arithm.cpp 114.6 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;                                                          \
        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;                                        \
        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

915 916 917 918 919 920 921 922 923 924 925

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,
       OCL_OP_AND=9, OCL_OP_OR=10, OCL_OP_XOR=11, OCL_OP_NOT=12, OCL_OP_MIN=13, OCL_OP_MAX=14 };

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

static bool ocl_binary_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                          InputArray _mask, bool bitwise, int oclop, bool haveScalar )
926
{
927 928 929 930 931
    bool haveMask = !_mask.empty();
    int srctype = _src1.type();
    int srcdepth = CV_MAT_DEPTH(srctype);
    int cn = CV_MAT_CN(srctype);

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Ilya Lavrenov 已提交
932
    if( oclop < 0 || ((haveMask || haveScalar) && (cn > 4 || cn == 3)) )
933 934 935 936 937 938 939 940 941 942 943 944 945
        return false;

    char opts[1024];
    int kercn = haveMask || haveScalar ? cn : 1;
    sprintf(opts, "-D %s%s -D %s -D dstT=%s",
            (haveMask ? "MASK_" : ""), (haveScalar ? "UNARY_OP" : "BINARY_OP"), oclop2str[oclop],
            bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, kercn)) :
            ocl::typeToStr(CV_MAKETYPE(srcdepth, kercn)));

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

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Ilya Lavrenov 已提交
946 947 948
    UMat src1 = _src1.getUMat(), src2;
    UMat dst = _dst.getUMat(), mask = _mask.getUMat();

949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001
    int cscale = cn/kercn;
    ocl::KernelArg src1arg = ocl::KernelArg::ReadOnlyNoSize(src1, cscale);
    ocl::KernelArg dstarg = haveMask ? ocl::KernelArg::ReadWrite(dst, cscale) :
                                       ocl::KernelArg::WriteOnly(dst, cscale);
    ocl::KernelArg maskarg = ocl::KernelArg::ReadOnlyNoSize(mask, 1);

    if( haveScalar )
    {
        size_t esz = CV_ELEM_SIZE(srctype);
        double buf[4] = {0,0,0,0};

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

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

        if( !haveMask )
            k.args(src1arg, dstarg, scalararg);
        else
            k.args(src1arg, maskarg, dstarg, scalararg);
    }
    else
    {
        src2 = _src2.getUMat();
        ocl::KernelArg src2arg = ocl::KernelArg::ReadOnlyNoSize(src2, cscale);

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

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


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();
    bool use_opencl = (kind1 == _InputArray::UMAT || kind2 == _InputArray::UMAT) &&
                        ocl::useOpenCL() && dims1 <= 2 && dims2 <= 2;
1002 1003
    bool haveMask = !_mask.empty(), haveScalar = false;
    BinaryFunc func;
1004

1005
    if( dims1 <= 2 && dims2 <= 2 && kind1 == kind2 && sz1 == sz2 && type1 == type2 && !haveMask )
1006
    {
1007 1008 1009
        _dst.create(sz1, type1);
        if( use_opencl && ocl_binary_op(*psrc1, *psrc2, _dst, _mask, bitwise, oclop, false) )
            return;
1010 1011 1012
        if( bitwise )
        {
            func = *tab;
1013
            cn = (int)CV_ELEM_SIZE(type1);
1014 1015
        }
        else
1016
            func = tab[depth1];
1017

1018
        Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat();
1019
        Size sz = getContinuousSize(src1, src2, dst);
1020
        size_t len = sz.width*(size_t)cn;
1021 1022 1023 1024 1025 1026
        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;
        }
1027
    }
1028

1029 1030 1031 1032
    if( oclop == OCL_OP_NOT )
        haveScalar = true;
    else if( (kind1 == _InputArray::MATX) + (kind2 == _InputArray::MATX) == 1 ||
        !psrc1->sameSize(*psrc2) || type1 != type2 )
1033
    {
1034 1035
        if( checkScalar(*psrc1, type2, kind1, kind2) )
        {
1036
            // src1 is a scalar; swap it with src2
1037 1038 1039 1040 1041 1042 1043
            swap(psrc1, psrc2);
            swap(type1, type2);
            swap(depth1, depth2);
            swap(cn, cn2);
            swap(sz1, sz2);
        }
        else if( !checkScalar(*psrc2, type1, kind2, kind1) )
1044 1045 1046 1047 1048
            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;
    }
1049 1050 1051 1052
    else
    {
        CV_Assert( psrc1->sameSize(*psrc2) && type1 == type2 );
    }
1053

