arithm.cpp 122.4 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);
I
Ilya Lavrenov 已提交
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();
I
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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) &&
I
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);
I
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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Ilya Lavrenov 已提交
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 1324 1325
            ocl::typeToStr(depth1), ocl::typeToStr(CV_MAKETYPE(depth2, kercn)),
            ocl::typeToStr(depth2), ocl::typeToStr(CV_MAKETYPE(ddepth, kercn)),
            ocl::typeToStr(ddepth), ocl::typeToStr(CV_MAKETYPE(wdepth, kercn)),
1326
            ocl::typeToStr(CV_MAKETYPE(wdepth, scalarcn)),
1327
            ocl::typeToStr(wdepth), wdepth,
1328 1329
            ocl::convertTypeStr(depth1, wdepth, kercn, cvtstr[0]),
            ocl::convertTypeStr(depth2, wdepth, kercn, cvtstr[1]),
I
Ilya Lavrenov 已提交
1330
            ocl::convertTypeStr(wdepth, ddepth, kercn, cvtstr[2]),
1331
            doubleSupport ? " -D DOUBLE_SUPPORT" : "", kercn);
1332

I
Ilya Lavrenov 已提交
1333
    size_t usrdata_esz = CV_ELEM_SIZE(wdepth);
1334 1335 1336 1337
    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
1338
        oclop == OCL_OP_RDIV_SCALE || oclop == OCL_OP_RECIP_SCALE ? 1 : oclop == OCL_OP_ADDW ? 3 : 0;
1339 1340 1341 1342 1343 1344 1345 1346
    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);
1347
    if (k.empty())
1348 1349
        return false;

I
Ilya Lavrenov 已提交
1350 1351 1352
    UMat src1 = _src1.getUMat(), src2;
    UMat dst = _dst.getUMat(), mask = _mask.getUMat();

I
Ilya Lavrenov 已提交
1353 1354 1355
    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);
1356 1357 1358 1359
    ocl::KernelArg maskarg = ocl::KernelArg::ReadOnlyNoSize(mask, 1);

    if( haveScalar )
    {
1360
        size_t esz = CV_ELEM_SIZE1(wtype)*scalarcn;
1361 1362 1363 1364 1365
        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
1366
        ocl::KernelArg scalararg = ocl::KernelArg(0, 0, 0, 0, buf, esz);
1367 1368

        if( !haveMask )
I
Ilya Lavrenov 已提交
1369 1370 1371 1372 1373
        {
            if(n == 0)
                k.args(src1arg, dstarg, scalararg);
            else if(n == 1)
                k.args(src1arg, dstarg, scalararg,
I
Ilya Lavrenov 已提交
1374
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p, usrdata_esz));
I
Ilya Lavrenov 已提交
1375 1376 1377
            else
                CV_Error(Error::StsNotImplemented, "unsupported number of extra parameters");
        }
1378 1379 1380 1381 1382 1383
        else
            k.args(src1arg, maskarg, dstarg, scalararg);
    }
    else
    {
        src2 = _src2.getUMat();
I
Ilya Lavrenov 已提交
1384
        ocl::KernelArg src2arg = ocl::KernelArg::ReadOnlyNoSize(src2, cn, kercn);
1385 1386 1387

        if( !haveMask )
        {
1388
            if (n == 0)
1389
                k.args(src1arg, src2arg, dstarg);
1390
            else if (n == 1)
1391
                k.args(src1arg, src2arg, dstarg,
I
Ilya Lavrenov 已提交
1392
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p, usrdata_esz));
1393
            else if (n == 3)
1394
                k.args(src1arg, src2arg, dstarg,
I
Ilya Lavrenov 已提交
1395 1396 1397
                       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));
1398 1399 1400 1401 1402 1403 1404
            else
                CV_Error(Error::StsNotImplemented, "unsupported number of extra parameters");
        }
        else
            k.args(src1arg, src2arg, maskarg, dstarg);
    }

I
Ilya Lavrenov 已提交
1405
    size_t globalsize[] = { src1.cols * cn / kercn, src1.rows };
1406
    return k.run(2, globalsize, NULL, false);
1407 1408
}

I
Ilya Lavrenov 已提交
1409
#endif
1410 1411 1412 1413 1414 1415 1416 1417 1418 1419 1420 1421 1422 1423

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();
I
Ilya Lavrenov 已提交
1424 1425 1426
#ifdef HAVE_OPENCL
    bool use_opencl = _dst.isUMat() && dims1 <= 2 && dims2 <= 2;
#endif
1427 1428 1429 1430 1431 1432
    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
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1433
        ((src1Scalar && src2Scalar) || (!src1Scalar && !src2Scalar)) )
V
Vadim Pisarevsky 已提交
1434
    {
1435
        _dst.createSameSize(*psrc1, type1);
I
Ilya Lavrenov 已提交
1436
        CV_OCL_RUN(use_opencl,
1437 1438 1439
            ocl_arithm_op(*psrc1, *psrc2, _dst, _mask,
                          (!usrdata ? type1 : std::max(depth1, CV_32F)),
                          usrdata, oclop, false))
1440

1441
        Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat();
1442
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
1443
        tab[depth1](src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, usrdata);
V
Vadim Pisarevsky 已提交
1444 1445
        return;
    }
1446

