD(VOr<uchar>)>(src1, step1, src2, step2, dst, step, sz)));
874 875 876 877 878 879 880
}

static void xor8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
{
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
881
           ippiXor_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz),
882
           (vBinOp<uchar, OpXor<uchar>, IF_SIMD(VXor<uchar>)>(src1, step1, src2, step2, dst, step, sz)));
883
}
884 885 886 887 888

static void not8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
{
I
Ilya Lavrenov 已提交
889
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step); (void *)src2;
890
           ippiNot_8u_C1R(src1, (int)step1, dst, (int)step, (IppiSize&)sz),
891
           (vBinOp<uchar, OpNot<uchar>, IF_SIMD(VNot<uchar>)>(src1, step1, src2, step2, dst, step, sz)));
892
}
893

894 895 896
/****************************************************************************************\
*                                   logical operations                                   *
\****************************************************************************************/
897

898
void convertAndUnrollScalar( const Mat& sc, int buftype, uchar* scbuf, size_t blocksize )
899 900 901 902 903 904 905 906 907 908 909 910 911 912 913
{
    int scn = (int)sc.total(), cn = CV_MAT_CN(buftype);
    size_t esz = CV_ELEM_SIZE(buftype);
    getConvertFunc(sc.depth(), buftype)(sc.data, 0, 0, 0, scbuf, 0, Size(std::min(cn, scn), 1), 0);
    // unroll the scalar
    if( scn < cn )
    {
        CV_Assert( scn == 1 );
        size_t esz1 = CV_ELEM_SIZE1(buftype);
        for( size_t i = esz1; i < esz; i++ )
            scbuf[i] = scbuf[i - esz1];
    }
    for( size_t i = esz; i < blocksize*esz; i++ )
        scbuf[i] = scbuf[i - esz];
}
914

915 916 917

enum { OCL_OP_ADD=0, OCL_OP_SUB=1, OCL_OP_RSUB=2, OCL_OP_ABSDIFF=3, OCL_OP_MUL=4,
       OCL_OP_MUL_SCALE=5, OCL_OP_DIV_SCALE=6, OCL_OP_RECIP_SCALE=7, OCL_OP_ADDW=8,
I
Ilya Lavrenov 已提交
918 919
       OCL_OP_AND=9, OCL_OP_OR=10, OCL_OP_XOR=11, OCL_OP_NOT=12, OCL_OP_MIN=13, OCL_OP_MAX=14,
       OCL_OP_RDIV_SCALE=15 };
920

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921 922
#ifdef HAVE_OPENCL

923 924
static const char* oclop2str[] = { "OP_ADD", "OP_SUB", "OP_RSUB", "OP_ABSDIFF",
    "OP_MUL", "OP_MUL_SCALE", "OP_DIV_SCALE", "OP_RECIP_SCALE",
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925
    "OP_ADDW", "OP_AND", "OP_OR", "OP_XOR", "OP_NOT", "OP_MIN", "OP_MAX", "OP_RDIV_SCALE", 0 };
926 927 928

static bool ocl_binary_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                          InputArray _mask, bool bitwise, int oclop, bool haveScalar )
929
{
930 931 932 933 934
    bool haveMask = !_mask.empty();
    int srctype = _src1.type();
    int srcdepth = CV_MAT_DEPTH(srctype);
    int cn = CV_MAT_CN(srctype);

935
    bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
936
    if( oclop < 0 || ((haveMask || haveScalar) && cn > 4) ||
I
Ilya Lavrenov 已提交
937
            (!doubleSupport && srcdepth == CV_64F && !bitwise))
938 939 940
        return false;

    char opts[1024];
I
Ilya Lavrenov 已提交
941
    int kercn = haveMask || haveScalar ? cn : ocl::predictOptimalVectorWidth(_src1, _src2, _dst);
942 943 944
    int scalarcn = kercn == 3 ? 4 : kercn;

    sprintf(opts, "-D %s%s -D %s -D dstT=%s%s -D dstT_C1=%s -D workST=%s -D cn=%d",
I
Ilya Lavrenov 已提交
945
            haveMask ? "MASK_" : "", haveScalar ? "UNARY_OP" : "BINARY_OP", oclop2str[oclop],
946
            bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, kercn)) :
I
Ilya Lavrenov 已提交
947
                ocl::typeToStr(CV_MAKETYPE(srcdepth, kercn)), doubleSupport ? " -D DOUBLE_SUPPORT" : "",
948
            bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, 1)) :
I
Ilya Lavrenov 已提交
949
                ocl::typeToStr(CV_MAKETYPE(srcdepth, 1)),
950
            bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, scalarcn)) :
I
Ilya Lavrenov 已提交
951
                ocl::typeToStr(CV_MAKETYPE(srcdepth, scalarcn)),
952
            kercn);
953 954

    ocl::Kernel k("KF", ocl::core::arithm_oclsrc, opts);
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955
    if (k.empty())
956 957
        return false;

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958 959 960
    UMat src1 = _src1.getUMat(), src2;
    UMat dst = _dst.getUMat(), mask = _mask.getUMat();

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961 962 963
    ocl::KernelArg src1arg = ocl::KernelArg::ReadOnlyNoSize(src1, cn, kercn);
    ocl::KernelArg dstarg = haveMask ? ocl::KernelArg::ReadWrite(dst, cn, kercn) :
                                       ocl::KernelArg::WriteOnly(dst, cn, kercn);
964 965 966 967
    ocl::KernelArg maskarg = ocl::KernelArg::ReadOnlyNoSize(mask, 1);

    if( haveScalar )
    {
968
        size_t esz = CV_ELEM_SIZE1(srctype)*scalarcn;
969 970 971 972 973 974 975 976
        double buf[4] = {0,0,0,0};

        if( oclop != OCL_OP_NOT )
        {
            Mat src2sc = _src2.getMat();
            convertAndUnrollScalar(src2sc, srctype, (uchar*)buf, 1);
        }

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Ilya Lavrenov 已提交
977
        ocl::KernelArg scalararg = ocl::KernelArg(0, 0, 0, 0, buf, esz);
978 979 980 981 982 983 984 985 986

        if( !haveMask )
            k.args(src1arg, dstarg, scalararg);
        else
            k.args(src1arg, maskarg, dstarg, scalararg);
    }
    else
    {
        src2 = _src2.getUMat();
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987
        ocl::KernelArg src2arg = ocl::KernelArg::ReadOnlyNoSize(src2, cn, kercn);
988 989 990 991 992 993 994

        if( !haveMask )
            k.args(src1arg, src2arg, dstarg);
        else
            k.args(src1arg, src2arg, maskarg, dstarg);
    }

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995
    size_t globalsize[] = { src1.cols * cn / kercn, src1.rows };
996 997 998
    return k.run(2, globalsize, 0, false);
}

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999
#endif
1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011

static void binary_op( InputArray _src1, InputArray _src2, OutputArray _dst,
                       InputArray _mask, const BinaryFunc* tab,
                       bool bitwise, int oclop )
{
    const _InputArray *psrc1 = &_src1, *psrc2 = &_src2;
    int kind1 = psrc1->kind(), kind2 = psrc2->kind();
    int type1 = psrc1->type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
    int type2 = psrc2->type(), depth2 = CV_MAT_DEPTH(type2), cn2 = CV_MAT_CN(type2);
    int dims1 = psrc1->dims(), dims2 = psrc2->dims();
    Size sz1 = dims1 <= 2 ? psrc1->size() : Size();
    Size sz2 = dims2 <= 2 ? psrc2->size() : Size();
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1012
#ifdef HAVE_OPENCL
1013
    bool use_opencl = (kind1 == _InputArray::UMAT || kind2 == _InputArray::UMAT) &&
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Ilya Lavrenov 已提交
1014 1015
            dims1 <= 2 && dims2 <= 2;
#endif
1016 1017
    bool haveMask = !_mask.empty(), haveScalar = false;
    BinaryFunc func;
1018

1019
    if( dims1 <= 2 && dims2 <= 2 && kind1 == kind2 && sz1 == sz2 && type1 == type2 && !haveMask )
1020
    {
1021
        _dst.create(sz1, type1);
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Ilya Lavrenov 已提交
1022 1023 1024
        CV_OCL_RUN(use_opencl,
                   ocl_binary_op(*psrc1, *psrc2, _dst, _mask, bitwise, oclop, false))

1025 1026 1027
        if( bitwise )
        {
            func = *tab;
1028
            cn = (int)CV_ELEM_SIZE(type1);
1029 1030
        }
        else
1031
            func = tab[depth1];
1032

1033
        Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat();
1034
        Size sz = getContinuousSize(src1, src2, dst);
1035
        size_t len = sz.width*(size_t)cn;
1036 1037 1038 1039 1040 1041
        if( len == (size_t)(int)len )
        {
            sz.width = (int)len;
            func(src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, 0);
            return;
        }
1042
    }
1043

1044 1045 1046 1047
    if( oclop == OCL_OP_NOT )
        haveScalar = true;
    else if( (kind1 == _InputArray::MATX) + (kind2 == _InputArray::MATX) == 1 ||
        !psrc1->sameSize(*psrc2) || type1 != type2 )
1048
    {
1049 1050
        if( checkScalar(*psrc1, type2, kind1, kind2) )
        {
1051
            // src1 is a scalar; swap it with src2
1052 1053 1054 1055 1056 1057 1058
            swap(psrc1, psrc2);
            swap(type1, type2);
            swap(depth1, depth2);
            swap(cn, cn2);
            swap(sz1, sz2);
        }
        else if( !checkScalar(*psrc2, type1, kind2, kind1) )
1059 1060 1061 1062 1063
            CV_Error( CV_StsUnmatchedSizes,
                      "The operation is neither 'array op array' (where arrays have the same size and type), "
                      "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
    }
1064 1065 1066 1067
    else
    {
        CV_Assert( psrc1->sameSize(*psrc2) && type1 == type2 );
    }
1068

1069
    size_t esz = CV_ELEM_SIZE(type1);
1070 1071
    size_t blocksize0 = (BLOCK_SIZE + esz-1)/esz;
    BinaryFunc copymask = 0;
1072
    bool reallocate = false;
1073

1074 1075
    if( haveMask )
    {
1076 1077
        int mtype = _mask.type();
        CV_Assert( (mtype == CV_8U || mtype == CV_8S) && _mask.sameSize(*psrc1));
1078
        copymask = getCopyMaskFunc(esz);
1079
        reallocate = !_dst.sameSize(*psrc1) || _dst.type() != type1;
1080
    }
1081

1082 1083
    AutoBuffer<uchar> _buf;
    uchar *scbuf = 0, *maskbuf = 0;
1084

1085
    _dst.createSameSize(*psrc1, type1);
1086
    // if this is mask operation and dst has been reallocated,
1087
    // we have to clear the destination
1088
    if( haveMask && reallocate )
1089 1090
        _dst.setTo(0.);

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1091 1092 1093
    CV_OCL_RUN(use_opencl,
               ocl_binary_op(*psrc1, *psrc2, _dst, _mask, bitwise, oclop, haveScalar))

1094 1095 1096

    Mat src1 = psrc1->getMat(), src2 = psrc2->getMat();
    Mat dst = _dst.getMat(), mask = _mask.getMat();
1097

1098 1099 1100
    if( bitwise )
    {
        func = *tab;
1101
        cn = (int)esz;
1102 1103
    }
    else
1104
        func = tab[depth1];
1105

1106
    if( !haveScalar )
1107
    {
1108 1109
        const Mat* arrays[] = { &src1, &src2, &dst, &mask, 0 };
        uchar* ptrs[4];
1110

1111 1112
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = total;
1113

1114 1115
        if( blocksize*cn > INT_MAX )
            blocksize = INT_MAX/cn;
1116

1117 1118 1119 1120 1121 1122
        if( haveMask )
        {
            blocksize = std::min(blocksize, blocksize0);
            _buf.allocate(blocksize*esz);
            maskbuf = _buf;
        }
1123

1124
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1125
        {
1126
            for( size_t j = 0; j < total; j += blocksize )
1127
            {
1128
                int bsz = (int)MIN(total - j, blocksize);
1129

1130
                func( ptrs[0], 0, ptrs[1], 0, haveMask ? maskbuf : ptrs[2], 0, Size(bsz*cn, 1), 0 );
1131
                if( haveMask )
1132
                {
1133 1134
                    copymask( maskbuf, 0, ptrs[3], 0, ptrs[2], 0, Size(bsz, 1), &esz );
                    ptrs[3] += bsz;
1135
                }
1136

1137 1138
                bsz *= (int)esz;
                ptrs[0] += bsz; ptrs[1] += bsz; ptrs[2] += bsz;
1139 1140
            }
        }
1141 1142 1143 1144 1145
    }
    else
    {
        const Mat* arrays[] = { &src1, &dst, &mask, 0 };
        uchar* ptrs[3];
1146

1147 1148
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
1149

1150 1151 1152
        _buf.allocate(blocksize*(haveMask ? 2 : 1)*esz + 32);
        scbuf = _buf;
        maskbuf = alignPtr(scbuf + blocksize*esz, 16);
1153