1054
    size_t esz = CV_ELEM_SIZE(type1);
1055 1056
    size_t blocksize0 = (BLOCK_SIZE + esz-1)/esz;
    BinaryFunc copymask = 0;
1057
    bool reallocate = false;
1058

1059 1060
    if( haveMask )
    {
1061 1062
        int mtype = _mask.type();
        CV_Assert( (mtype == CV_8U || mtype == CV_8S) && _mask.sameSize(*psrc1));
1063
        copymask = getCopyMaskFunc(esz);
1064
        reallocate = !_dst.sameSize(*psrc1) || _dst.type() != type1;
1065
    }
1066

1067 1068
    AutoBuffer<uchar> _buf;
    uchar *scbuf = 0, *maskbuf = 0;
1069

1070
    _dst.createSameSize(*psrc1, type1);
1071
    // if this is mask operation and dst has been reallocated,
1072
    // we have to clear the destination
1073
    if( haveMask && reallocate )
1074 1075 1076 1077 1078 1079 1080
        _dst.setTo(0.);

    if( use_opencl && ocl_binary_op(*psrc1, *psrc2, _dst, _mask, bitwise, oclop, haveScalar ))
        return;

    Mat src1 = psrc1->getMat(), src2 = psrc2->getMat();
    Mat dst = _dst.getMat(), mask = _mask.getMat();
1081

1082 1083 1084
    if( bitwise )
    {
        func = *tab;
1085
        cn = (int)esz;
1086 1087 1088
    }
    else
    {
1089
        func = tab[depth1];
1090
    }
1091

1092
    if( !haveScalar )
1093
    {
1094 1095
        const Mat* arrays[] = { &src1, &src2, &dst, &mask, 0 };
        uchar* ptrs[4];
1096

1097 1098
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = total;
1099

1100 1101
        if( blocksize*cn > INT_MAX )
            blocksize = INT_MAX/cn;
1102

1103 1104 1105 1106 1107 1108
        if( haveMask )
        {
            blocksize = std::min(blocksize, blocksize0);
            _buf.allocate(blocksize*esz);
            maskbuf = _buf;
        }
1109

1110
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1111
        {
1112
            for( size_t j = 0; j < total; j += blocksize )
1113
            {
1114
                int bsz = (int)MIN(total - j, blocksize);
1115

1116
                func( ptrs[0], 0, ptrs[1], 0, haveMask ? maskbuf : ptrs[2], 0, Size(bsz*cn, 1), 0 );
1117
                if( haveMask )
1118
                {
1119 1120
                    copymask( maskbuf, 0, ptrs[3], 0, ptrs[2], 0, Size(bsz, 1), &esz );
                    ptrs[3] += bsz;
1121
                }
1122

1123 1124
                bsz *= (int)esz;
                ptrs[0] += bsz; ptrs[1] += bsz; ptrs[2] += bsz;
1125 1126
            }
        }
1127 1128 1129 1130 1131
    }
    else
    {
        const Mat* arrays[] = { &src1, &dst, &mask, 0 };
        uchar* ptrs[3];
1132

1133 1134
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
1135

1136 1137 1138
        _buf.allocate(blocksize*(haveMask ? 2 : 1)*esz + 32);
        scbuf = _buf;
        maskbuf = alignPtr(scbuf + blocksize*esz, 16);
1139

1140
        convertAndUnrollScalar( src2, src1.type(), scbuf, blocksize);
1141

1142
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1143
        {
1144
            for( size_t j = 0; j < total; j += blocksize )
1145
            {
1146
                int bsz = (int)MIN(total - j, blocksize);
1147

1148
                func( ptrs[0], 0, scbuf, 0, haveMask ? maskbuf : ptrs[1], 0, Size(bsz*cn, 1), 0 );
1149
                if( haveMask )
1150
                {
1151 1152
                    copymask( maskbuf, 0, ptrs[2], 0, ptrs[1], 0, Size(bsz, 1), &esz );
                    ptrs[2] += bsz;
1153
                }
1154