1447
    bool haveScalar = false, swapped12 = false;
1448 1449

    if( dims1 != dims2 || sz1 != sz2 || cn != cn2 ||
1450 1451
        (kind1 == _InputArray::MATX && (sz1 == Size(1,4) || sz1 == Size(1,1))) ||
        (kind2 == _InputArray::MATX && (sz2 == Size(1,4) || sz2 == Size(1,1))) )
1452
    {
1453
        if( checkScalar(*psrc1, type2, kind1, kind2) )
1454 1455
        {
            // src1 is a scalar; swap it with src2
1456 1457 1458 1459 1460 1461
            swap(psrc1, psrc2);
            swap(sz1, sz2);
            swap(type1, type2);
            swap(depth1, depth2);
            swap(cn, cn2);
            swap(dims1, dims2);
1462
            swapped12 = true;
1463 1464
            if( oclop == OCL_OP_SUB )
                oclop = OCL_OP_RSUB;
I
Ilya Lavrenov 已提交
1465 1466
            if ( oclop == OCL_OP_DIV_SCALE )
                oclop = OCL_OP_RDIV_SCALE;
1467
        }
1468
        else if( !checkScalar(*psrc2, type1, kind2, kind1) )
1469
            CV_Error( CV_StsUnmatchedSizes,
1470 1471
                     "The operation is neither 'array op array' "
                     "(where arrays have the same size and the same number of channels), "
1472 1473
                     "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
1474
        CV_Assert(type2 == CV_64F && (sz2.height == 1 || sz2.height == 4));
A
Andrey Kamaev 已提交
1475

1476 1477
        if (!muldiv)
        {
1478 1479 1480
            Mat sc = psrc2->getMat();
            depth2 = actualScalarDepth(sc.ptr<double>(), cn);
            if( depth2 == CV_64F && (depth1 < CV_32S || depth1 == CV_32F) )
1481 1482
                depth2 = CV_32F;
        }
A
Andrey Kamaev 已提交
1483
        else
1484
            depth2 = CV_64F;
1485
    }
1486

1487 1488 1489 1490 1491 1492
    if( dtype < 0 )
    {
        if( _dst.fixedType() )
            dtype = _dst.type();
        else
        {
1493
            if( !haveScalar && type1 != type2 )
1494 1495 1496
                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");
1497
            dtype = type1;
1498 1499 1500
        }
    }
    dtype = CV_MAT_DEPTH(dtype);
1501

1502 1503 1504 1505 1506 1507 1508
    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);
1509

1510 1511 1512 1513 1514 1515 1516 1517 1518 1519 1520
        // 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);
    }
1521

1522 1523
    dtype = CV_MAKETYPE(dtype, cn);
    wtype = CV_MAKETYPE(wtype, cn);
1524

1525 1526
    if( haveMask )
    {
1527 1528 1529
        int mtype = _mask.type();
        CV_Assert( (mtype == CV_8UC1 || mtype == CV_8SC1) && _mask.sameSize(*psrc1) );
        reallocate = !_dst.sameSize(*psrc1) || _dst.type() != dtype;
1530
    }
1531

1532 1533 1534
    _dst.createSameSize(*psrc1, dtype);
    if( reallocate )
        _dst.setTo(0.);
1535

I
Ilya Lavrenov 已提交
1536 1537 1538
    CV_OCL_RUN(use_opencl,
               ocl_arithm_op(*psrc1, *psrc2, _dst, _mask, wtype,
               usrdata, oclop, haveScalar))
1539

1540 1541 1542 1543 1544 1545 1546 1547 1548
    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();
1549

1550 1551 1552 1553 1554 1555
    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);
1556
    BinaryFunc func = tab[CV_MAT_DEPTH(wtype)];
1557

1558 1559 1560 1561
    if( !haveScalar )
    {
        const Mat* arrays[] = { &src1, &src2, &dst, &mask, 0 };
        uchar* ptrs[4];
1562

1563 1564
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = total;
1565

1566 1567 1568 1569 1570 1571 1572 1573 1574 1575 1576 1577 1578 1579
        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;
1580

1581
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1582
        {
1583
            for( size_t j = 0; j < total; j += blocksize )
1584
            {
1585
                int bsz = (int)MIN(total - j, blocksize);
1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600
                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;
                }
1601

1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616 1617 1618 1619 1620 1621
                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;
1622 1623
            }
        }
1624 1625 1626 1627 1628
    }
    else
    {
        const Mat* arrays[] = { &src1, &dst, &mask, 0 };
        uchar* ptrs[3];
1629

1630 1631
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
1632

1633 1634 1635 1636 1637 1638 1639 1640 1641 1642
        _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;
1643

1644
        convertAndUnrollScalar( src2, wtype, buf2, blocksize);
1645

1646
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1647
        {
1648 1649
            for( size_t j = 0; j < total; j += blocksize )
            {
1650
                int bsz = (int)MIN(total - j, blocksize);
1651 1652 1653 1654
                Size bszn(bsz*cn, 1);
                const uchar *sptr1 = ptrs[0];
                const uchar* sptr2 = buf2;
                uchar* dptr = ptrs[1];
1655

1656 1657 1658 1659 1660
                if( cvtsrc1 )
                {
                    cvtsrc1( sptr1, 0, 0, 0, buf1, 0, bszn, 0 );
                    sptr1 = buf1;
                }
1661

1662 1663
                if( swapped12 )
                    std::swap(sptr1, sptr2);
1664

1665 1666 1667 1668 1669 1670 1671 1672 1673 1674 1675 1676 1677 1678 1679 1680 1681 1682 1683 1684 1685
                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;
            }
1686 1687 1688
        }
    }
}
1689

1690
static BinaryFunc* getAddTab()
1691
{
1692 1693 1694 1695 1696 1697 1698 1699
    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
    };
1700

1701 1702 1703 1704
    return addTab;
}

static BinaryFunc* getSubTab()
1705
{
1706 1707 1708 1709 1710 1711 1712 1713 1714 1715 1716
    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;
}
1717

1718
static BinaryFunc* getAbsDiffTab()
1719
{
1720 1721 1722 1723 1724 1725 1726 1727 1728 1729 1730
    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;
}
1731 1732

}
1733

1734 1735
void cv::add( InputArray src1, InputArray src2, OutputArray dst,
          InputArray mask, int dtype )
1736
{
1737
    arithm_op(src1, src2, dst, mask, dtype, getAddTab(), false, 0, OCL_OP_ADD );
1738 1739
}