1154
        convertAndUnrollScalar( src2, src1.type(), scbuf, blocksize);
1155

1156
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1157
        {
1158
            for( size_t j = 0; j < total; j += blocksize )
1159
            {
1160
                int bsz = (int)MIN(total - j, blocksize);
1161

1162
                func( ptrs[0], 0, scbuf, 0, haveMask ? maskbuf : ptrs[1], 0, Size(bsz*cn, 1), 0 );
1163
                if( haveMask )
1164
                {
1165 1166
                    copymask( maskbuf, 0, ptrs[2], 0, ptrs[1], 0, Size(bsz, 1), &esz );
                    ptrs[2] += bsz;
1167
                }
1168

1169 1170
                bsz *= (int)esz;
                ptrs[0] += bsz; ptrs[1] += bsz;
1171 1172 1173 1174
            }
        }
    }
}
1175

1176
static BinaryFunc* getMaxTab()
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Vadim Pisarevsky 已提交
1177
{
1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188
    static BinaryFunc maxTab[] =
    {
        (BinaryFunc)GET_OPTIMIZED(max8u), (BinaryFunc)GET_OPTIMIZED(max8s),
        (BinaryFunc)GET_OPTIMIZED(max16u), (BinaryFunc)GET_OPTIMIZED(max16s),
        (BinaryFunc)GET_OPTIMIZED(max32s),
        (BinaryFunc)GET_OPTIMIZED(max32f), (BinaryFunc)max64f,
        0
    };

    return maxTab;
}
1189

1190
static BinaryFunc* getMinTab()
1191
{
1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202
    static BinaryFunc minTab[] =
    {
        (BinaryFunc)GET_OPTIMIZED(min8u), (BinaryFunc)GET_OPTIMIZED(min8s),
        (BinaryFunc)GET_OPTIMIZED(min16u), (BinaryFunc)GET_OPTIMIZED(min16s),
        (BinaryFunc)GET_OPTIMIZED(min32s),
        (BinaryFunc)GET_OPTIMIZED(min32f), (BinaryFunc)min64f,
        0
    };

    return minTab;
}
1203

V
Vadim Pisarevsky 已提交
1204
}
1205

1206
void cv::bitwise_and(InputArray a, InputArray b, OutputArray c, InputArray mask)
1207
{
A
Andrey Kamaev 已提交
1208
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(and8u);
1209
    binary_op(a, b, c, mask, &f, true, OCL_OP_AND);
1210 1211
}

1212
void cv::bitwise_or(InputArray a, InputArray b, OutputArray c, InputArray mask)
1213
{
A
Andrey Kamaev 已提交
1214
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(or8u);
1215
    binary_op(a, b, c, mask, &f, true, OCL_OP_OR);
1216 1217
}

1218
void cv::bitwise_xor(InputArray a, InputArray b, OutputArray c, InputArray mask)
1219
{
A
Andrey Kamaev 已提交
1220
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(xor8u);
1221
    binary_op(a, b, c, mask, &f, true, OCL_OP_XOR);
1222 1223
}

1224
void cv::bitwise_not(InputArray a, OutputArray c, InputArray mask)
1225
{
A
Andrey Kamaev 已提交
1226
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(not8u);
1227
    binary_op(a, a, c, mask, &f, true, OCL_OP_NOT);
1228 1229
}

1230
void cv::max( InputArray src1, InputArray src2, OutputArray dst )
1231
{
1232
    binary_op(src1, src2, dst, noArray(), getMaxTab(), false, OCL_OP_MAX );
1233 1234
}

1235
void cv::min( InputArray src1, InputArray src2, OutputArray dst )
1236
{
1237
    binary_op(src1, src2, dst, noArray(), getMinTab(), false, OCL_OP_MIN );
1238 1239
}

1240
void cv::max(const Mat& src1, const Mat& src2, Mat& dst)
1241
{
1242
    OutputArray _dst(dst);
1243
    binary_op(src1, src2, _dst, noArray(), getMaxTab(), false, OCL_OP_MAX );
1244 1245
}

1246 1247 1248
void cv::min(const Mat& src1, const Mat& src2, Mat& dst)
{
    OutputArray _dst(dst);
1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261
    binary_op(src1, src2, _dst, noArray(), getMinTab(), false, OCL_OP_MIN );
}

void cv::max(const UMat& src1, const UMat& src2, UMat& dst)
{
    OutputArray _dst(dst);
    binary_op(src1, src2, _dst, noArray(), getMaxTab(), false, OCL_OP_MAX );
}

void cv::min(const UMat& src1, const UMat& src2, UMat& dst)
{
    OutputArray _dst(dst);
    binary_op(src1, src2, _dst, noArray(), getMinTab(), false, OCL_OP_MIN );
1262
}
1263 1264


1265 1266 1267
/****************************************************************************************\
*                                      add/subtract                                      *
\****************************************************************************************/
1268

1269 1270
namespace cv
{
1271

1272 1273
static int actualScalarDepth(const double* data, int len)
{
1274 1275
    int i = 0, minval = INT_MAX, maxval = INT_MIN;
    for(; i < len; ++i)
1276
    {
1277 1278 1279 1280 1281
        int ival = cvRound(data[i]);
        if( ival != data[i] )
            break;
        minval = MIN(minval, ival);
        maxval = MAX(maxval, ival);
1282
    }
1283
    return i < len ? CV_64F :
A
Andrey Kamaev 已提交
1284 1285 1286 1287
        minval >= 0 && maxval <= (int)UCHAR_MAX ? CV_8U :
        minval >= (int)SCHAR_MIN && maxval <= (int)SCHAR_MAX ? CV_8S :
        minval >= 0 && maxval <= (int)USHRT_MAX ? CV_16U :
        minval >= (int)SHRT_MIN && maxval <= (int)SHRT_MAX ? CV_16S :
1288
        CV_32S;
1289 1290
}

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Ilya Lavrenov 已提交
1291
#ifdef HAVE_OPENCL
1292 1293 1294 1295 1296

static bool ocl_arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                          InputArray _mask, int wtype,
                          void* usrdata, int oclop,
                          bool haveScalar )
1297
{
I
Ilya Lavrenov 已提交
1298
    bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
1299
    int type1 = _src1.type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
1300
    bool haveMask = !_mask.empty();
1301

1302
    if( ((haveMask || haveScalar) && cn > 4) )
1303 1304
        return false;

1305
    int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), wdepth = std::max(CV_32S, CV_MAT_DEPTH(wtype));
I
Ilya Lavrenov 已提交
1306 1307 1308
    if (!doubleSupport)
        wdepth = std::min(wdepth, CV_32F);

1309
    wtype = CV_MAKETYPE(wdepth, cn);
1310
    int type2 = haveScalar ? wtype : _src2.type(), depth2 = CV_MAT_DEPTH(type2);
I
Ilya Lavrenov 已提交
1311 1312
    if (!doubleSupport && (depth2 == CV_64F || depth1 == CV_64F))
        return false;
1313

I
Ilya Lavrenov 已提交
1314
    int kercn = haveMask || haveScalar ? cn : ocl::predictOptimalVectorWidth(_src1, _src2, _dst);
1315
    int scalarcn = kercn == 3 ? 4 : kercn;
1316

I
Ilya Lavrenov 已提交
1317
    char cvtstr[4][32], opts[1024];
1318
    sprintf(opts, "-D %s%s -D %s -D srcT1=%s -D srcT1_C1=%s -D srcT2=%s -D srcT2_C1=%s "
I
Ilya Lavrenov 已提交
1319
            "-D dstT=%s -D dstT_C1=%s -D workT=%s -D workST=%s -D scaleT=%s -D wdepth=%d -D convertToWT1=%s "
1320
            "-D convertToWT2=%s -D convertToDT=%s%s -D cn=%d",
1321 1322
            (haveMask ? "MASK_" : ""), (haveScalar ? "UNARY_OP" : "BINARY_OP"),
            oclop2str[oclop], ocl::typeToStr(CV_MAKETYPE(depth1, kercn)),
1323
            ocl::typeToStr(CV_MAKETYPE(depth1, 1)),
1324
            ocl::typeToStr(CV_MAKETYPE(depth2, kercn)),
1325
            ocl::typeToStr(CV_MAKETYPE(depth2, 1)),
1326
            ocl::typeToStr(CV_MAKETYPE(ddepth, kercn)),
1327
            ocl::typeToStr(CV_MAKETYPE(ddepth, 1)),
1328
            ocl::typeToStr(CV_MAKETYPE(wdepth, kercn)),
1329
            ocl::typeToStr(CV_MAKETYPE(wdepth, scalarcn)),
I
Ilya Lavrenov 已提交
1330
            ocl::typeToStr(CV_MAKETYPE(wdepth, 1)), wdepth,
1331 1332
            ocl::convertTypeStr(depth1, wdepth, kercn, cvtstr[0]),
            ocl::convertTypeStr(depth2, wdepth, kercn, cvtstr[1]),
I
Ilya Lavrenov 已提交
1333
            ocl::convertTypeStr(wdepth, ddepth, kercn, cvtstr[2]),
1334
            doubleSupport ? " -D DOUBLE_SUPPORT" : "", kercn);
1335

I
Ilya Lavrenov 已提交
1336
    size_t usrdata_esz = CV_ELEM_SIZE(wdepth);
1337 1338 1339 1340
    const uchar* usrdata_p = (const uchar*)usrdata;
    const double* usrdata_d = (const double*)usrdata;
    float usrdata_f[3];
    int i, n = oclop == OCL_OP_MUL_SCALE || oclop == OCL_OP_DIV_SCALE ||
I
Ilya Lavrenov 已提交
1341
        oclop == OCL_OP_RDIV_SCALE || oclop == OCL_OP_RECIP_SCALE ? 1 : oclop == OCL_OP_ADDW ? 3 : 0;
1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352
    if( n > 0 && wdepth == CV_32F )
    {
        for( i = 0; i < n; i++ )
            usrdata_f[i] = (float)usrdata_d[i];
        usrdata_p = (const uchar*)usrdata_f;
    }

    ocl::Kernel k("KF", ocl::core::arithm_oclsrc, opts);
    if( k.empty() )
        return false;

I
Ilya Lavrenov 已提交
1353 1354 1355
    UMat src1 = _src1.getUMat(), src2;
    UMat dst = _dst.getUMat(), mask = _mask.getUMat();

I
Ilya Lavrenov 已提交
1356 1357 1358
    ocl::KernelArg src1arg = ocl::KernelArg::ReadOnlyNoSize(src1, cn, kercn);
    ocl::KernelArg dstarg = haveMask ? ocl::KernelArg::ReadWrite(dst, cn, kercn) :
                                       ocl::KernelArg::WriteOnly(dst, cn, kercn);
1359 1360 1361 1362
    ocl::KernelArg maskarg = ocl::KernelArg::ReadOnlyNoSize(mask, 1);

    if( haveScalar )
    {
1363
        size_t esz = CV_ELEM_SIZE1(wtype)*scalarcn;
1364 1365 1366 1367 1368
        double buf[4]={0,0,0,0};
        Mat src2sc = _src2.getMat();

        if( !src2sc.empty() )
            convertAndUnrollScalar(src2sc, wtype, (uchar*)buf, 1);
I
Ilya Lavrenov 已提交
1369
        ocl::KernelArg scalararg = ocl::KernelArg(0, 0, 0, 0, buf, esz);
1370 1371

        if( !haveMask )
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Ilya Lavrenov 已提交
1372 1373 1374 1375 1376
        {
            if(n == 0)
                k.args(src1arg, dstarg, scalararg);
            else if(n == 1)
                k.args(src1arg, dstarg, scalararg,
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1377
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p, usrdata_esz));
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1378 1379 1380
            else
                CV_Error(Error::StsNotImplemented, "unsupported number of extra parameters");
        }
1381 1382 1383 1384 1385 1386
        else
            k.args(src1arg, maskarg, dstarg, scalararg);
    }
    else
    {
        src2 = _src2.getUMat();
I
Ilya Lavrenov 已提交
1387
        ocl::KernelArg src2arg = ocl::KernelArg::ReadOnlyNoSize(src2, cn, kercn);
1388 1389 1390 1391 1392 1393 1394

        if( !haveMask )
        {
            if(n == 0)
                k.args(src1arg, src2arg, dstarg);
            else if(n == 1)
                k.args(src1arg, src2arg, dstarg,
I
Ilya Lavrenov 已提交
1395
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p, usrdata_esz));
1396 1397
            else if(n == 3)
                k.args(src1arg, src2arg, dstarg,
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Ilya Lavrenov 已提交
1398 1399 1400
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p, usrdata_esz),
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p + usrdata_esz, usrdata_esz),
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p + usrdata_esz*2, usrdata_esz));
1401 1402 1403 1404 1405 1406 1407
            else
                CV_Error(Error::StsNotImplemented, "unsupported number of extra parameters");
        }
        else
            k.args(src1arg, src2arg, maskarg, dstarg);
    }

I
Ilya Lavrenov 已提交
1408
    size_t globalsize[] = { src1.cols * cn / kercn, src1.rows };
1409
    return k.run(2, globalsize, NULL, false);
1410 1411
}