1155 1156
                bsz *= (int)esz;
                ptrs[0] += bsz; ptrs[1] += bsz;
1157 1158 1159 1160
            }
        }
    }
}
1161

1162
static BinaryFunc* getMaxTab()
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Vadim Pisarevsky 已提交
1163
{
1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174
    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;
}
1175

1176
static BinaryFunc* getMinTab()
1177
{
1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188
    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;
}
1189

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Vadim Pisarevsky 已提交
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}
1191

1192
void cv::bitwise_and(InputArray a, InputArray b, OutputArray c, InputArray mask)
1193
{
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Andrey Kamaev 已提交
1194
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(and8u);
1195
    binary_op(a, b, c, mask, &f, true, OCL_OP_AND);
1196 1197
}

1198
void cv::bitwise_or(InputArray a, InputArray b, OutputArray c, InputArray mask)
1199
{
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Andrey Kamaev 已提交
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    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(or8u);
1201
    binary_op(a, b, c, mask, &f, true, OCL_OP_OR);
1202 1203
}

1204
void cv::bitwise_xor(InputArray a, InputArray b, OutputArray c, InputArray mask)
1205
{
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Andrey Kamaev 已提交
1206
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(xor8u);
1207
    binary_op(a, b, c, mask, &f, true, OCL_OP_XOR);
1208 1209
}

1210
void cv::bitwise_not(InputArray a, OutputArray c, InputArray mask)
1211
{
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Andrey Kamaev 已提交
1212
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(not8u);
1213
    binary_op(a, a, c, mask, &f, true, OCL_OP_NOT);
1214 1215
}

1216
void cv::max( InputArray src1, InputArray src2, OutputArray dst )
1217
{
1218
    binary_op(src1, src2, dst, noArray(), getMaxTab(), false, OCL_OP_MAX );
1219 1220
}

1221
void cv::min( InputArray src1, InputArray src2, OutputArray dst )
1222
{
1223
    binary_op(src1, src2, dst, noArray(), getMinTab(), false, OCL_OP_MIN );
1224 1225
}

1226
void cv::max(const Mat& src1, const Mat& src2, Mat& dst)
1227
{
1228
    OutputArray _dst(dst);
1229
    binary_op(src1, src2, _dst, noArray(), getMaxTab(), false, OCL_OP_MAX );
1230 1231
}

1232 1233 1234
void cv::min(const Mat& src1, const Mat& src2, Mat& dst)
{
    OutputArray _dst(dst);
1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247
    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 );
1248
}
1249 1250


1251 1252 1253
/****************************************************************************************\
*                                      add/subtract                                      *
\****************************************************************************************/
1254

1255 1256
namespace cv
{
1257

1258 1259
static int actualScalarDepth(const double* data, int len)
{
1260 1261
    int i = 0, minval = INT_MAX, maxval = INT_MIN;
    for(; i < len; ++i)
1262
    {
1263 1264 1265 1266 1267
        int ival = cvRound(data[i]);
        if( ival != data[i] )
            break;
        minval = MIN(minval, ival);
        maxval = MAX(maxval, ival);
1268
    }
1269
    return i < len ? CV_64F :
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Andrey Kamaev 已提交
1270 1271 1272 1273
        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 :
1274
        CV_32S;
1275 1276
}

1277 1278 1279 1280 1281

static bool ocl_arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                          InputArray _mask, int wtype,
                          void* usrdata, int oclop,
                          bool haveScalar )
1282
{
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Ilya Lavrenov 已提交
1283
    bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
1284
    int type1 = _src1.type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
1285
    bool haveMask = !_mask.empty();
1286

I
Ilya Lavrenov 已提交
1287
    if( ((haveMask || haveScalar) && (cn > 4 || cn == 3)) )
1288 1289
        return false;

1290
    int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), wdepth = std::max(CV_32S, CV_MAT_DEPTH(wtype));
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Ilya Lavrenov 已提交
1291 1292 1293
    if (!doubleSupport)
        wdepth = std::min(wdepth, CV_32F);