1740 1741
void cv::subtract( InputArray src1, InputArray src2, OutputArray dst,
               InputArray mask, int dtype )
1742
{
A
Andrey Kamaev 已提交
1743
#ifdef HAVE_TEGRA_OPTIMIZATION
1744
    if (mask.empty() && src1.depth() == CV_8U && src2.depth() == CV_8U)
1745
    {
1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769
        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;
            }
        }
1770
    }
A
Andrey Kamaev 已提交
1771
#endif
1772
    arithm_op(src1, src2, dst, mask, dtype, getSubTab(), false, 0, OCL_OP_SUB );
1773 1774
}

1775
void cv::absdiff( InputArray src1, InputArray src2, OutputArray dst )
1776
{
1777
    arithm_op(src1, src2, dst, noArray(), -1, getAbsDiffTab(), false, 0, OCL_OP_ABSDIFF);
1778
}
1779 1780 1781 1782 1783

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

1784 1785 1786
namespace cv
{

1787
template<typename T, typename WT> static void
1788 1789
mul_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, WT scale )
1790
{
1791 1792 1793
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1794

1795
    if( scale == (WT)1. )
1796
    {
1797
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1798
        {
V
Victoria Zhislina 已提交
1799
            int i=0;
1800
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1801
            for(; i <= size.width - 4; i += 4 )
1802
            {
1803 1804 1805 1806 1807 1808
                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;
1809 1810 1811

                t0 = saturate_cast<T>(src1[i+2] * src2[i+2]);
                t1 = saturate_cast<T>(src1[i+3] * src2[i+3]);
1812 1813
                dst[i+2] = t0;
                dst[i+3] = t1;
1814
            }
V
Victoria Zhislina 已提交
1815
            #endif
1816 1817 1818 1819 1820 1821
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(src1[i] * src2[i]);
        }
    }
    else
    {
1822
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1823
        {
V
Victoria Zhislina 已提交
1824
            int i = 0;
1825
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1826
            for(; i <= size.width - 4; i += 4 )
1827 1828 1829 1830 1831 1832 1833 1834 1835
            {
                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
1836
            #endif
1837 1838 1839 1840 1841 1842 1843
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(scale*(WT)src1[i]*src2[i]);
        }
    }
}

template<typename T> static void
1844 1845
div_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, double scale )
1846
{
1847 1848 1849
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1850

1851
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1852 1853
    {
        int i = 0;
1854
        #if CV_ENABLE_UNROLLED
1855 1856 1857 1858 1859 1860 1861 1862 1863
        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;
1864

1865 1866 1867 1868
                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));
1869

1870 1871 1872 1873 1874 1875 1876 1877 1878
                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;
1879

1880 1881 1882 1883
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1884
        #endif
1885 1886 1887 1888 1889 1890
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(src1[i]*scale/src2[i]) : 0;
    }
}

template<typename T> static void
1891 1892
recip_( const T*, size_t, const T* src2, size_t step2,
        T* dst, size_t step, Size size, double scale )
1893
{
1894 1895
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1896

1897
    for( ; size.height--; src2 += step2, dst += step )
1898 1899
    {
        int i = 0;
1900
        #if CV_ENABLE_UNROLLED
1901 1902 1903 1904 1905 1906 1907 1908 1909
        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;
1910

1911 1912 1913 1914
                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);
1915

1916 1917 1918 1919 1920 1921 1922 1923 1924
                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;
1925

1926 1927 1928 1929
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1930
        #endif
1931 1932 1933 1934
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(scale/src2[i]) : 0;
    }
}
1935 1936


1937 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
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);
}
1966

1967 1968 1969 1970 1971
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);
}
1972

1973 1974 1975 1976 1977
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);
}
1978

1979 1980 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
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);
}
2047

2048 2049 2050 2051 2052 2053 2054 2055 2056 2057 2058 2059 2060 2061 2062 2063 2064
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);
}
2065 2066


2067
static BinaryFunc* getMulTab()
2068
{
2069 2070 2071 2072 2073 2074 2075 2076 2077
    static BinaryFunc mulTab[] =
    {
        (BinaryFunc)mul8u, (BinaryFunc)mul8s, (BinaryFunc)mul16u,
        (BinaryFunc)mul16s, (BinaryFunc)mul32s, (BinaryFunc)mul32f,
        (BinaryFunc)mul64f, 0
    };

    return mulTab;
}
2078

2079
static BinaryFunc* getDivTab()
2080
{
2081 2082 2083 2084 2085 2086
    static BinaryFunc divTab[] =
    {
        (BinaryFunc)div8u, (BinaryFunc)div8s, (BinaryFunc)div16u,
        (BinaryFunc)div16s, (BinaryFunc)div32s, (BinaryFunc)div32f,
        (BinaryFunc)div64f, 0
    };
2087

2088 2089 2090 2091
    return divTab;
}

static BinaryFunc* getRecipTab()
2092
{
2093 2094 2095 2096 2097 2098
    static BinaryFunc recipTab[] =
    {
        (BinaryFunc)recip8u, (BinaryFunc)recip8s, (BinaryFunc)recip16u,
        (BinaryFunc)recip16s, (BinaryFunc)recip32s, (BinaryFunc)recip32f,
        (BinaryFunc)recip64f, 0
    };
2099

2100 2101
    return recipTab;
}
2102

2103
}
2104

2105
void cv::multiply(InputArray src1, InputArray src2,
2106
                  OutputArray dst, double scale, int dtype)
2107
{
2108
    arithm_op(src1, src2, dst, noArray(), dtype, getMulTab(),
I
Ilya Lavrenov 已提交
2109
              true, &scale, std::abs(scale - 1.0) < DBL_EPSILON ? OCL_OP_MUL : OCL_OP_MUL_SCALE);
2110
}
2111

2112
void cv::divide(InputArray src1, InputArray src2,
2113 2114
                OutputArray dst, double scale, int dtype)
{
2115
    arithm_op(src1, src2, dst, noArray(), dtype, getDivTab(), true, &scale, OCL_OP_DIV_SCALE);
2116 2117
}