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Ilya Lavrenov 已提交
1412
#endif
1413 1414 1415 1416 1417 1418 1419 1420 1421 1422 1423 1424 1425 1426

static void arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                      InputArray _mask, int dtype, BinaryFunc* tab, bool muldiv=false,
                      void* usrdata=0, int oclop=-1 )
{
    const _InputArray *psrc1 = &_src1, *psrc2 = &_src2;
    int kind1 = psrc1->kind(), kind2 = psrc2->kind();
    bool haveMask = !_mask.empty();
    bool reallocate = false;
    int type1 = psrc1->type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
    int type2 = psrc2->type(), depth2 = CV_MAT_DEPTH(type2), cn2 = CV_MAT_CN(type2);
    int wtype, dims1 = psrc1->dims(), dims2 = psrc2->dims();
    Size sz1 = dims1 <= 2 ? psrc1->size() : Size();
    Size sz2 = dims2 <= 2 ? psrc2->size() : Size();
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Ilya Lavrenov 已提交
1427 1428 1429
#ifdef HAVE_OPENCL
    bool use_opencl = _dst.isUMat() && dims1 <= 2 && dims2 <= 2;
#endif
1430 1431 1432 1433 1434 1435
    bool src1Scalar = checkScalar(*psrc1, type2, kind1, kind2);
    bool src2Scalar = checkScalar(*psrc2, type1, kind2, kind1);

    if( (kind1 == kind2 || cn == 1) && sz1 == sz2 && dims1 <= 2 && dims2 <= 2 && type1 == type2 &&
        !haveMask && ((!_dst.fixedType() && (dtype < 0 || CV_MAT_DEPTH(dtype) == depth1)) ||
                       (_dst.fixedType() && _dst.type() == type1)) &&
B
Bo Li 已提交
1436
        ((src1Scalar && src2Scalar) || (!src1Scalar && !src2Scalar)) )
V
Vadim Pisarevsky 已提交
1437
    {
1438
        _dst.createSameSize(*psrc1, type1);
I
Ilya Lavrenov 已提交
1439
        CV_OCL_RUN(use_opencl,
1440 1441 1442
            ocl_arithm_op(*psrc1, *psrc2, _dst, _mask,
                          (!usrdata ? type1 : std::max(depth1, CV_32F)),
                          usrdata, oclop, false))
1443

1444
        Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat();
1445
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
1446
        tab[depth1](src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, usrdata);
V
Vadim Pisarevsky 已提交
1447 1448
        return;
    }
1449

1450
    bool haveScalar = false, swapped12 = false;
1451 1452

    if( dims1 != dims2 || sz1 != sz2 || cn != cn2 ||
1453 1454
        (kind1 == _InputArray::MATX && (sz1 == Size(1,4) || sz1 == Size(1,1))) ||
        (kind2 == _InputArray::MATX && (sz2 == Size(1,4) || sz2 == Size(1,1))) )
1455
    {
1456
        if( checkScalar(*psrc1, type2, kind1, kind2) )
1457 1458
        {
            // src1 is a scalar; swap it with src2
1459 1460 1461 1462 1463 1464
            swap(psrc1, psrc2);
            swap(sz1, sz2);
            swap(type1, type2);
            swap(depth1, depth2);
            swap(cn, cn2);
            swap(dims1, dims2);
1465
            swapped12 = true;
1466 1467
            if( oclop == OCL_OP_SUB )
                oclop = OCL_OP_RSUB;
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Ilya Lavrenov 已提交
1468 1469
            if ( oclop == OCL_OP_DIV_SCALE )
                oclop = OCL_OP_RDIV_SCALE;
1470
        }
1471
        else if( !checkScalar(*psrc2, type1, kind2, kind1) )
1472
            CV_Error( CV_StsUnmatchedSizes,
1473 1474
                     "The operation is neither 'array op array' "
                     "(where arrays have the same size and the same number of channels), "
1475 1476
                     "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
1477
        CV_Assert(type2 == CV_64F && (sz2.height == 1 || sz2.height == 4));
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Andrey Kamaev 已提交
1478

1479 1480
        if (!muldiv)
        {
1481 1482 1483
            Mat sc = psrc2->getMat();
            depth2 = actualScalarDepth(sc.ptr<double>(), cn);
            if( depth2 == CV_64F && (depth1 < CV_32S || depth1 == CV_32F) )
1484 1485
                depth2 = CV_32F;
        }
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Andrey Kamaev 已提交
1486
        else
1487
            depth2 = CV_64F;
1488
    }
1489

1490 1491 1492 1493 1494 1495
    if( dtype < 0 )
    {
        if( _dst.fixedType() )
            dtype = _dst.type();
        else
        {
1496
            if( !haveScalar && type1 != type2 )
1497 1498 1499
                CV_Error(CV_StsBadArg,
                     "When the input arrays in add/subtract/multiply/divide functions have different types, "
                     "the output array type must be explicitly specified");
1500
            dtype = type1;
1501 1502 1503
        }
    }
    dtype = CV_MAT_DEPTH(dtype);
1504

1505 1506 1507 1508 1509 1510 1511
    if( depth1 == depth2 && dtype == depth1 )
        wtype = dtype;
    else if( !muldiv )
    {
        wtype = depth1 <= CV_8S && depth2 <= CV_8S ? CV_16S :
                depth1 <= CV_32S && depth2 <= CV_32S ? CV_32S : std::max(depth1, depth2);
        wtype = std::max(wtype, dtype);
1512

1513 1514 1515 1516 1517 1518 1519 1520 1521 1522 1523
        // when the result of addition should be converted to an integer type,
        // and just one of the input arrays is floating-point, it makes sense to convert that input to integer type before the operation,
        // instead of converting the other input to floating-point and then converting the operation result back to integers.
        if( dtype < CV_32F && (depth1 < CV_32F || depth2 < CV_32F) )
            wtype = CV_32S;
    }
    else
    {
        wtype = std::max(depth1, std::max(depth2, CV_32F));
        wtype = std::max(wtype, dtype);
    }
1524

1525 1526
    dtype = CV_MAKETYPE(dtype, cn);
    wtype = CV_MAKETYPE(wtype, cn);
1527

1528 1529
    if( haveMask )
    {
1530 1531 1532
        int mtype = _mask.type();
        CV_Assert( (mtype == CV_8UC1 || mtype == CV_8SC1) && _mask.sameSize(*psrc1) );
        reallocate = !_dst.sameSize(*psrc1) || _dst.type() != dtype;
1533
    }
1534

1535 1536 1537
    _dst.createSameSize(*psrc1, dtype);
    if( reallocate )
        _dst.setTo(0.);
1538

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Ilya Lavrenov 已提交
1539 1540 1541
    CV_OCL_RUN(use_opencl,
               ocl_arithm_op(*psrc1, *psrc2, _dst, _mask, wtype,
               usrdata, oclop, haveScalar))
1542

1543 1544 1545 1546 1547 1548 1549 1550 1551
    BinaryFunc cvtsrc1 = type1 == wtype ? 0 : getConvertFunc(type1, wtype);
    BinaryFunc cvtsrc2 = type2 == type1 ? cvtsrc1 : type2 == wtype ? 0 : getConvertFunc(type2, wtype);
    BinaryFunc cvtdst = dtype == wtype ? 0 : getConvertFunc(wtype, dtype);

    size_t esz1 = CV_ELEM_SIZE(type1), esz2 = CV_ELEM_SIZE(type2);
    size_t dsz = CV_ELEM_SIZE(dtype), wsz = CV_ELEM_SIZE(wtype);
    size_t blocksize0 = (size_t)(BLOCK_SIZE + wsz-1)/wsz;
    BinaryFunc copymask = getCopyMaskFunc(dsz);
    Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat(), mask = _mask.getMat();
1552

1553 1554 1555 1556 1557 1558
    AutoBuffer<uchar> _buf;
    uchar *buf, *maskbuf = 0, *buf1 = 0, *buf2 = 0, *wbuf = 0;
    size_t bufesz = (cvtsrc1 ? wsz : 0) +
                    (cvtsrc2 || haveScalar ? wsz : 0) +
                    (cvtdst ? wsz : 0) +
                    (haveMask ? dsz : 0);
1559
    BinaryFunc func = tab[CV_MAT_DEPTH(wtype)];
1560

1561 1562 1563 1564
    if( !haveScalar )
    {
        const Mat* arrays[] = { &src1, &src2, &dst, &mask, 0 };
        uchar* ptrs[4];
1565

1566 1567
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = total;
1568

1569 1570 1571 1572 1573 1574 1575 1576 1577 1578 1579 1580 1581 1582
        if( haveMask || cvtsrc1 || cvtsrc2 || cvtdst )
            blocksize = std::min(blocksize, blocksize0);

        _buf.allocate(bufesz*blocksize + 64);
        buf = _buf;
        if( cvtsrc1 )
            buf1 = buf, buf = alignPtr(buf + blocksize*wsz, 16);
        if( cvtsrc2 )
            buf2 = buf, buf = alignPtr(buf + blocksize*wsz, 16);
        wbuf = maskbuf = buf;
        if( cvtdst )
            buf = alignPtr(buf + blocksize*wsz, 16);
        if( haveMask )
            maskbuf = buf;
1583

1584
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1585
        {
1586
            for( size_t j = 0; j < total; j += blocksize )
1587
            {
1588
                int bsz = (int)MIN(total - j, blocksize);
1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600 1601 1602 1603
                Size bszn(bsz*cn, 1);
                const uchar *sptr1 = ptrs[0], *sptr2 = ptrs[1];
                uchar* dptr = ptrs[2];
                if( cvtsrc1 )
                {
                    cvtsrc1( sptr1, 0, 0, 0, buf1, 0, bszn, 0 );
                    sptr1 = buf1;
                }
                if( ptrs[0] == ptrs[1] )
                    sptr2 = sptr1;
                else if( cvtsrc2 )
                {
                    cvtsrc2( sptr2, 0, 0, 0, buf2, 0, bszn, 0 );
                    sptr2 = buf2;
                }
1604

1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616 1617 1618 1619 1620 1621 1622 1623 1624
                if( !haveMask && !cvtdst )
                    func( sptr1, 0, sptr2, 0, dptr, 0, bszn, usrdata );
                else
                {
                    func( sptr1, 0, sptr2, 0, wbuf, 0, bszn, usrdata );
                    if( !haveMask )
                        cvtdst( wbuf, 0, 0, 0, dptr, 0, bszn, 0 );
                    else if( !cvtdst )
                    {
                        copymask( wbuf, 0, ptrs[3], 0, dptr, 0, Size(bsz, 1), &dsz );
                        ptrs[3] += bsz;
                    }
                    else
                    {
                        cvtdst( wbuf, 0, 0, 0, maskbuf, 0, bszn, 0 );
                        copymask( maskbuf, 0, ptrs[3], 0, dptr, 0, Size(bsz, 1), &dsz );
                        ptrs[3] += bsz;
                    }
                }
                ptrs[0] += bsz*esz1; ptrs[1] += bsz*esz2; ptrs[2] += bsz*dsz;
1625 1626
            }
        }
1627 1628 1629 1630 1631
    }
    else
    {
        const Mat* arrays[] = { &src1, &dst, &mask, 0 };
        uchar* ptrs[3];
1632

1633 1634
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
1635

1636 1637 1638 1639 1640 1641 1642 1643 1644 1645
        _buf.allocate(bufesz*blocksize + 64);
        buf = _buf;
        if( cvtsrc1 )
            buf1 = buf, buf = alignPtr(buf + blocksize*wsz, 16);
        buf2 = buf; buf = alignPtr(buf + blocksize*wsz, 16);
        wbuf = maskbuf = buf;
        if( cvtdst )
            buf = alignPtr(buf + blocksize*wsz, 16);
        if( haveMask )
            maskbuf = buf;
1646

1647
        convertAndUnrollScalar( src2, wtype, buf2, blocksize);
1648

1649
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1650
        {
1651 1652
            for( size_t j = 0; j < total; j += blocksize )
            {
1653
                int bsz = (int)MIN(total - j, blocksize);
1654 1655 1656 1657
                Size bszn(bsz*cn, 1);
                const uchar *sptr1 = ptrs[0];
                const uchar* sptr2 = buf2;
                uchar* dptr = ptrs[1];
1658

1659 1660 1661 1662 1663
                if( cvtsrc1 )
                {
                    cvtsrc1( sptr1, 0, 0, 0, buf1, 0, bszn, 0 );
                    sptr1 = buf1;
                }
1664

1665 1666
                if( swapped12 )
                    std::swap(sptr1, sptr2);
1667

1668 1669 1670 1671 1672 1673 1674 1675 1676 1677 1678 1679 1680 1681 1682 1683 1684 1685 1686 1687 1688
                if( !haveMask && !cvtdst )
                    func( sptr1, 0, sptr2, 0, dptr, 0, bszn, usrdata );
                else
                {
                    func( sptr1, 0, sptr2, 0, wbuf, 0, bszn, usrdata );
                    if( !haveMask )
                        cvtdst( wbuf, 0, 0, 0, dptr, 0, bszn, 0 );
                    else if( !cvtdst )
                    {
                        copymask( wbuf, 0, ptrs[2], 0, dptr, 0, Size(bsz, 1), &dsz );
                        ptrs[2] += bsz;
                    }
                    else
                    {
                        cvtdst( wbuf, 0, 0, 0, maskbuf, 0, bszn, 0 );
                        copymask( maskbuf, 0, ptrs[2], 0, dptr, 0, Size(bsz, 1), &dsz );
                        ptrs[2] += bsz;
                    }
                }
                ptrs[0] += bsz*esz1; ptrs[1] += bsz*dsz;
            }
1689 1690 1691
        }
    }
}
1692