1294
    wtype = CV_MAKETYPE(wdepth, cn);
1295
    int type2 = haveScalar ? wtype : _src2.type(), depth2 = CV_MAT_DEPTH(type2);
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Ilya Lavrenov 已提交
1296 1297
    if (!doubleSupport && (depth2 == CV_64F || depth1 == CV_64F))
        return false;
1298

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Ilya Lavrenov 已提交
1299
    int kercn = haveMask || haveScalar ? cn : 1;
1300

1301 1302 1303
    char cvtstr[3][32], opts[1024];
    sprintf(opts, "-D %s%s -D %s -D srcT1=%s -D srcT2=%s "
            "-D dstT=%s -D workT=%s -D convertToWT1=%s "
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Ilya Lavrenov 已提交
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            "-D convertToWT2=%s -D convertToDT=%s%s",
1305 1306 1307 1308 1309 1310 1311
            (haveMask ? "MASK_" : ""), (haveScalar ? "UNARY_OP" : "BINARY_OP"),
            oclop2str[oclop], ocl::typeToStr(CV_MAKETYPE(depth1, kercn)),
            ocl::typeToStr(CV_MAKETYPE(depth2, kercn)),
            ocl::typeToStr(CV_MAKETYPE(ddepth, kercn)),
            ocl::typeToStr(CV_MAKETYPE(wdepth, kercn)),
            ocl::convertTypeStr(depth1, wdepth, kercn, cvtstr[0]),
            ocl::convertTypeStr(depth2, wdepth, kercn, cvtstr[1]),
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Ilya Lavrenov 已提交
1312 1313
            ocl::convertTypeStr(wdepth, ddepth, kercn, cvtstr[2]),
            doubleSupport ? " -D DOUBLE_SUPPORT" : "");
1314 1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330

    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 ||
        oclop == OCL_OP_RECIP_SCALE ? 1 : oclop == OCL_OP_ADDW ? 3 : 0;
    if( n > 0 && wdepth == CV_32F )
    {
        for( i = 0; i < n; i++ )
            usrdata_f[i] = (float)usrdata_d[i];
        usrdata_p = (const uchar*)usrdata_f;
    }

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

I
Ilya Lavrenov 已提交
1331 1332 1333
    UMat src1 = _src1.getUMat(), src2;
    UMat dst = _dst.getUMat(), mask = _mask.getUMat();

1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357
    int cscale = cn/kercn;

    ocl::KernelArg src1arg = ocl::KernelArg::ReadOnlyNoSize(src1, cscale);
    ocl::KernelArg dstarg = haveMask ? ocl::KernelArg::ReadWrite(dst, cscale) :
                                       ocl::KernelArg::WriteOnly(dst, cscale);
    ocl::KernelArg maskarg = ocl::KernelArg::ReadOnlyNoSize(mask, 1);

    if( haveScalar )
    {
        size_t esz = CV_ELEM_SIZE(wtype);
        double buf[4]={0,0,0,0};
        Mat src2sc = _src2.getMat();

        if( !src2sc.empty() )
            convertAndUnrollScalar(src2sc, wtype, (uchar*)buf, 1);
        ocl::KernelArg scalararg = ocl::KernelArg(0, 0, 0, buf, esz);

        if( !haveMask )
            k.args(src1arg, dstarg, scalararg);
        else
            k.args(src1arg, maskarg, dstarg, scalararg);
    }
    else
    {
1358
        size_t usrdata_esz = CV_ELEM_SIZE(wdepth);
1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380
        src2 = _src2.getUMat();
        ocl::KernelArg src2arg = ocl::KernelArg::ReadOnlyNoSize(src2, cscale);

        if( !haveMask )
        {
            if(n == 0)
                k.args(src1arg, src2arg, dstarg);
            else if(n == 1)
                k.args(src1arg, src2arg, dstarg,
                       ocl::KernelArg(0, 0, 0, usrdata_p, usrdata_esz));
            else if(n == 3)
                k.args(src1arg, src2arg, dstarg,
                       ocl::KernelArg(0, 0, 0, usrdata_p, usrdata_esz),
                       ocl::KernelArg(0, 0, 0, usrdata_p + usrdata_esz, usrdata_esz),
                       ocl::KernelArg(0, 0, 0, usrdata_p + usrdata_esz*2, usrdata_esz));
            else
                CV_Error(Error::StsNotImplemented, "unsupported number of extra parameters");
        }
        else
            k.args(src1arg, src2arg, maskarg, dstarg);
    }