2118
void cv::divide(double scale, InputArray src2,
2119 2120
                OutputArray dst, int dtype)
{
2121
    arithm_op(src2, src2, dst, noArray(), dtype, getRecipTab(), true, &scale, OCL_OP_RECIP_SCALE);
2122 2123
}

2124 2125 2126 2127
/****************************************************************************************\
*                                      addWeighted                                       *
\****************************************************************************************/

2128 2129 2130
namespace cv
{

2131
template<typename T, typename WT> static void
2132 2133 2134 2135 2136 2137 2138 2139 2140 2141
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 )
2142
    {
2143
        int x = 0;
2144
        #if CV_ENABLE_UNROLLED
2145
        for( ; x <= size.width - 4; x += 4 )
2146
        {
2147 2148 2149
            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;
2150

2151 2152 2153
            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;
2154
        }
V
Victoria Zhislina 已提交
2155
        #endif
2156 2157
        for( ; x < size.width; x++ )
            dst[x] = saturate_cast<T>(src1[x]*alpha + src2[x]*beta + gamma);
2158 2159 2160 2161 2162
    }
}


static void
2163 2164 2165 2166 2167 2168 2169
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];
2170

2171
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2172
    {
2173
        int x = 0;
2174

2175 2176
#if CV_SSE2
        if( USE_SSE2 )
2177
        {
2178 2179
            __m128 a4 = _mm_set1_ps(alpha), b4 = _mm_set1_ps(beta), g4 = _mm_set1_ps(gamma);
            __m128i z = _mm_setzero_si128();
2180

2181
            for( ; x <= size.width - 8; x += 8 )
2182
            {
2183 2184
                __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);
2185

2186 2187 2188 2189
                __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));
2190

2191 2192 2193
                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);
2194

2195 2196
                u = _mm_packs_epi32(_mm_cvtps_epi32(u0), _mm_cvtps_epi32(u1));
                u = _mm_packus_epi16(u, u);
2197

2198
                _mm_storel_epi64((__m128i*)(dst + x), u);
2199 2200
            }
        }
2201
#endif
2202
        #if CV_ENABLE_UNROLLED
2203
        for( ; x <= size.width - 4; x += 4 )
2204
        {
2205 2206 2207
            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;
2208

2209 2210
            dst[x] = saturate_cast<uchar>(t0);
            dst[x+1] = saturate_cast<uchar>(t1);
2211

2212 2213
            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;
2214

2215 2216 2217
            dst[x+2] = saturate_cast<uchar>(t0);
            dst[x+3] = saturate_cast<uchar>(t1);
        }
V
Victoria Zhislina 已提交
2218
        #endif
2219

2220 2221 2222 2223
        for( ; x < size.width; x++ )
        {
            float t0 = CV_8TO32F(src1[x])*alpha + CV_8TO32F(src2[x])*beta + gamma;
            dst[x] = saturate_cast<uchar>(t0);
2224 2225 2226 2227
        }
    }
}

2228 2229
static void addWeighted8s( const schar* src1, size_t step1, const schar* src2, size_t step2,
                           schar* dst, size_t step, Size sz, void* scalars )
2230
{
2231
    addWeighted_<schar, float>(src1, step1, src2, step2, dst, step, sz, scalars);
2232 2233
}

2234 2235
static void addWeighted16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                            ushort* dst, size_t step, Size sz, void* scalars )
2236
{
2237 2238
    addWeighted_<ushort, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2239

2240 2241
static void addWeighted16s( const short* src1, size_t step1, const short* src2, size_t step2,
                            short* dst, size_t step, Size sz, void* scalars )
2242
{
2243 2244
    addWeighted_<short, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2245

2246 2247
static void addWeighted32s( const int* src1, size_t step1, const int* src2, size_t step2,
                            int* dst, size_t step, Size sz, void* scalars )
2248
{
2249
    addWeighted_<int, double>(src1, step1, src2, step2, dst, step, sz, scalars);
2250 2251
}

2252 2253
static void addWeighted32f( const float* src1, size_t step1, const float* src2, size_t step2,
                            float* dst, size_t step, Size sz, void* scalars )
2254
{
2255 2256
    addWeighted_<float, double>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2257

2258 2259 2260 2261 2262
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
2263

2264
static BinaryFunc* getAddWeightedTab()
2265
{
2266 2267 2268 2269 2270 2271 2272 2273 2274
    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;
}
2275

2276
}
2277

2278
void cv::addWeighted( InputArray src1, double alpha, InputArray src2,
2279 2280 2281
                      double beta, double gamma, OutputArray dst, int dtype )
{
    double scalars[] = {alpha, beta, gamma};
2282
    arithm_op(src1, src2, dst, noArray(), dtype, getAddWeightedTab(), true, scalars, OCL_OP_ADDW);
2283 2284
}

2285

2286
/****************************************************************************************\
2287
*                                          compare                                       *
2288 2289
\****************************************************************************************/

2290
namespace cv
2291 2292
{

2293 2294 2295
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)
2296
{
2297 2298 2299
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    if( code == CMP_GE || code == CMP_LT )
2300
    {
2301 2302 2303
        std::swap(src1, src2);
        std::swap(step1, step2);
        code = code == CMP_GE ? CMP_LE : CMP_GT;
2304
    }
2305

2306
    if( code == CMP_GT || code == CMP_LE )
2307
    {
2308 2309 2310 2311
        int m = code == CMP_GT ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2312
            #if CV_ENABLE_UNROLLED
2313 2314 2315 2316 2317 2318 2319 2320 2321 2322
            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
2323
            #endif
2324 2325
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2326
               }
2327
    }
2328
    else if( code == CMP_EQ || code == CMP_NE )
2329
    {
2330 2331 2332 2333
        int m = code == CMP_EQ ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2334
            #if CV_ENABLE_UNROLLED
2335 2336 2337 2338 2339 2340 2341 2342 2343 2344
            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
2345
            #endif
2346 2347 2348
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
2349
    }
2350
}
2351