1693
static BinaryFunc* getAddTab()
1694
{
1695 1696 1697 1698 1699 1700 1701 1702
    static BinaryFunc addTab[] =
    {
        (BinaryFunc)GET_OPTIMIZED(add8u), (BinaryFunc)GET_OPTIMIZED(add8s),
        (BinaryFunc)GET_OPTIMIZED(add16u), (BinaryFunc)GET_OPTIMIZED(add16s),
        (BinaryFunc)GET_OPTIMIZED(add32s),
        (BinaryFunc)GET_OPTIMIZED(add32f), (BinaryFunc)add64f,
        0
    };
1703

1704 1705 1706 1707
    return addTab;
}

static BinaryFunc* getSubTab()
1708
{
1709 1710 1711 1712 1713 1714 1715 1716 1717 1718 1719
    static BinaryFunc subTab[] =
    {
        (BinaryFunc)GET_OPTIMIZED(sub8u), (BinaryFunc)GET_OPTIMIZED(sub8s),
        (BinaryFunc)GET_OPTIMIZED(sub16u), (BinaryFunc)GET_OPTIMIZED(sub16s),
        (BinaryFunc)GET_OPTIMIZED(sub32s),
        (BinaryFunc)GET_OPTIMIZED(sub32f), (BinaryFunc)sub64f,
        0
    };

    return subTab;
}
1720

1721
static BinaryFunc* getAbsDiffTab()
1722
{
1723 1724 1725 1726 1727 1728 1729 1730 1731 1732 1733
    static BinaryFunc absDiffTab[] =
    {
        (BinaryFunc)GET_OPTIMIZED(absdiff8u), (BinaryFunc)GET_OPTIMIZED(absdiff8s),
        (BinaryFunc)GET_OPTIMIZED(absdiff16u), (BinaryFunc)GET_OPTIMIZED(absdiff16s),
        (BinaryFunc)GET_OPTIMIZED(absdiff32s),
        (BinaryFunc)GET_OPTIMIZED(absdiff32f), (BinaryFunc)absdiff64f,
        0
    };

    return absDiffTab;
}
1734 1735

}
1736

1737 1738
void cv::add( InputArray src1, InputArray src2, OutputArray dst,
          InputArray mask, int dtype )
1739
{
1740
    arithm_op(src1, src2, dst, mask, dtype, getAddTab(), false, 0, OCL_OP_ADD );
1741 1742
}

1743 1744
void cv::subtract( InputArray src1, InputArray src2, OutputArray dst,
               InputArray mask, int dtype )
1745
{
A
Andrey Kamaev 已提交
1746
#ifdef HAVE_TEGRA_OPTIMIZATION
1747
    if (mask.empty() && src1.depth() == CV_8U && src2.depth() == CV_8U)
1748
    {
1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772
        if (dtype == -1 && dst.fixedType())
            dtype = dst.depth();

        if (!dst.fixedType() || dtype == dst.depth())
        {
            if (dtype == CV_16S)
            {
                Mat _dst = dst.getMat();
                if(tegra::subtract_8u8u16s(src1.getMat(), src2.getMat(), _dst))
                    return;
            }
            else if (dtype == CV_32F)
            {
                Mat _dst = dst.getMat();
                if(tegra::subtract_8u8u32f(src1.getMat(), src2.getMat(), _dst))
                    return;
            }
            else if (dtype == CV_8S)
            {
                Mat _dst = dst.getMat();
                if(tegra::subtract_8u8u8s(src1.getMat(), src2.getMat(), _dst))
                    return;
            }
        }
1773
    }
A
Andrey Kamaev 已提交
1774
#endif
1775
    arithm_op(src1, src2, dst, mask, dtype, getSubTab(), false, 0, OCL_OP_SUB );
1776 1777
}

1778
void cv::absdiff( InputArray src1, InputArray src2, OutputArray dst )
1779
{
1780
    arithm_op(src1, src2, dst, noArray(), -1, getAbsDiffTab(), false, 0, OCL_OP_ABSDIFF);
1781
}
1782 1783 1784 1785 1786

/****************************************************************************************\
*                                    multiply/divide                                     *
\****************************************************************************************/

1787 1788 1789
namespace cv
{

1790
template<typename T, typename WT> static void
1791 1792
mul_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, WT scale )
1793
{
1794 1795 1796
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1797

1798
    if( scale == (WT)1. )
1799
    {
1800
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1801
        {
V
Victoria Zhislina 已提交
1802
            int i=0;
1803
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1804
            for(; i <= size.width - 4; i += 4 )
1805
            {
1806 1807 1808 1809 1810 1811
                T t0;
                T t1;
                t0 = saturate_cast<T>(src1[i  ] * src2[i  ]);
                t1 = saturate_cast<T>(src1[i+1] * src2[i+1]);
                dst[i  ] = t0;
                dst[i+1] = t1;
1812 1813 1814

                t0 = saturate_cast<T>(src1[i+2] * src2[i+2]);
                t1 = saturate_cast<T>(src1[i+3] * src2[i+3]);
1815 1816
                dst[i+2] = t0;
                dst[i+3] = t1;
1817
            }
V
Victoria Zhislina 已提交
1818
            #endif
1819 1820 1821 1822 1823 1824
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(src1[i] * src2[i]);
        }
    }
    else
    {
1825
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1826
        {
V
Victoria Zhislina 已提交
1827
            int i = 0;
1828
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1829
            for(; i <= size.width - 4; i += 4 )
1830 1831 1832 1833 1834 1835 1836 1837 1838
            {
                T t0 = saturate_cast<T>(scale*(WT)src1[i]*src2[i]);
                T t1 = saturate_cast<T>(scale*(WT)src1[i+1]*src2[i+1]);
                dst[i] = t0; dst[i+1] = t1;

                t0 = saturate_cast<T>(scale*(WT)src1[i+2]*src2[i+2]);
                t1 = saturate_cast<T>(scale*(WT)src1[i+3]*src2[i+3]);
                dst[i+2] = t0; dst[i+3] = t1;
            }
V
Victoria Zhislina 已提交
1839
            #endif
1840 1841 1842 1843 1844 1845 1846
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(scale*(WT)src1[i]*src2[i]);
        }
    }
}

template<typename T> static void
1847 1848
div_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, double scale )
1849
{
1850 1851 1852
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1853

1854
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1855 1856
    {
        int i = 0;
1857
        #if CV_ENABLE_UNROLLED
1858 1859 1860 1861 1862 1863 1864 1865 1866
        for( ; i <= size.width - 4; i += 4 )
        {
            if( src2[i] != 0 && src2[i+1] != 0 && src2[i+2] != 0 && src2[i+3] != 0 )
            {
                double a = (double)src2[i] * src2[i+1];
                double b = (double)src2[i+2] * src2[i+3];
                double d = scale/(a * b);
                b *= d;
                a *= d;
1867

1868 1869 1870 1871
                T z0 = saturate_cast<T>(src2[i+1] * ((double)src1[i] * b));
                T z1 = saturate_cast<T>(src2[i] * ((double)src1[i+1] * b));
                T z2 = saturate_cast<T>(src2[i+3] * ((double)src1[i+2] * a));
                T z3 = saturate_cast<T>(src2[i+2] * ((double)src1[i+3] * a));
1872

1873 1874 1875 1876 1877 1878 1879 1880 1881
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
            else
            {
                T z0 = src2[i] != 0 ? saturate_cast<T>(src1[i]*scale/src2[i]) : 0;
                T z1 = src2[i+1] != 0 ? saturate_cast<T>(src1[i+1]*scale/src2[i+1]) : 0;
                T z2 = src2[i+2] != 0 ? saturate_cast<T>(src1[i+2]*scale/src2[i+2]) : 0;
                T z3 = src2[i+3] != 0 ? saturate_cast<T>(src1[i+3]*scale/src2[i+3]) : 0;
1882

1883 1884 1885 1886
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1887
        #endif
1888 1889 1890 1891 1892 1893
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(src1[i]*scale/src2[i]) : 0;
    }
}

template<typename T> static void
1894 1895
recip_( const T*, size_t, const T* src2, size_t step2,
        T* dst, size_t step, Size size, double scale )
1896
{
1897 1898
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1899

1900
    for( ; size.height--; src2 += step2, dst += step )
1901 1902
    {
        int i = 0;
1903
        #if CV_ENABLE_UNROLLED
1904 1905 1906 1907 1908 1909 1910 1911 1912
        for( ; i <= size.width - 4; i += 4 )
        {
            if( src2[i] != 0 && src2[i+1] != 0 && src2[i+2] != 0 && src2[i+3] != 0 )
            {
                double a = (double)src2[i] * src2[i+1];
                double b = (double)src2[i+2] * src2[i+3];
                double d = scale/(a * b);
                b *= d;
                a *= d;
1913

1914 1915 1916 1917
                T z0 = saturate_cast<T>(src2[i+1] * b);
                T z1 = saturate_cast<T>(src2[i] * b);
                T z2 = saturate_cast<T>(src2[i+3] * a);
                T z3 = saturate_cast<T>(src2[i+2] * a);
1918

1919 1920 1921 1922 1923 1924 1925 1926 1927
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
            else
            {
                T z0 = src2[i] != 0 ? saturate_cast<T>(scale/src2[i]) : 0;
                T z1 = src2[i+1] != 0 ? saturate_cast<T>(scale/src2[i+1]) : 0;
                T z2 = src2[i+2] != 0 ? saturate_cast<T>(scale/src2[i+2]) : 0;
                T z3 = src2[i+3] != 0 ? saturate_cast<T>(scale/src2[i+3]) : 0;
1928

1929 1930 1931 1932
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1933
        #endif
1934 1935 1936 1937
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(scale/src2[i]) : 0;
    }
}
1938 1939


1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968
static void mul8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* scale)
{
    mul_(src1, step1, src2, step2, dst, step, sz, (float)*(const double*)scale);
}

static void mul8s( const schar* src1, size_t step1, const schar* src2, size_t step2,
                   schar* dst, size_t step, Size sz, void* scale)
{
    mul_(src1, step1, src2, step2, dst, step, sz, (float)*(const double*)scale);
}

static void mul16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* scale)
{
    mul_(src1, step1, src2, step2, dst, step, sz, (float)*(const double*)scale);
}

static void mul16s( const short* src1, size_t step1, const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* scale)
{
    mul_(src1, step1, src2, step2, dst, step, sz, (float)*(const double*)scale);
}

static void mul32s( const int* src1, size_t step1, const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* scale)
{
    mul_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}
1969

1970 1971 1972 1973 1974
static void mul32f( const float* src1, size_t step1, const float* src2, size_t step2,
                    float* dst, size_t step, Size sz, void* scale)
{
    mul_(src1, step1, src2, step2, dst, step, sz, (float)*(const double*)scale);
}
1975

1976 1977 1978 1979 1980
static void mul64f( const double* src1, size_t step1, const double* src2, size_t step2,
                    double* dst, size_t step, Size sz, void* scale)
{
    mul_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}
1981

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049
static void div8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* scale)
{
    if( src1 )
        div_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
    else
        recip_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void div8s( const schar* src1, size_t step1, const schar* src2, size_t step2,
                  schar* dst, size_t step, Size sz, void* scale)
{
    div_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void div16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* scale)
{
    div_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void div16s( const short* src1, size_t step1, const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* scale)
{
    div_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void div32s( const int* src1, size_t step1, const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* scale)
{
    div_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void div32f( const float* src1, size_t step1, const float* src2, size_t step2,
                    float* dst, size_t step, Size sz, void* scale)
{
    div_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void div64f( const double* src1, size_t step1, const double* src2, size_t step2,
                    double* dst, size_t step, Size sz, void* scale)
{
    div_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void recip8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                  uchar* dst, size_t step, Size sz, void* scale)
{
    recip_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void recip8s( const schar* src1, size_t step1, const schar* src2, size_t step2,
                  schar* dst, size_t step, Size sz, void* scale)
{
    recip_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void recip16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                   ushort* dst, size_t step, Size sz, void* scale)
{
    recip_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void recip16s( const short* src1, size_t step1, const short* src2, size_t step2,
                   short* dst, size_t step, Size sz, void* scale)
{
    recip_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}
2050

2051 2052 2053 2054 2055 2056 2057 2058 2059 2060 2061 2062 2063 2064 2065 2066 2067
static void recip32s( const int* src1, size_t step1, const int* src2, size_t step2,
                   int* dst, size_t step, Size sz, void* scale)
{
    recip_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void recip32f( const float* src1, size_t step1, const float* src2, size_t step2,
                   float* dst, size_t step, Size sz, void* scale)
{
    recip_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}

static void recip64f( const double* src1, size_t step1, const double* src2, size_t step2,
                   double* dst, size_t step, Size sz, void* scale)
{
    recip_(src1, step1, src2, step2, dst, step, sz, *(const double*)scale);
}
2068 2069