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2352 2353 2354 2355 2356 2357 2358 2359 2360 2361 2362
#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
2363

2364 2365
static void cmp8u(const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2366
{
K
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2367 2368 2369 2370 2371 2372 2373 2374 2375
#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
2376
  //vz optimized  cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2377
    int code = *(int*)_cmpop;
2378 2379 2380 2381 2382 2383 2384 2385 2386 2387 2388 2389 2390 2391 2392
    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;
2393 2394
            #if CV_SSE2
            if( USE_SSE2 ){
2395 2396
                __m128i m128 = code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
                __m128i c128 = _mm_set1_epi8 (-128);
2397 2398 2399 2400 2401 2402 2403 2404 2405 2406 2407 2408 2409
                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);

                }
            }
2410 2411
           #endif

2412
            for( ; x < size.width; x++ ){
2413
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2414
            }
2415 2416 2417 2418 2419
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2420
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2421 2422
        {
            int x = 0;
2423 2424
            #if CV_SSE2
            if( USE_SSE2 ){
2425
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
2426 2427 2428 2429 2430 2431 2432 2433
                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);
                }
            }
2434 2435 2436 2437 2438
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2439 2440
}

2441 2442
static void cmp8s(const schar* src1, size_t step1, const schar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2443
{
2444
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2445 2446
}

2447 2448
static void cmp16u(const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2449
{
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2450 2451 2452 2453 2454 2455 2456 2457 2458
#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
2459
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2460 2461
}

2462 2463
static void cmp16s(const short* src1, size_t step1, const short* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2464
{
K
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2465 2466 2467 2468 2469 2470 2471 2472 2473
#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
2474 2475
   //vz optimized cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);

2476
    int code = *(int*)_cmpop;
2477 2478 2479 2480 2481 2482 2483 2484 2485 2486 2487 2488 2489 2490 2491
    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;
2492 2493
            #if CV_SSE2
            if( USE_SSE2){//
2494
                __m128i m128 =  code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2495 2496 2497 2498 2499 2500 2501 2502 2503 2504 2505 2506 2507 2508 2509 2510 2511 2512 2513 2514 2515 2516
                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;
                }
            }
2517 2518
           #endif

2519
            for( ; x < size.width; x++ ){
2520
                 dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2521
            }
2522 2523 2524 2525 2526
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2527
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2528 2529
        {
            int x = 0;
2530 2531
            #if CV_SSE2
            if( USE_SSE2 ){
2532
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2533 2534 2535 2536 2537 2538 2539 2540 2541 2542 2543 2544 2545 2546 2547 2548 2549 2550 2551 2552 2553 2554
                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;
                }
            }
2555 2556 2557 2558 2559
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2560 2561
}

2562 2563 2564 2565 2566
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);
}
2567

2568 2569
static void cmp32f(const float* src1, size_t step1, const float* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2570
{
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2571 2572 2573 2574 2575 2576 2577 2578 2579
#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
2580 2581
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
}
2582

2583 2584
static void cmp64f(const double* src1, size_t step1, const double* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2585
{
2586
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2587 2588
}

2589
static BinaryFunc getCmpFunc(int depth)
2590
{
2591 2592 2593 2594 2595 2596 2597 2598
    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
    };
2599

2600 2601
    return cmpTab[depth];
}
2602

2603
static double getMinVal(int depth)
2604
{
2605 2606 2607
    static const double tab[] = {0, -128, 0, -32768, INT_MIN, -FLT_MAX, -DBL_MAX, 0};
    return tab[depth];
}
2608

2609
static double getMaxVal(int depth)
2610
{
2611 2612 2613
    static const double tab[] = {255, 127, 65535, 32767, INT_MAX, FLT_MAX, DBL_MAX, 0};
    return tab[depth];
}
2614

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2615 2616
#ifdef HAVE_OPENCL

A
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2617
static bool ocl_compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op, bool haveScalar)
I
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2618
{
A
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2619 2620
    const ocl::Device& dev = ocl::Device::getDefault();
    bool doubleSupport = dev.doubleFPConfig() > 0;
I
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2621 2622
    int type1 = _src1.type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1),
            type2 = _src2.type(), depth2 = CV_MAT_DEPTH(type2);
A
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2623 2624 2625

    if (!haveScalar)
    {
I
Ilya Lavrenov 已提交
2626
        if ( (!doubleSupport && depth1 == CV_64F) ||
A
Alexander Alekhin 已提交
2627 2628 2629
            !_src1.sameSize(_src2) || type1 != type2)
            return false;
    }
I
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2630

A
Alexander Alekhin 已提交
2631
    int kercn = haveScalar ? cn : ocl::predictOptimalVectorWidth(_src1, _src2, _dst);
A
Alexander Alekhin 已提交
2632
    // Workaround for bug with "?:" operator in AMD OpenCL compiler
I
Ilya Lavrenov 已提交
2633
    if (depth1 >= CV_16U)
A
Alexander Alekhin 已提交
2634 2635
        kercn = 1;

A
Alexander Alekhin 已提交
2636
    int scalarcn = kercn == 3 ? 4 : kercn;
I
Ilya Lavrenov 已提交
2637
    const char * const operationMap[] = { "==", ">", ">=", "<", "<=", "!=" };
I
Ilya Lavrenov 已提交
2638 2639
    char cvt[40];

I
Ilya Lavrenov 已提交
2640 2641 2642 2643 2644 2645 2646 2647 2648 2649 2650 2651 2652
    String opts = format("-D %s -D srcT1=%s -D dstT=%s -D workT=srcT1 -D cn=%d"
                         " -D convertToDT=%s -D OP_CMP -D CMP_OPERATOR=%s -D srcT1_C1=%s"
                         " -D srcT2_C1=%s -D dstT_C1=%s -D workST=%s%s",
                         haveScalar ? "UNARY_OP" : "BINARY_OP",
                         ocl::typeToStr(CV_MAKE_TYPE(depth1, kercn)),
                         ocl::typeToStr(CV_8UC(kercn)), kercn,
                         ocl::convertTypeStr(depth1, CV_8U, kercn, cvt),
                         operationMap[op], ocl::typeToStr(depth1),
                         ocl::typeToStr(depth1), ocl::typeToStr(CV_8U),
                         ocl::typeToStr(CV_MAKE_TYPE(depth1, scalarcn)),
                         doubleSupport ? " -D DOUBLE_SUPPORT" : "");

    ocl::Kernel k("KF", ocl::core::arithm_oclsrc, opts);
I
Ilya Lavrenov 已提交
2653 2654 2655
    if (k.empty())
        return false;

A
Alexander Alekhin 已提交
2656
    UMat src1 = _src1.getUMat();
I
Ilya Lavrenov 已提交
2657 2658 2659
    Size size = src1.size();
    _dst.create(size, CV_8UC(cn));
    UMat dst = _dst.getUMat();
I
Ilya Lavrenov 已提交
2660

A
Alexander Alekhin 已提交
2661 2662
    if (haveScalar)
    {
I
Ilya Lavrenov 已提交
2663 2664 2665 2666 2667 2668 2669 2670 2671 2672 2673 2674
        size_t esz = CV_ELEM_SIZE1(type1) * scalarcn;
        double buf[4] = { 0, 0, 0, 0 };
        Mat src2 = _src2.getMat();

        if( depth1 > CV_32S )
            convertAndUnrollScalar( src2, depth1, (uchar *)buf, kercn );
        else
        {
            double fval = 0;
            getConvertFunc(depth2, CV_64F)(src2.data, 0, 0, 0, (uchar *)&fval, 0, Size(1, 1), 0);
            if( fval < getMinVal(depth1) )
                return dst.setTo(Scalar::all(op == CMP_GT || op == CMP_GE || op == CMP_NE ? 255 : 0)), true;
A
Alexander Alekhin 已提交
2675

I
Ilya Lavrenov 已提交
2676 2677 2678 2679 2680 2681 2682 2683 2684 2685 2686 2687 2688 2689 2690
            if( fval > getMaxVal(depth1) )
                return dst.setTo(Scalar::all(op == CMP_LT || op == CMP_LE || op == CMP_NE ? 255 : 0)), true;

            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
                    return dst.setTo(Scalar::all(op == CMP_NE ? 255 : 0)), true;
            }
            convertAndUnrollScalar(Mat(1, 1, CV_32S, &ival), depth1, (uchar *)buf, kercn);
        }
A
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2691 2692 2693 2694

        ocl::KernelArg scalararg = ocl::KernelArg(0, 0, 0, 0, buf, esz);

        k.args(ocl::KernelArg::ReadOnlyNoSize(src1, cn, kercn),
I
Ilya Lavrenov 已提交
2695
               ocl::KernelArg::WriteOnly(dst, cn, kercn), scalararg);
A
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2696 2697 2698 2699 2700 2701 2702 2703 2704
    }
    else
    {
        UMat src2 = _src2.getUMat();

        k.args(ocl::KernelArg::ReadOnlyNoSize(src1),
               ocl::KernelArg::ReadOnlyNoSize(src2),
               ocl::KernelArg::WriteOnly(dst, cn, kercn));
    }
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Ilya Lavrenov 已提交
2705

I
Ilya Lavrenov 已提交
2706
    size_t globalsize[2] = { dst.cols * cn / kercn, dst.rows };
I
Ilya Lavrenov 已提交
2707 2708 2709
    return k.run(2, globalsize, NULL, false);
}

I
Ilya Lavrenov 已提交
2710 2711
#endif

2712 2713
}

2714
void cv::compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op)
2715 2716 2717
{
    CV_Assert( op == CMP_LT || op == CMP_LE || op == CMP_EQ ||
               op == CMP_NE || op == CMP_GE || op == CMP_GT );
2718

A
Alexander Alekhin 已提交
2719 2720 2721 2722 2723 2724 2725 2726 2727 2728 2729 2730 2731 2732 2733 2734 2735 2736 2737 2738 2739
    bool haveScalar = false;

    if ((_src1.isMatx() + _src2.isMatx()) == 1
            || !_src1.sameSize(_src2)
            || _src1.type() != _src2.type())
    {
        if (checkScalar(_src1, _src2.type(), _src1.kind(), _src2.kind()))
        {
            op = op == CMP_LT ? CMP_GT : op == CMP_LE ? CMP_GE :
                op == CMP_GE ? CMP_LE : op == CMP_GT ? CMP_LT : op;
            // src1 is a scalar; swap it with src2
            compare(_src2, _src1, _dst, op);
            return;
        }
        else if( !checkScalar(_src2, _src1.type(), _src2.kind(), _src1.kind()) )
            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;
    }

I
Ilya Lavrenov 已提交
2740
    CV_OCL_RUN(_src1.dims() <= 2 && _src2.dims() <= 2 && _dst.isUMat(),
A
Alexander Alekhin 已提交
2741
               ocl_compare(_src1, _src2, _dst, op, haveScalar))
I
Ilya Lavrenov 已提交
2742

2743 2744
    int kind1 = _src1.kind(), kind2 = _src2.kind();
    Mat src1 = _src1.getMat(), src2 = _src2.getMat();
2745

2746
    if( kind1 == kind2 && src1.dims <= 2 && src2.dims <= 2 && src1.size() == src2.size() && src1.type() == src2.type() )
2747
    {
2748 2749
        int cn = src1.channels();
        _dst.create(src1.size(), CV_8UC(cn));
2750 2751
        Mat dst = _dst.getMat();
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
2752
        getCmpFunc(src1.depth())(src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, &op);
2753 2754
        return;
    }
2755