2070
static BinaryFunc* getMulTab()
2071
{
2072 2073 2074 2075 2076 2077 2078 2079 2080
    static BinaryFunc mulTab[] =
    {
        (BinaryFunc)mul8u, (BinaryFunc)mul8s, (BinaryFunc)mul16u,
        (BinaryFunc)mul16s, (BinaryFunc)mul32s, (BinaryFunc)mul32f,
        (BinaryFunc)mul64f, 0
    };

    return mulTab;
}
2081

2082
static BinaryFunc* getDivTab()
2083
{
2084 2085 2086 2087 2088 2089
    static BinaryFunc divTab[] =
    {
        (BinaryFunc)div8u, (BinaryFunc)div8s, (BinaryFunc)div16u,
        (BinaryFunc)div16s, (BinaryFunc)div32s, (BinaryFunc)div32f,
        (BinaryFunc)div64f, 0
    };
2090

2091 2092 2093 2094
    return divTab;
}

static BinaryFunc* getRecipTab()
2095
{
2096 2097 2098 2099 2100 2101
    static BinaryFunc recipTab[] =
    {
        (BinaryFunc)recip8u, (BinaryFunc)recip8s, (BinaryFunc)recip16u,
        (BinaryFunc)recip16s, (BinaryFunc)recip32s, (BinaryFunc)recip32f,
        (BinaryFunc)recip64f, 0
    };
2102

2103 2104
    return recipTab;
}
2105

2106
}
2107

2108
void cv::multiply(InputArray src1, InputArray src2,
2109
                  OutputArray dst, double scale, int dtype)
2110
{
2111
    arithm_op(src1, src2, dst, noArray(), dtype, getMulTab(),
I
Ilya Lavrenov 已提交
2112
              true, &scale, std::abs(scale - 1.0) < DBL_EPSILON ? OCL_OP_MUL : OCL_OP_MUL_SCALE);
2113
}
2114

2115
void cv::divide(InputArray src1, InputArray src2,
2116 2117
                OutputArray dst, double scale, int dtype)
{
2118
    arithm_op(src1, src2, dst, noArray(), dtype, getDivTab(), true, &scale, OCL_OP_DIV_SCALE);
2119 2120
}

2121
void cv::divide(double scale, InputArray src2,
2122 2123
                OutputArray dst, int dtype)
{
2124
    arithm_op(src2, src2, dst, noArray(), dtype, getRecipTab(), true, &scale, OCL_OP_RECIP_SCALE);
2125 2126
}

2127 2128 2129 2130
/****************************************************************************************\
*                                      addWeighted                                       *
\****************************************************************************************/

2131 2132 2133
namespace cv
{

2134
template<typename T, typename WT> static void
2135 2136 2137 2138 2139 2140 2141 2142 2143 2144
addWeighted_( const T* src1, size_t step1, const T* src2, size_t step2,
              T* dst, size_t step, Size size, void* _scalars )
{
    const double* scalars = (const double*)_scalars;
    WT alpha = (WT)scalars[0], beta = (WT)scalars[1], gamma = (WT)scalars[2];
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);

    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2145
    {
2146
        int x = 0;
2147
        #if CV_ENABLE_UNROLLED
2148
        for( ; x <= size.width - 4; x += 4 )
2149
        {
2150 2151 2152
            T t0 = saturate_cast<T>(src1[x]*alpha + src2[x]*beta + gamma);
            T t1 = saturate_cast<T>(src1[x+1]*alpha + src2[x+1]*beta + gamma);
            dst[x] = t0; dst[x+1] = t1;
2153

2154 2155 2156
            t0 = saturate_cast<T>(src1[x+2]*alpha + src2[x+2]*beta + gamma);
            t1 = saturate_cast<T>(src1[x+3]*alpha + src2[x+3]*beta + gamma);
            dst[x+2] = t0; dst[x+3] = t1;
2157
        }
V
Victoria Zhislina 已提交
2158
        #endif
2159 2160
        for( ; x < size.width; x++ )
            dst[x] = saturate_cast<T>(src1[x]*alpha + src2[x]*beta + gamma);
2161 2162 2163 2164 2165
    }
}


static void
2166 2167 2168 2169 2170 2171 2172
addWeighted8u( const uchar* src1, size_t step1,
               const uchar* src2, size_t step2,
               uchar* dst, size_t step, Size size,
               void* _scalars )
{
    const double* scalars = (const double*)_scalars;
    float alpha = (float)scalars[0], beta = (float)scalars[1], gamma = (float)scalars[2];
2173

2174
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2175
    {
2176
        int x = 0;
2177

2178 2179
#if CV_SSE2
        if( USE_SSE2 )
2180
        {
2181 2182
            __m128 a4 = _mm_set1_ps(alpha), b4 = _mm_set1_ps(beta), g4 = _mm_set1_ps(gamma);
            __m128i z = _mm_setzero_si128();
2183

2184
            for( ; x <= size.width - 8; x += 8 )
2185
            {
2186 2187
                __m128i u = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(src1 + x)), z);
                __m128i v = _mm_unpacklo_epi8(_mm_loadl_epi64((const __m128i*)(src2 + x)), z);
2188

2189 2190 2191 2192
                __m128 u0 = _mm_cvtepi32_ps(_mm_unpacklo_epi16(u, z));
                __m128 u1 = _mm_cvtepi32_ps(_mm_unpackhi_epi16(u, z));
                __m128 v0 = _mm_cvtepi32_ps(_mm_unpacklo_epi16(v, z));
                __m128 v1 = _mm_cvtepi32_ps(_mm_unpackhi_epi16(v, z));
2193

2194 2195 2196
                u0 = _mm_add_ps(_mm_mul_ps(u0, a4), _mm_mul_ps(v0, b4));
                u1 = _mm_add_ps(_mm_mul_ps(u1, a4), _mm_mul_ps(v1, b4));
                u0 = _mm_add_ps(u0, g4); u1 = _mm_add_ps(u1, g4);
2197

2198 2199
                u = _mm_packs_epi32(_mm_cvtps_epi32(u0), _mm_cvtps_epi32(u1));
                u = _mm_packus_epi16(u, u);
2200

2201
                _mm_storel_epi64((__m128i*)(dst + x), u);
2202 2203
            }
        }
2204
#endif
2205
        #if CV_ENABLE_UNROLLED
2206
        for( ; x <= size.width - 4; x += 4 )
2207
        {
2208 2209 2210
            float t0, t1;
            t0 = CV_8TO32F(src1[x])*alpha + CV_8TO32F(src2[x])*beta + gamma;
            t1 = CV_8TO32F(src1[x+1])*alpha + CV_8TO32F(src2[x+1])*beta + gamma;
2211

2212 2213
            dst[x] = saturate_cast<uchar>(t0);
            dst[x+1] = saturate_cast<uchar>(t1);
2214

2215 2216
            t0 = CV_8TO32F(src1[x+2])*alpha + CV_8TO32F(src2[x+2])*beta + gamma;
            t1 = CV_8TO32F(src1[x+3])*alpha + CV_8TO32F(src2[x+3])*beta + gamma;
2217

2218 2219 2220
            dst[x+2] = saturate_cast<uchar>(t0);
            dst[x+3] = saturate_cast<uchar>(t1);
        }
V
Victoria Zhislina 已提交
2221
        #endif
2222

2223 2224 2225 2226
        for( ; x < size.width; x++ )
        {
            float t0 = CV_8TO32F(src1[x])*alpha + CV_8TO32F(src2[x])*beta + gamma;
            dst[x] = saturate_cast<uchar>(t0);
2227 2228 2229 2230
        }
    }
}

2231 2232
static void addWeighted8s( const schar* src1, size_t step1, const schar* src2, size_t step2,
                           schar* dst, size_t step, Size sz, void* scalars )
2233
{
2234
    addWeighted_<schar, float>(src1, step1, src2, step2, dst, step, sz, scalars);
2235 2236
}

2237 2238
static void addWeighted16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                            ushort* dst, size_t step, Size sz, void* scalars )
2239
{
2240 2241
    addWeighted_<ushort, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2242

2243 2244
static void addWeighted16s( const short* src1, size_t step1, const short* src2, size_t step2,
                            short* dst, size_t step, Size sz, void* scalars )
2245
{
2246 2247
    addWeighted_<short, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2248

2249 2250
static void addWeighted32s( const int* src1, size_t step1, const int* src2, size_t step2,
                            int* dst, size_t step, Size sz, void* scalars )
2251
{
2252
    addWeighted_<int, double>(src1, step1, src2, step2, dst, step, sz, scalars);
2253 2254
}

2255 2256
static void addWeighted32f( const float* src1, size_t step1, const float* src2, size_t step2,
                            float* dst, size_t step, Size sz, void* scalars )
2257
{
2258 2259
    addWeighted_<float, double>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2260

2261 2262 2263 2264 2265
static void addWeighted64f( const double* src1, size_t step1, const double* src2, size_t step2,
                            double* dst, size_t step, Size sz, void* scalars )
{
    addWeighted_<double, double>(src1, step1, src2, step2, dst, step, sz, scalars);
}
V
Vadim Pisarevsky 已提交
2266

2267
static BinaryFunc* getAddWeightedTab()
2268
{
2269 2270 2271 2272 2273 2274 2275 2276 2277
    static BinaryFunc addWeightedTab[] =
    {
        (BinaryFunc)GET_OPTIMIZED(addWeighted8u), (BinaryFunc)GET_OPTIMIZED(addWeighted8s), (BinaryFunc)GET_OPTIMIZED(addWeighted16u),
        (BinaryFunc)GET_OPTIMIZED(addWeighted16s), (BinaryFunc)GET_OPTIMIZED(addWeighted32s), (BinaryFunc)addWeighted32f,
        (BinaryFunc)addWeighted64f, 0
    };

    return addWeightedTab;
}
2278

2279
}
2280

2281
void cv::addWeighted( InputArray src1, double alpha, InputArray src2,
2282 2283 2284
                      double beta, double gamma, OutputArray dst, int dtype )
{
    double scalars[] = {alpha, beta, gamma};
2285
    arithm_op(src1, src2, dst, noArray(), dtype, getAddWeightedTab(), true, scalars, OCL_OP_ADDW);
2286 2287
}

2288

2289
/****************************************************************************************\
2290
*                                          compare                                       *
2291 2292
\****************************************************************************************/

2293
namespace cv
2294 2295
{

2296 2297 2298
template<typename T> static void
cmp_(const T* src1, size_t step1, const T* src2, size_t step2,
     uchar* dst, size_t step, Size size, int code)
2299
{
2300 2301 2302
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    if( code == CMP_GE || code == CMP_LT )
2303
    {
2304 2305 2306
        std::swap(src1, src2);
        std::swap(step1, step2);
        code = code == CMP_GE ? CMP_LE : CMP_GT;
2307
    }
2308

2309
    if( code == CMP_GT || code == CMP_LE )
2310
    {
2311 2312 2313 2314
        int m = code == CMP_GT ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2315
            #if CV_ENABLE_UNROLLED
2316 2317 2318 2319 2320 2321 2322 2323 2324 2325
            for( ; x <= size.width - 4; x += 4 )
            {
                int t0, t1;
                t0 = -(src1[x] > src2[x]) ^ m;
                t1 = -(src1[x+1] > src2[x+1]) ^ m;
                dst[x] = (uchar)t0; dst[x+1] = (uchar)t1;
                t0 = -(src1[x+2] > src2[x+2]) ^ m;
                t1 = -(src1[x+3] > src2[x+3]) ^ m;
                dst[x+2] = (uchar)t0; dst[x+3] = (uchar)t1;
            }
V
Victoria Zhislina 已提交
2326
            #endif
2327 2328
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2329
               }
2330
    }
2331
    else if( code == CMP_EQ || code == CMP_NE )
2332
    {
2333 2334 2335 2336
        int m = code == CMP_EQ ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2337
            #if CV_ENABLE_UNROLLED
2338 2339 2340 2341 2342 2343 2344 2345 2346 2347
            for( ; x <= size.width - 4; x += 4 )
            {
                int t0, t1;
                t0 = -(src1[x] == src2[x]) ^ m;
                t1 = -(src1[x+1] == src2[x+1]) ^ m;
                dst[x] = (uchar)t0; dst[x+1] = (uchar)t1;
                t0 = -(src1[x+2] == src2[x+2]) ^ m;
                t1 = -(src1[x+3] == src2[x+3]) ^ m;
                dst[x+2] = (uchar)t0; dst[x+3] = (uchar)t1;
            }
V
Victoria Zhislina 已提交
2348
            #endif
2349 2350 2351
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
2352
    }
2353
}
2354

K
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2355 2356 2357 2358 2359 2360 2361 2362 2363 2364 2365
#if ARITHM_USE_IPP
inline static IppCmpOp convert_cmp(int _cmpop)
{
    return _cmpop == CMP_EQ ? ippCmpEq :
        _cmpop == CMP_GT ? ippCmpGreater :
        _cmpop == CMP_GE ? ippCmpGreaterEq :
        _cmpop == CMP_LT ? ippCmpLess :
        _cmpop == CMP_LE ? ippCmpLessEq :
        (IppCmpOp)-1;
}
#endif
2366

2367 2368
static void cmp8u(const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2369
{
K
kdrobnyh 已提交
2370 2371 2372 2373 2374 2375 2376 2377 2378
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  >= 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
        if( ippiCompare_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op) >= 0 )
            return;
    }
#endif
2379
  //vz optimized  cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2380
    int code = *(int*)_cmpop;
2381 2382 2383 2384 2385 2386 2387 2388 2389 2390 2391 2392 2393 2394 2395
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    if( code == CMP_GE || code == CMP_LT )
    {
        std::swap(src1, src2);
        std::swap(step1, step2);
        code = code == CMP_GE ? CMP_LE : CMP_GT;
    }

    if( code == CMP_GT || code == CMP_LE )
    {
        int m = code == CMP_GT ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x =0;
2396 2397
            #if CV_SSE2
            if( USE_SSE2 ){
2398 2399
                __m128i m128 = code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
                __m128i c128 = _mm_set1_epi8 (-128);
2400 2401 2402 2403 2404 2405 2406 2407 2408 2409 2410 2411 2412
                for( ; x <= size.width - 16; x += 16 )
                {
                    __m128i r00 = _mm_loadu_si128((const __m128i*)(src1 + x));
                    __m128i r10 = _mm_loadu_si128((const __m128i*)(src2 + x));
                    // no simd for 8u comparison, that's why we need the trick
                    r00 = _mm_sub_epi8(r00,c128);
                    r10 = _mm_sub_epi8(r10,c128);

                    r00 =_mm_xor_si128(_mm_cmpgt_epi8(r00, r10), m128);
                    _mm_storeu_si128((__m128i*)(dst + x),r00);

                }
            }
2413 2414
           #endif

2415
            for( ; x < size.width; x++ ){
2416
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2417
            }
2418 2419 2420 2421 2422
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2423
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2424 2425
        {
            int x = 0;
2426 2427
            #if CV_SSE2
            if( USE_SSE2 ){
2428
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
2429 2430 2431 2432 2433 2434 2435 2436
                for( ; x <= size.width - 16; x += 16 )
                {
                    __m128i r00 = _mm_loadu_si128((const __m128i*)(src1 + x));
                    __m128i r10 = _mm_loadu_si128((const __m128i*)(src2 + x));
                    r00 = _mm_xor_si128 ( _mm_cmpeq_epi8 (r00, r10), m128);
                    _mm_storeu_si128((__m128i*)(dst + x), r00);
                }
            }
2437 2438 2439 2440 2441
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2442 2443
}

2444 2445
static void cmp8s(const schar* src1, size_t step1, const schar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2446
{
2447
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2448 2449
}

2450 2451
static void cmp16u(const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2452
{
K
kdrobnyh 已提交
2453 2454 2455 2456 2457 2458 2459 2460 2461
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  >= 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
        if( ippiCompare_16u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op) >= 0 )
            return;
    }
#endif
2462
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2463 2464
}

2465 2466
static void cmp16s(const short* src1, size_t step1, const short* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2467
{
K
kdrobnyh 已提交
2468 2469 2470 2471 2472 2473 2474 2475 2476
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  > 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
        if( ippiCompare_16s_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op) >= 0 )
            return;
    }
#endif
2477 2478
   //vz optimized cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);

2479
    int code = *(int*)_cmpop;
2480 2481 2482 2483 2484 2485 2486 2487 2488 2489 2490 2491 2492 2493 2494
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    if( code == CMP_GE || code == CMP_LT )
    {
        std::swap(src1, src2);
        std::swap(step1, step2);
        code = code == CMP_GE ? CMP_LE : CMP_GT;
    }

    if( code == CMP_GT || code == CMP_LE )
    {
        int m = code == CMP_GT ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x =0;
2495 2496
            #if CV_SSE2
            if( USE_SSE2){//
2497
                __m128i m128 =  code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2498 2499 2500 2501 2502 2503 2504 2505 2506 2507 2508 2509 2510 2511 2512 2513 2514 2515 2516 2517 2518 2519
                for( ; x <= size.width - 16; x += 16 )
                {
                    __m128i r00 = _mm_loadu_si128((const __m128i*)(src1 + x));
                    __m128i r10 = _mm_loadu_si128((const __m128i*)(src2 + x));
                    r00 = _mm_xor_si128 ( _mm_cmpgt_epi16 (r00, r10), m128);
                    __m128i r01 = _mm_loadu_si128((const __m128i*)(src1 + x + 8));
                    __m128i r11 = _mm_loadu_si128((const __m128i*)(src2 + x + 8));
                    r01 = _mm_xor_si128 ( _mm_cmpgt_epi16 (r01, r11), m128);
                    r11 = _mm_packs_epi16(r00, r01);
                    _mm_storeu_si128((__m128i*)(dst + x), r11);
                }
                if( x <= size.width-8)
                {
                    __m128i r00 = _mm_loadu_si128((const __m128i*)(src1 + x));
                    __m128i r10 = _mm_loadu_si128((const __m128i*)(src2 + x));
                    r00 = _mm_xor_si128 ( _mm_cmpgt_epi16 (r00, r10), m128);
                    r10 = _mm_packs_epi16(r00, r00);
                    _mm_storel_epi64((__m128i*)(dst + x), r10);

                    x += 8;
                }
            }
2520 2521
           #endif

2522
            for( ; x < size.width; x++ ){
2523
                 dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2524
            }
2525 2526 2527 2528 2529
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2530
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2531 2532
        {
            int x = 0;
2533 2534
            #if CV_SSE2
            if( USE_SSE2 ){
2535
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2536 2537 2538 2539 2540 2541 2542 2543 2544 2545 2546 2547 2548 2549 2550 2551 2552 2553 2554 2555 2556 2557
                for( ; x <= size.width - 16; x += 16 )
                {
                    __m128i r00 = _mm_loadu_si128((const __m128i*)(src1 + x));
                    __m128i r10 = _mm_loadu_si128((const __m128i*)(src2 + x));
                    r00 = _mm_xor_si128 ( _mm_cmpeq_epi16 (r00, r10), m128);
                    __m128i r01 = _mm_loadu_si128((const __m128i*)(src1 + x + 8));
                    __m128i r11 = _mm_loadu_si128((const __m128i*)(src2 + x + 8));
                    r01 = _mm_xor_si128 ( _mm_cmpeq_epi16 (r01, r11), m128);
                    r11 = _mm_packs_epi16(r00, r01);
                    _mm_storeu_si128((__m128i*)(dst + x), r11);
                }
                if( x <= size.width - 8)
                {
                    __m128i r00 = _mm_loadu_si128((const __m128i*)(src1 + x));
                    __m128i r10 = _mm_loadu_si128((const __m128i*)(src2 + x));
                    r00 = _mm_xor_si128 ( _mm_cmpeq_epi16 (r00, r10), m128);
                    r10 = _mm_packs_epi16(r00, r00);
                    _mm_storel_epi64((__m128i*)(dst + x), r10);

                    x += 8;
                }
            }
2558 2559 2560 2561 2562
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2563 2564
}

2565 2566 2567 2568 2569
static void cmp32s(const int* src1, size_t step1, const int* src2, size_t step2,
                   uchar* dst, size_t step, Size size, void* _cmpop)
{
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
}
2570

2571 2572
static void cmp32f(const float* src1, size_t step1, const float* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2573
{
K
kdrobnyh 已提交
2574 2575 2576 2577 2578 2579 2580 2581 2582
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  >= 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
        if( ippiCompare_32f_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op) >= 0 )
            return;
    }
#endif
2583 2584
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
}
2585

2586 2587
static void cmp64f(const double* src1, size_t step1, const double* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2588
{
2589
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2590 2591
}

2592
static BinaryFunc getCmpFunc(int depth)
2593
{
2594 2595 2596 2597 2598 2599 2600 2601
    static BinaryFunc cmpTab[] =
    {
        (BinaryFunc)GET_OPTIMIZED(cmp8u), (BinaryFunc)GET_OPTIMIZED(cmp8s),
        (BinaryFunc)GET_OPTIMIZED(cmp16u), (BinaryFunc)GET_OPTIMIZED(cmp16s),
        (BinaryFunc)GET_OPTIMIZED(cmp32s),
        (BinaryFunc)GET_OPTIMIZED(cmp32f), (BinaryFunc)cmp64f,
        0
    };
2602

2603 2604
    return cmpTab[depth];
}
2605

2606
static double getMinVal(int depth)
2607
{
2608 2609 2610
    static const double tab[] = {0, -128, 0, -32768, INT_MIN, -FLT_MAX, -DBL_MAX, 0};
    return tab[depth];
}
2611

2612
static double getMaxVal(int depth)
2613
{
2614 2615 2616
    static const double tab[] = {255, 127, 65535, 32767, INT_MAX, FLT_MAX, DBL_MAX, 0};
    return tab[depth];
}
2617

I
Ilya Lavrenov 已提交
2618 2619
#ifdef HAVE_OPENCL

I
Ilya Lavrenov 已提交
2620 2621 2622 2623 2624 2625 2626 2627 2628 2629 2630 2631
static bool ocl_compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op)
{
    if ( !((_src1.isMat() || _src1.isUMat()) && (_src2.isMat() || _src2.isUMat())) )
        return false;

    bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
    int type = _src1.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type), type2 = _src2.type();
    if (!doubleSupport && (depth == CV_64F || _src2.depth() == CV_64F))
        return false;

    const char * const operationMap[] = { "==", ">", ">=", "<", "<=", "!=" };
    ocl::Kernel k("KF", ocl::core::arithm_oclsrc,
2632
                  format("-D BINARY_OP -D srcT1=%s -D workT=srcT1 -D cn=1"
I
Ilya Lavrenov 已提交
2633 2634 2635 2636
                         " -D OP_CMP -D CMP_OPERATOR=%s%s",
                         ocl::typeToStr(CV_MAKE_TYPE(depth, 1)),
                         operationMap[op],
                         doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
I
Ilya Lavrenov 已提交
2637 2638 2639 2640 2641 2642 2643 2644 2645 2646
    if (k.empty())
        return false;

    CV_Assert(type == type2);
    UMat src1 = _src1.getUMat(), src2 = _src2.getUMat();
    Size size = src1.size();
    CV_Assert(size == src2.size());

    _dst.create(size, CV_8UC(cn));
    UMat dst = _dst.getUMat();
I
Ilya Lavrenov 已提交
2647 2648 2649 2650 2651 2652 2653 2654 2655

    k.args(ocl::KernelArg::ReadOnlyNoSize(src1),
           ocl::KernelArg::ReadOnlyNoSize(src2),
           ocl::KernelArg::WriteOnly(dst, cn));

    size_t globalsize[2] = { dst.cols * cn, dst.rows };
    return k.run(2, globalsize, NULL, false);
}

I
Ilya Lavrenov 已提交
2656 2657
#endif

2658 2659
}

2660
void cv::compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op)
2661 2662 2663
{
    CV_Assert( op == CMP_LT || op == CMP_LE || op == CMP_EQ ||
               op == CMP_NE || op == CMP_GE || op == CMP_GT );
2664

I
Ilya Lavrenov 已提交
2665 2666
    CV_OCL_RUN(_src1.dims() <= 2 && _src2.dims() <= 2 && _dst.isUMat(),
               ocl_compare(_src1, _src2, _dst, op))
I
Ilya Lavrenov 已提交
2667

2668 2669
    int kind1 = _src1.kind(), kind2 = _src2.kind();
    Mat src1 = _src1.getMat(), src2 = _src2.getMat();
2670

2671
    if( kind1 == kind2 && src1.dims <= 2 && src2.dims <= 2 && src1.size() == src2.size() && src1.type() == src2.type() )
2672
    {
2673 2674
        int cn = src1.channels();
        _dst.create(src1.size(), CV_8UC(cn));
2675 2676
        Mat dst = _dst.getMat();
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
2677
        getCmpFunc(src1.depth())(src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, &op);
2678 2679
        return;
    }
2680

2681
    bool haveScalar = false;
2682

2683
    if( (kind1 == _InputArray::MATX) + (kind2 == _InputArray::MATX) == 1 ||
2684 2685 2686
        src1.size != src2.size || src1.type() != src2.type() )
    {
        if( checkScalar(src1, src2.type(), kind1, kind2) )
2687
        {
2688 2689 2690 2691 2692 2693 2694 2695 2696 2697 2698
            // src1 is a scalar; swap it with src2
            swap(src1, src2);
            op = op == CMP_LT ? CMP_GT : op == CMP_LE ? CMP_GE :
                op == CMP_GE ? CMP_LE : op == CMP_GT ? CMP_LT : op;
        }
        else if( !checkScalar(src2, src1.type(), kind2, kind1) )
            CV_Error( CV_StsUnmatchedSizes,
                     "The operation is neither 'array op array' (where arrays have the same size and the same type), "
                     "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
    }
2699

2700

2701
    int cn = src1.channels(), depth1 = src1.depth(), depth2 = src2.depth();
2702

2703 2704 2705
    _dst.create(src1.dims, src1.size, CV_8UC(cn));
    src1 = src1.reshape(1); src2 = src2.reshape(1);
    Mat dst = _dst.getMat().reshape(1);
2706