2756
    int cn = src1.channels(), depth1 = src1.depth(), depth2 = src2.depth();
2757

2758 2759 2760
    _dst.create(src1.dims, src1.size, CV_8UC(cn));
    src1 = src1.reshape(1); src2 = src2.reshape(1);
    Mat dst = _dst.getMat().reshape(1);
2761

2762 2763
    size_t esz = src1.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
2764
    BinaryFunc func = getCmpFunc(depth1);
2765

2766
    if( !haveScalar )
2767
    {
2768 2769
        const Mat* arrays[] = { &src1, &src2, &dst, 0 };
        uchar* ptrs[3];
2770

2771 2772
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size;
2773

2774 2775
        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 );
2776
    }
2777
    else
2778
    {
2779 2780
        const Mat* arrays[] = { &src1, &dst, 0 };
        uchar* ptrs[2];
2781

2782 2783
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
2784

2785 2786 2787 2788 2789 2790
        AutoBuffer<uchar> _buf(blocksize*esz);
        uchar *buf = _buf;

        if( depth1 > CV_32S )
            convertAndUnrollScalar( src2, depth1, buf, blocksize );
        else
2791
        {
2792 2793 2794 2795 2796 2797 2798
            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;
            }
2799

2800 2801 2802 2803 2804
            if( fval > getMaxVal(depth1) )
            {
                dst = Scalar::all(op == CMP_LT || op == CMP_LE || op == CMP_NE ? 255 : 0);
                return;
            }
2805

2806 2807 2808 2809 2810 2811 2812 2813 2814 2815 2816 2817 2818 2819 2820
            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);
        }
2821

2822
        for( size_t i = 0; i < it.nplanes; i++, ++it )
2823
        {
2824 2825
            for( size_t j = 0; j < total; j += blocksize )
            {
2826
                int bsz = (int)MIN(total - j, blocksize);
2827 2828 2829 2830 2831
                func( ptrs[0], 0, buf, 0, ptrs[1], 0, Size(bsz, 1), &op);
                ptrs[0] += bsz*esz;
                ptrs[1] += bsz;
            }
        }
2832
    }
2833
}
2834

2835 2836 2837
/****************************************************************************************\
*                                        inRange                                         *
\****************************************************************************************/
2838

2839 2840
namespace cv
{
2841

2842 2843 2844 2845 2846 2847 2848 2849
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]);
2850

2851
    for( ; size.height--; src1 += step1, src2 += step2, src3 += step3, dst += step )
V
Vadim Pisarevsky 已提交
2852
    {
2853
        int x = 0;
2854
        #if CV_ENABLE_UNROLLED
2855
        for( ; x <= size.width - 4; x += 4 )
V
Vadim Pisarevsky 已提交
2856
        {
2857 2858 2859 2860 2861 2862 2863
            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
2864
        }
V
Victoria Zhislina 已提交
2865
        #endif
2866 2867
        for( ; x < size.width; x++ )
            dst[x] = (uchar)-(src2[x] <= src1[x] && src1[x] <= src3[x]);
V
Vadim Pisarevsky 已提交
2868
    }
2869 2870
}

2871

2872 2873
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)
2874
{
2875 2876
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2877

2878 2879
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)
2880
{
2881 2882
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2883

2884 2885
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)
2886
{
2887 2888
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2889

2890 2891 2892 2893
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);
2894 2895
}

2896 2897
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)
2898
{
2899 2900
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2901

2902 2903 2904 2905
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);
2906 2907
}

2908 2909
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)
2910
{
2911
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
2912
}
2913

2914 2915 2916 2917 2918 2919 2920 2921 2922 2923 2924 2925 2926 2927 2928 2929
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];
2930

2931 2932 2933 2934
    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
2935
    }
2936
}
2937

2938 2939
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 );
2940

2941
static InRangeFunc getInRangeFunc(int depth)
2942
{
2943 2944 2945 2946 2947 2948 2949 2950 2951
    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];
}
2952

I
Ilya Lavrenov 已提交
2953 2954
#ifdef HAVE_OPENCL

I
Ilya Lavrenov 已提交
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 3006 3007 3008 3009 3010 3011 3012 3013 3014 3015 3016 3017 3018 3019 3020 3021 3022 3023 3024 3025 3026 3027 3028 3029 3030 3031 3032 3033 3034 3035 3036 3037 3038 3039 3040 3041 3042 3043 3044 3045 3046 3047 3048 3049 3050 3051 3052 3053 3054 3055 3056 3057 3058 3059 3060
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);
}

I
Ilya Lavrenov 已提交
3061 3062
#endif

3063 3064
}

3065 3066
void cv::inRange(InputArray _src, InputArray _lowerb,
                 InputArray _upperb, OutputArray _dst)
3067
{
I
Ilya Lavrenov 已提交
3068 3069 3070
    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
3071

3072 3073
    int skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
    Mat src = _src.getMat(), lb = _lowerb.getMat(), ub = _upperb.getMat();
3074

3075
    bool lbScalar = false, ubScalar = false;
3076

3077
    if( (lkind == _InputArray::MATX && skind != _InputArray::MATX) ||
3078 3079 3080 3081 3082 3083 3084
        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;
    }
3085

3086
    if( (ukind == _InputArray::MATX && skind != _InputArray::MATX) ||
3087 3088 3089 3090 3091 3092 3093
        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;
    }
3094

I
Ilya Lavrenov 已提交
3095
    CV_Assert(lbScalar == ubScalar);
3096

3097
    int cn = src.channels(), depth = src.depth();
3098

3099 3100
    size_t esz = src.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
3101

I
Ilya Lavrenov 已提交
3102
    _dst.create(src.dims, src.size, CV_8UC1);
3103
    Mat dst = _dst.getMat();
3104
    InRangeFunc func = getInRangeFunc(depth);
3105