2707 2708
    size_t esz = src1.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
2709
    BinaryFunc func = getCmpFunc(depth1);
2710

2711
    if( !haveScalar )
2712
    {
2713 2714
        const Mat* arrays[] = { &src1, &src2, &dst, 0 };
        uchar* ptrs[3];
2715

2716 2717
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size;
2718

2719 2720
        for( size_t i = 0; i < it.nplanes; i++, ++it )
            func( ptrs[0], 0, ptrs[1], 0, ptrs[2], 0, Size((int)total, 1), &op );
2721
    }
2722
    else
2723
    {
2724 2725
        const Mat* arrays[] = { &src1, &dst, 0 };
        uchar* ptrs[2];
2726

2727 2728
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
2729

2730 2731 2732 2733 2734 2735
        AutoBuffer<uchar> _buf(blocksize*esz);
        uchar *buf = _buf;

        if( depth1 > CV_32S )
            convertAndUnrollScalar( src2, depth1, buf, blocksize );
        else
2736
        {
2737 2738 2739 2740 2741 2742 2743
            double fval=0;
            getConvertFunc(depth2, CV_64F)(src2.data, 0, 0, 0, (uchar*)&fval, 0, Size(1,1), 0);
            if( fval < getMinVal(depth1) )
            {
                dst = Scalar::all(op == CMP_GT || op == CMP_GE || op == CMP_NE ? 255 : 0);
                return;
            }
2744

2745 2746 2747 2748 2749
            if( fval > getMaxVal(depth1) )
            {
                dst = Scalar::all(op == CMP_LT || op == CMP_LE || op == CMP_NE ? 255 : 0);
                return;
            }
2750

2751 2752 2753 2754 2755 2756 2757 2758 2759 2760 2761 2762 2763 2764 2765
            int ival = cvRound(fval);
            if( fval != ival )
            {
                if( op == CMP_LT || op == CMP_GE )
                    ival = cvCeil(fval);
                else if( op == CMP_LE || op == CMP_GT )
                    ival = cvFloor(fval);
                else
                {
                    dst = Scalar::all(op == CMP_NE ? 255 : 0);
                    return;
                }
            }
            convertAndUnrollScalar(Mat(1, 1, CV_32S, &ival), depth1, buf, blocksize);
        }
2766

2767
        for( size_t i = 0; i < it.nplanes; i++, ++it )
2768
        {
2769 2770
            for( size_t j = 0; j < total; j += blocksize )
            {
2771
                int bsz = (int)MIN(total - j, blocksize);
2772 2773 2774 2775 2776
                func( ptrs[0], 0, buf, 0, ptrs[1], 0, Size(bsz, 1), &op);
                ptrs[0] += bsz*esz;
                ptrs[1] += bsz;
            }
        }
2777
    }
2778
}
2779

2780 2781 2782
/****************************************************************************************\
*                                        inRange                                         *
\****************************************************************************************/
2783

2784 2785
namespace cv
{
2786

2787 2788 2789 2790 2791 2792 2793 2794
template<typename T> static void
inRange_(const T* src1, size_t step1, const T* src2, size_t step2,
         const T* src3, size_t step3, uchar* dst, size_t step,
         Size size)
{
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step3 /= sizeof(src3[0]);
2795

2796
    for( ; size.height--; src1 += step1, src2 += step2, src3 += step3, dst += step )
V
Vadim Pisarevsky 已提交
2797
    {
2798
        int x = 0;
2799
        #if CV_ENABLE_UNROLLED
2800
        for( ; x <= size.width - 4; x += 4 )
V
Vadim Pisarevsky 已提交
2801
        {
2802 2803 2804 2805 2806 2807 2808
            int t0, t1;
            t0 = src2[x] <= src1[x] && src1[x] <= src3[x];
            t1 = src2[x+1] <= src1[x+1] && src1[x+1] <= src3[x+1];
            dst[x] = (uchar)-t0; dst[x+1] = (uchar)-t1;
            t0 = src2[x+2] <= src1[x+2] && src1[x+2] <= src3[x+2];
            t1 = src2[x+3] <= src1[x+3] && src1[x+3] <= src3[x+3];
            dst[x+2] = (uchar)-t0; dst[x+3] = (uchar)-t1;
V
Vadim Pisarevsky 已提交
2809
        }
V
Victoria Zhislina 已提交
2810
        #endif
2811 2812
        for( ; x < size.width; x++ )
            dst[x] = (uchar)-(src2[x] <= src1[x] && src1[x] <= src3[x]);
V
Vadim Pisarevsky 已提交
2813
    }
2814 2815
}

2816

2817 2818
static void inRange8u(const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                      const uchar* src3, size_t step3, uchar* dst, size_t step, Size size)
2819
{
2820 2821
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2822

2823 2824
static void inRange8s(const schar* src1, size_t step1, const schar* src2, size_t step2,
                      const schar* src3, size_t step3, uchar* dst, size_t step, Size size)
2825
{
2826 2827
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2828

2829 2830
static void inRange16u(const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                       const ushort* src3, size_t step3, uchar* dst, size_t step, Size size)
2831
{
2832 2833
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2834

2835 2836 2837 2838
static void inRange16s(const short* src1, size_t step1, const short* src2, size_t step2,
                       const short* src3, size_t step3, uchar* dst, size_t step, Size size)
{
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
2839 2840
}

2841 2842
static void inRange32s(const int* src1, size_t step1, const int* src2, size_t step2,
                       const int* src3, size_t step3, uchar* dst, size_t step, Size size)
2843
{
2844 2845
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2846

2847 2848 2849 2850
static void inRange32f(const float* src1, size_t step1, const float* src2, size_t step2,
                       const float* src3, size_t step3, uchar* dst, size_t step, Size size)
{
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
2851 2852
}

2853 2854
static void inRange64f(const double* src1, size_t step1, const double* src2, size_t step2,
                       const double* src3, size_t step3, uchar* dst, size_t step, Size size)
2855
{
2856
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
2857
}
2858

2859 2860 2861 2862 2863 2864 2865 2866 2867 2868 2869 2870 2871 2872 2873 2874
static void inRangeReduce(const uchar* src, uchar* dst, size_t len, int cn)
{
    int k = cn % 4 ? cn % 4 : 4;
    size_t i, j;
    if( k == 1 )
        for( i = j = 0; i < len; i++, j += cn )
            dst[i] = src[j];
    else if( k == 2 )
        for( i = j = 0; i < len; i++, j += cn )
            dst[i] = src[j] & src[j+1];
    else if( k == 3 )
        for( i = j = 0; i < len; i++, j += cn )
            dst[i] = src[j] & src[j+1] & src[j+2];
    else
        for( i = j = 0; i < len; i++, j += cn )
            dst[i] = src[j] & src[j+1] & src[j+2] & src[j+3];
2875

2876 2877 2878 2879
    for( ; k < cn; k += 4 )
    {
        for( i = 0, j = k; i < len; i++, j += cn )
            dst[i] &= src[j] & src[j+1] & src[j+2] & src[j+3];
V
Vadim Pisarevsky 已提交
2880
    }
2881
}
2882

2883 2884
typedef void (*InRangeFunc)( const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                             const uchar* src3, size_t step3, uchar* dst, size_t step, Size sz );
2885

2886
static InRangeFunc getInRangeFunc(int depth)
2887
{
2888 2889 2890 2891 2892 2893 2894 2895 2896
    static InRangeFunc inRangeTab[] =
    {
        (InRangeFunc)GET_OPTIMIZED(inRange8u), (InRangeFunc)GET_OPTIMIZED(inRange8s), (InRangeFunc)GET_OPTIMIZED(inRange16u),
        (InRangeFunc)GET_OPTIMIZED(inRange16s), (InRangeFunc)GET_OPTIMIZED(inRange32s), (InRangeFunc)GET_OPTIMIZED(inRange32f),
        (InRangeFunc)inRange64f, 0
    };

    return inRangeTab[depth];
}
2897

I
Ilya Lavrenov 已提交
2898 2899
#ifdef HAVE_OPENCL

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Ilya Lavrenov 已提交
2900 2901 2902 2903 2904 2905 2906 2907 2908 2909 2910 2911 2912 2913 2914 2915 2916 2917 2918 2919 2920 2921 2922 2923 2924 2925 2926 2927 2928 2929 2930 2931 2932 2933 2934 2935 2936 2937 2938 2939 2940 2941 2942 2943 2944 2945 2946 2947 2948 2949 2950 2951 2952 2953 2954 2955 2956 2957 2958 2959 2960 2961 2962 2963 2964 2965 2966 2967 2968 2969 2970 2971 2972 2973 2974 2975 2976 2977 2978 2979 2980 2981 2982 2983 2984 2985 2986 2987 2988 2989 2990 2991 2992 2993 2994 2995 2996 2997 2998 2999 3000 3001 3002 3003 3004 3005
static bool ocl_inRange( InputArray _src, InputArray _lowerb,
                         InputArray _upperb, OutputArray _dst )
{
    int skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
    Size ssize = _src.size(), lsize = _lowerb.size(), usize = _upperb.size();
    int stype = _src.type(), ltype = _lowerb.type(), utype = _upperb.type();
    int sdepth = CV_MAT_DEPTH(stype), ldepth = CV_MAT_DEPTH(ltype), udepth = CV_MAT_DEPTH(utype);
    int cn = CV_MAT_CN(stype);
    bool lbScalar = false, ubScalar = false;

    if( (lkind == _InputArray::MATX && skind != _InputArray::MATX) ||
        ssize != lsize || stype != ltype )
    {
        if( !checkScalar(_lowerb, stype, lkind, skind) )
            CV_Error( CV_StsUnmatchedSizes,
                     "The lower bounary is neither an array of the same size and same type as src, nor a scalar");
        lbScalar = true;
    }

    if( (ukind == _InputArray::MATX && skind != _InputArray::MATX) ||
        ssize != usize || stype != utype )
    {
        if( !checkScalar(_upperb, stype, ukind, skind) )
            CV_Error( CV_StsUnmatchedSizes,
                     "The upper bounary is neither an array of the same size and same type as src, nor a scalar");
        ubScalar = true;
    }

    if (lbScalar != ubScalar)
        return false;

    bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0,
            haveScalar = lbScalar && ubScalar;

    if ( (!doubleSupport && sdepth == CV_64F) ||
         (!haveScalar && (sdepth != ldepth || sdepth != udepth)) )
        return false;

    ocl::Kernel ker("inrange", ocl::core::inrange_oclsrc,
                    format("%s-D cn=%d -D T=%s%s", haveScalar ? "-D HAVE_SCALAR " : "",
                           cn, ocl::typeToStr(sdepth), doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
    if (ker.empty())
        return false;

    _dst.create(ssize, CV_8UC1);
    UMat src = _src.getUMat(), dst = _dst.getUMat(), lscalaru, uscalaru;
    Mat lscalar, uscalar;

    if (lbScalar && ubScalar)
    {
        lscalar = _lowerb.getMat();
        uscalar = _upperb.getMat();

        size_t esz = src.elemSize();
        size_t blocksize = 36;

        AutoBuffer<uchar> _buf(blocksize*(((int)lbScalar + (int)ubScalar)*esz + cn) + 2*cn*sizeof(int) + 128);
        uchar *buf = alignPtr(_buf + blocksize*cn, 16);

        if( ldepth != sdepth && sdepth < CV_32S )
        {
            int* ilbuf = (int*)alignPtr(buf + blocksize*esz, 16);
            int* iubuf = ilbuf + cn;

            BinaryFunc sccvtfunc = getConvertFunc(ldepth, CV_32S);
            sccvtfunc(lscalar.data, 0, 0, 0, (uchar*)ilbuf, 0, Size(cn, 1), 0);
            sccvtfunc(uscalar.data, 0, 0, 0, (uchar*)iubuf, 0, Size(cn, 1), 0);
            int minval = cvRound(getMinVal(sdepth)), maxval = cvRound(getMaxVal(sdepth));

            for( int k = 0; k < cn; k++ )
            {
                if( ilbuf[k] > iubuf[k] || ilbuf[k] > maxval || iubuf[k] < minval )
                    ilbuf[k] = minval+1, iubuf[k] = minval;
            }
            lscalar = Mat(cn, 1, CV_32S, ilbuf);
            uscalar = Mat(cn, 1, CV_32S, iubuf);
        }

        lscalar.convertTo(lscalar, stype);
        uscalar.convertTo(uscalar, stype);
    }
    else
    {
        lscalaru = _lowerb.getUMat();
        uscalaru = _upperb.getUMat();
    }

    ocl::KernelArg srcarg = ocl::KernelArg::ReadOnlyNoSize(src),
            dstarg = ocl::KernelArg::WriteOnly(dst);

    if (haveScalar)
    {
        lscalar.copyTo(lscalaru);
        uscalar.copyTo(uscalaru);

        ker.args(srcarg, dstarg, ocl::KernelArg::PtrReadOnly(lscalaru),
               ocl::KernelArg::PtrReadOnly(uscalaru));
    }
    else
        ker.args(srcarg, dstarg, ocl::KernelArg::ReadOnlyNoSize(lscalaru),
               ocl::KernelArg::ReadOnlyNoSize(uscalaru));

    size_t globalsize[2] = { ssize.width, ssize.height };
    return ker.run(2, globalsize, NULL, false);
}