3106 3107 3108
    const Mat* arrays_sc[] = { &src, &dst, 0 };
    const Mat* arrays_nosc[] = { &src, &dst, &lb, &ub, 0 };
    uchar* ptrs[4];
3109

3110 3111
    NAryMatIterator it(lbScalar && ubScalar ? arrays_sc : arrays_nosc, ptrs);
    size_t total = it.size, blocksize = std::min(total, blocksize0);
3112

3113 3114 3115
    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);
3116

3117 3118 3119 3120
    if( lbScalar && ubScalar )
    {
        lbuf = buf;
        ubuf = buf = alignPtr(buf + blocksize*esz, 16);
3121

3122 3123
        CV_Assert( lb.type() == ub.type() );
        int scdepth = lb.depth();
3124

3125 3126 3127 3128
        if( scdepth != depth && depth < CV_32S )
        {
            int* ilbuf = (int*)alignPtr(buf + blocksize*esz, 16);
            int* iubuf = ilbuf + cn;
3129

3130 3131 3132
            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);
3133
            int minval = cvRound(getMinVal(depth)), maxval = cvRound(getMaxVal(depth));
3134

3135 3136 3137 3138 3139 3140 3141 3142
            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);
        }
3143

3144 3145 3146
        convertAndUnrollScalar( lb, src.type(), lbuf, blocksize );
        convertAndUnrollScalar( ub, src.type(), ubuf, blocksize );
    }
3147

3148
    for( size_t i = 0; i < it.nplanes; i++, ++it )
V
Vadim Pisarevsky 已提交
3149
    {
3150 3151
        for( size_t j = 0; j < total; j += blocksize )
        {
3152
            int bsz = (int)MIN(total - j, blocksize);
3153 3154 3155 3156 3157 3158 3159 3160 3161 3162 3163 3164 3165 3166
            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));
3167
            if( cn > 1 )
3168 3169 3170 3171
                inRangeReduce(mbuf, ptrs[1], bsz, cn);
            ptrs[0] += delta;
            ptrs[1] += bsz;
        }
V
Vadim Pisarevsky 已提交
3172
    }
3173 3174 3175 3176 3177 3178 3179 3180 3181 3182
}

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

CV_IMPL void
cvNot( const CvArr* srcarr, CvArr* dstarr )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
3183
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3184 3185 3186 3187 3188 3189 3190 3191 3192
    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;
3193
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3194 3195 3196 3197 3198
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
    cv::bitwise_and( src1, src2, dst, mask );
}

3199

3200 3201 3202 3203 3204
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;
3205
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3206 3207 3208 3209 3210 3211 3212 3213 3214 3215 3216
    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;
3217
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3218 3219 3220 3221 3222 3223 3224 3225 3226 3227
    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;
3228
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3229 3230
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3231
    cv::bitwise_and( src, (const cv::Scalar&)s, dst, mask );
3232 3233 3234 3235 3236 3237 3238
}


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;
3239
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3240 3241
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3242
    cv::bitwise_or( src, (const cv::Scalar&)s, dst, mask );
3243 3244 3245 3246 3247 3248 3249
}


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;
3250
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3251 3252
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3253
    cv::bitwise_xor( src, (const cv::Scalar&)s, dst, mask );
3254 3255
}

3256

3257 3258 3259 3260
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;
3261
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3262 3263
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3264
    cv::add( src1, src2, dst, mask, dst.type() );
3265 3266
}

3267

3268 3269 3270 3271
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;
3272
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3273 3274
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3275
    cv::subtract( src1, src2, dst, mask, dst.type() );
3276 3277
}

3278

3279 3280 3281 3282
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;
3283
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3284 3285
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3286
    cv::add( src1, (const cv::Scalar&)value, dst, mask, dst.type() );
3287 3288
}

3289

3290 3291 3292 3293
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;
3294
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3295 3296
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3297
    cv::subtract( (const cv::Scalar&)value, src1, dst, mask, dst.type() );
3298 3299
}

3300

3301 3302 3303 3304 3305
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);
3306 3307
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::multiply( src1, src2, dst, scale, dst.type() );
3308 3309
}

3310

3311 3312 3313 3314 3315
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;
3316
    CV_Assert( src2.size == dst.size && src2.channels() == dst.channels() );
3317 3318

    if( srcarr1 )
3319
        cv::divide( cv::cvarrToMat(srcarr1), src2, dst, scale, dst.type() );
3320
    else
3321
        cv::divide( scale, src2, dst, dst.type() );
3322 3323 3324 3325 3326 3327 3328 3329 3330 3331
}


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);
3332 3333
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::addWeighted( src1, alpha, src2, beta, gamma, dst, dst.type() );
3334 3335 3336 3337 3338 3339 3340
}


CV_IMPL  void
cvAbsDiff( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3341
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3342 3343 3344 3345 3346 3347 3348 3349 3350

    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);
3351
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3352

3353
    cv::absdiff( src1, (const cv::Scalar&)scalar, dst );
3354 3355
}

3356

3357 3358 3359 3360 3361
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);
3362
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3363 3364 3365 3366

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

3367

3368 3369 3370 3371
CV_IMPL void
cvInRangeS( const void* srcarr1, CvScalar lowerb, CvScalar upperb, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3372
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3373

3374
    cv::inRange( src1, (const cv::Scalar&)lowerb, (const cv::Scalar&)upperb, dst );
3375 3376 3377 3378 3379 3380 3381
}


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);
3382
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3383 3384 3385 3386 3387 3388 3389 3390 3391

    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);
3392
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3393 3394 3395 3396 3397 3398 3399 3400 3401

    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);
3402
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3403 3404 3405 3406 3407 3408 3409 3410 3411

    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);
3412
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3413 3414 3415 3416

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

3417

3418 3419 3420 3421
CV_IMPL void
cvMinS( const void* srcarr1, double value, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3422
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3423 3424 3425 3426 3427 3428 3429 3430 3431

    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);
3432
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3433 3434 3435 3436 3437

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

/* End of file. */