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Ilya Lavrenov 已提交
3006 3007
#endif

3008 3009
}

3010 3011
void cv::inRange(InputArray _src, InputArray _lowerb,
                 InputArray _upperb, OutputArray _dst)
3012
{
I
Ilya Lavrenov 已提交
3013 3014 3015
    CV_OCL_RUN(_src.dims() <= 2 && _lowerb.dims() <= 2 &&
               _upperb.dims() <= 2 && _dst.isUMat(),
               ocl_inRange(_src, _lowerb, _upperb, _dst))
I
Ilya Lavrenov 已提交
3016

3017 3018
    int skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
    Mat src = _src.getMat(), lb = _lowerb.getMat(), ub = _upperb.getMat();
3019

3020
    bool lbScalar = false, ubScalar = false;
3021

3022
    if( (lkind == _InputArray::MATX && skind != _InputArray::MATX) ||
3023 3024 3025 3026 3027 3028 3029
        src.size != lb.size || src.type() != lb.type() )
    {
        if( !checkScalar(lb, src.type(), lkind, skind) )
            CV_Error( CV_StsUnmatchedSizes,
                     "The lower bounary is neither an array of the same size and same type as src, nor a scalar");
        lbScalar = true;
    }
3030

3031
    if( (ukind == _InputArray::MATX && skind != _InputArray::MATX) ||
3032 3033 3034 3035 3036 3037 3038
        src.size != ub.size || src.type() != ub.type() )
    {
        if( !checkScalar(ub, src.type(), ukind, skind) )
            CV_Error( CV_StsUnmatchedSizes,
                     "The upper bounary is neither an array of the same size and same type as src, nor a scalar");
        ubScalar = true;
    }
3039

I
Ilya Lavrenov 已提交
3040
    CV_Assert(lbScalar == ubScalar);
3041

3042
    int cn = src.channels(), depth = src.depth();
3043

3044 3045
    size_t esz = src.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
3046

I
Ilya Lavrenov 已提交
3047
    _dst.create(src.dims, src.size, CV_8UC1);
3048
    Mat dst = _dst.getMat();
3049
    InRangeFunc func = getInRangeFunc(depth);
3050

3051 3052 3053
    const Mat* arrays_sc[] = { &src, &dst, 0 };
    const Mat* arrays_nosc[] = { &src, &dst, &lb, &ub, 0 };
    uchar* ptrs[4];
3054

3055 3056
    NAryMatIterator it(lbScalar && ubScalar ? arrays_sc : arrays_nosc, ptrs);
    size_t total = it.size, blocksize = std::min(total, blocksize0);
3057

3058 3059 3060
    AutoBuffer<uchar> _buf(blocksize*(((int)lbScalar + (int)ubScalar)*esz + cn) + 2*cn*sizeof(int) + 128);
    uchar *buf = _buf, *mbuf = buf, *lbuf = 0, *ubuf = 0;
    buf = alignPtr(buf + blocksize*cn, 16);
3061

3062 3063 3064 3065
    if( lbScalar && ubScalar )
    {
        lbuf = buf;
        ubuf = buf = alignPtr(buf + blocksize*esz, 16);
3066

3067 3068
        CV_Assert( lb.type() == ub.type() );
        int scdepth = lb.depth();
3069

3070 3071 3072 3073
        if( scdepth != depth && depth < CV_32S )
        {
            int* ilbuf = (int*)alignPtr(buf + blocksize*esz, 16);
            int* iubuf = ilbuf + cn;
3074

3075 3076 3077
            BinaryFunc sccvtfunc = getConvertFunc(scdepth, CV_32S);
            sccvtfunc(lb.data, 0, 0, 0, (uchar*)ilbuf, 0, Size(cn, 1), 0);
            sccvtfunc(ub.data, 0, 0, 0, (uchar*)iubuf, 0, Size(cn, 1), 0);
3078
            int minval = cvRound(getMinVal(depth)), maxval = cvRound(getMaxVal(depth));
3079

3080 3081 3082 3083 3084 3085 3086 3087
            for( int k = 0; k < cn; k++ )
            {
                if( ilbuf[k] > iubuf[k] || ilbuf[k] > maxval || iubuf[k] < minval )
                    ilbuf[k] = minval+1, iubuf[k] = minval;
            }
            lb = Mat(cn, 1, CV_32S, ilbuf);
            ub = Mat(cn, 1, CV_32S, iubuf);
        }
3088

3089 3090 3091
        convertAndUnrollScalar( lb, src.type(), lbuf, blocksize );
        convertAndUnrollScalar( ub, src.type(), ubuf, blocksize );
    }
3092

3093
    for( size_t i = 0; i < it.nplanes; i++, ++it )
V
Vadim Pisarevsky 已提交
3094
    {
3095 3096
        for( size_t j = 0; j < total; j += blocksize )
        {
3097
            int bsz = (int)MIN(total - j, blocksize);
3098 3099 3100 3101 3102 3103 3104 3105 3106 3107 3108 3109 3110 3111
            size_t delta = bsz*esz;
            uchar *lptr = lbuf, *uptr = ubuf;
            if( !lbScalar )
            {
                lptr = ptrs[2];
                ptrs[2] += delta;
            }
            if( !ubScalar )
            {
                int idx = !lbScalar ? 3 : 2;
                uptr = ptrs[idx];
                ptrs[idx] += delta;
            }
            func( ptrs[0], 0, lptr, 0, uptr, 0, cn == 1 ? ptrs[1] : mbuf, 0, Size(bsz*cn, 1));
3112
            if( cn > 1 )
3113 3114 3115 3116
                inRangeReduce(mbuf, ptrs[1], bsz, cn);
            ptrs[0] += delta;
            ptrs[1] += bsz;
        }
V
Vadim Pisarevsky 已提交
3117
    }
3118 3119 3120 3121 3122 3123 3124 3125 3126 3127
}

/****************************************************************************************\
*                                Earlier API: cvAdd etc.                                 *
\****************************************************************************************/

CV_IMPL void
cvNot( const CvArr* srcarr, CvArr* dstarr )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
3128
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3129 3130 3131 3132 3133 3134 3135 3136 3137
    cv::bitwise_not( src, dst );
}


CV_IMPL void
cvAnd( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), src2 = cv::cvarrToMat(srcarr2),
        dst = cv::cvarrToMat(dstarr), mask;
3138
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3139 3140 3141 3142 3143
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
    cv::bitwise_and( src1, src2, dst, mask );
}

3144

3145 3146 3147 3148 3149
CV_IMPL void
cvOr( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), src2 = cv::cvarrToMat(srcarr2),
        dst = cv::cvarrToMat(dstarr), mask;
3150
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3151 3152 3153 3154 3155 3156 3157 3158 3159 3160 3161
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
    cv::bitwise_or( src1, src2, dst, mask );
}


CV_IMPL void
cvXor( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), src2 = cv::cvarrToMat(srcarr2),
        dst = cv::cvarrToMat(dstarr), mask;
3162
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3163 3164 3165 3166 3167 3168 3169 3170 3171 3172
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
    cv::bitwise_xor( src1, src2, dst, mask );
}


CV_IMPL void
cvAndS( const CvArr* srcarr, CvScalar s, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), mask;
3173
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3174 3175
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3176
    cv::bitwise_and( src, (const cv::Scalar&)s, dst, mask );
3177 3178 3179 3180 3181 3182 3183
}


CV_IMPL void
cvOrS( const CvArr* srcarr, CvScalar s, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), mask;
3184
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3185 3186
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3187
    cv::bitwise_or( src, (const cv::Scalar&)s, dst, mask );
3188 3189 3190 3191 3192 3193 3194
}


CV_IMPL void
cvXorS( const CvArr* srcarr, CvScalar s, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), mask;
3195
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3196 3197
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3198
    cv::bitwise_xor( src, (const cv::Scalar&)s, dst, mask );
3199 3200
}

3201

3202 3203 3204 3205
CV_IMPL void cvAdd( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), src2 = cv::cvarrToMat(srcarr2),
        dst = cv::cvarrToMat(dstarr), mask;
3206
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3207 3208
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3209
    cv::add( src1, src2, dst, mask, dst.type() );
3210 3211
}

3212

3213 3214 3215 3216
CV_IMPL void cvSub( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), src2 = cv::cvarrToMat(srcarr2),
        dst = cv::cvarrToMat(dstarr), mask;
3217
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3218 3219
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3220
    cv::subtract( src1, src2, dst, mask, dst.type() );
3221 3222
}

3223

3224 3225 3226 3227
CV_IMPL void cvAddS( const CvArr* srcarr1, CvScalar value, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1),
        dst = cv::cvarrToMat(dstarr), mask;
3228
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3229 3230
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3231
    cv::add( src1, (const cv::Scalar&)value, dst, mask, dst.type() );
3232 3233
}

3234

3235 3236 3237 3238
CV_IMPL void cvSubRS( const CvArr* srcarr1, CvScalar value, CvArr* dstarr, const CvArr* maskarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1),
        dst = cv::cvarrToMat(dstarr), mask;
3239
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3240 3241
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3242
    cv::subtract( (const cv::Scalar&)value, src1, dst, mask, dst.type() );
3243 3244
}

3245

3246 3247 3248 3249 3250
CV_IMPL void cvMul( const CvArr* srcarr1, const CvArr* srcarr2,
                    CvArr* dstarr, double scale )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), src2 = cv::cvarrToMat(srcarr2),
        dst = cv::cvarrToMat(dstarr);
3251 3252
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::multiply( src1, src2, dst, scale, dst.type() );
3253 3254
}

3255

3256 3257 3258 3259 3260
CV_IMPL void cvDiv( const CvArr* srcarr1, const CvArr* srcarr2,
                    CvArr* dstarr, double scale )
{
    cv::Mat src2 = cv::cvarrToMat(srcarr2),
        dst = cv::cvarrToMat(dstarr), mask;
3261
    CV_Assert( src2.size == dst.size && src2.channels() == dst.channels() );
3262 3263

    if( srcarr1 )
3264
        cv::divide( cv::cvarrToMat(srcarr1), src2, dst, scale, dst.type() );
3265
    else
3266
        cv::divide( scale, src2, dst, dst.type() );
3267 3268 3269 3270 3271 3272 3273 3274 3275 3276
}


CV_IMPL void
cvAddWeighted( const CvArr* srcarr1, double alpha,
               const CvArr* srcarr2, double beta,
               double gamma, CvArr* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), src2 = cv::cvarrToMat(srcarr2),
        dst = cv::cvarrToMat(dstarr);
3277 3278
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::addWeighted( src1, alpha, src2, beta, gamma, dst, dst.type() );
3279 3280 3281 3282 3283 3284 3285
}


CV_IMPL  void
cvAbsDiff( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3286
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3287 3288 3289 3290 3291 3292 3293 3294 3295

    cv::absdiff( src1, cv::cvarrToMat(srcarr2), dst );
}


CV_IMPL void
cvAbsDiffS( const CvArr* srcarr1, CvArr* dstarr, CvScalar scalar )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3296
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3297

3298
    cv::absdiff( src1, (const cv::Scalar&)scalar, dst );
3299 3300
}

3301

3302 3303 3304 3305 3306
CV_IMPL void
cvInRange( const void* srcarr1, const void* srcarr2,
           const void* srcarr3, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3307
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3308 3309 3310 3311

    cv::inRange( src1, cv::cvarrToMat(srcarr2), cv::cvarrToMat(srcarr3), dst );
}

3312

3313 3314 3315 3316
CV_IMPL void
cvInRangeS( const void* srcarr1, CvScalar lowerb, CvScalar upperb, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3317
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3318

3319
    cv::inRange( src1, (const cv::Scalar&)lowerb, (const cv::Scalar&)upperb, dst );
3320 3321 3322 3323 3324 3325 3326
}


CV_IMPL void
cvCmp( const void* srcarr1, const void* srcarr2, void* dstarr, int cmp_op )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3327
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3328 3329 3330 3331 3332 3333 3334 3335 3336

    cv::compare( src1, cv::cvarrToMat(srcarr2), dst, cmp_op );
}


CV_IMPL void
cvCmpS( const void* srcarr1, double value, void* dstarr, int cmp_op )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3337
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3338 3339 3340 3341 3342 3343 3344 3345 3346

    cv::compare( src1, value, dst, cmp_op );
}


CV_IMPL void
cvMin( const void* srcarr1, const void* srcarr2, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3347
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3348 3349 3350 3351 3352 3353 3354 3355 3356

    cv::min( src1, cv::cvarrToMat(srcarr2), dst );
}


CV_IMPL void
cvMax( const void* srcarr1, const void* srcarr2, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3357
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3358 3359 3360 3361

    cv::max( src1, cv::cvarrToMat(srcarr2), dst );
}

3362

3363 3364 3365 3366
CV_IMPL void
cvMinS( const void* srcarr1, double value, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3367
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3368 3369 3370 3371 3372 3373 3374 3375 3376

    cv::min( src1, value, dst );
}


CV_IMPL void
cvMaxS( const void* srcarr1, double value, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3377
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3378 3379 3380 3381 3382

    cv::max( src1, value, dst );
}

/* End of file. */