I
Ilya Lavrenov 已提交
1381
    size_t globalsize[] = { src1.cols * cscale, src1.rows };
1382
    return k.run(2, globalsize, NULL, false);
1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398
}


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();
1399
    bool use_opencl = _dst.kind() == _OutputArray::UMAT && ocl::useOpenCL() && dims1 <= 2 && dims2 <= 2;
1400 1401 1402 1403 1404 1405
    bool src1Scalar = checkScalar(*psrc1, type2, kind1, kind2);
    bool src2Scalar = checkScalar(*psrc2, type1, kind2, kind1);

    if( (kind1 == kind2 || cn == 1) && sz1 == sz2 && dims1 <= 2 && dims2 <= 2 && type1 == type2 &&
        !haveMask && ((!_dst.fixedType() && (dtype < 0 || CV_MAT_DEPTH(dtype) == depth1)) ||
                       (_dst.fixedType() && _dst.type() == type1)) &&
B
Bo Li 已提交
1406
        ((src1Scalar && src2Scalar) || (!src1Scalar && !src2Scalar)) )
V
Vadim Pisarevsky 已提交
1407
    {
1408 1409 1410 1411 1412 1413
        _dst.createSameSize(*psrc1, type1);
        if( use_opencl &&
            ocl_arithm_op(*psrc1, *psrc2, _dst, _mask,
                          (!usrdata ? type1 : std::max(depth1, CV_32F)),
                          usrdata, oclop, false))
            return;
1414

1415
        Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat();
1416
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
1417
        tab[depth1](src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, usrdata);
V
Vadim Pisarevsky 已提交
1418 1419
        return;
    }
1420

1421
    bool haveScalar = false, swapped12 = false;
1422 1423

    if( dims1 != dims2 || sz1 != sz2 || cn != cn2 ||
1424
        ((kind1 == _InputArray::MATX || kind2 == _InputArray::MATX) &&
1425
         (sz1 == Size(1,4) || sz2 == Size(1,4))) )
1426
    {
1427
        if( checkScalar(*psrc1, type2, kind1, kind2) )
1428 1429
        {
            // src1 is a scalar; swap it with src2
1430 1431 1432 1433 1434 1435
            swap(psrc1, psrc2);
            swap(sz1, sz2);
            swap(type1, type2);
            swap(depth1, depth2);
            swap(cn, cn2);
            swap(dims1, dims2);
1436
            swapped12 = true;
1437 1438
            if( oclop == OCL_OP_SUB )
                oclop = OCL_OP_RSUB;
1439
        }
1440
        else if( !checkScalar(*psrc2, type1, kind2, kind1) )
1441
            CV_Error( CV_StsUnmatchedSizes,
1442 1443
                     "The operation is neither 'array op array' "
                     "(where arrays have the same size and the same number of channels), "
1444 1445
                     "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
1446
        CV_Assert(type2 == CV_64F && (sz2.height == 1 || sz2.height == 4));
A
Andrey Kamaev 已提交
1447

1448 1449
        if (!muldiv)
        {
1450 1451 1452
            Mat sc = psrc2->getMat();
            depth2 = actualScalarDepth(sc.ptr<double>(), cn);
            if( depth2 == CV_64F && (depth1 < CV_32S || depth1 == CV_32F) )
1453 1454
                depth2 = CV_32F;
        }
A
Andrey Kamaev 已提交
1455
        else
1456
            depth2 = CV_64F;
1457
    }
1458

1459 1460 1461 1462 1463 1464
    if( dtype < 0 )
    {
        if( _dst.fixedType() )
            dtype = _dst.type();
        else
        {
1465
            if( !haveScalar && type1 != type2 )
1466 1467 1468
                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");
1469
            dtype = type1;
1470 1471 1472
        }
    }
    dtype = CV_MAT_DEPTH(dtype);
1473

1474 1475 1476 1477 1478 1479 1480
    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);
1481

1482 1483 1484 1485 1486 1487 1488 1489 1490 1491 1492
        // 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);
    }
1493

1494 1495
    dtype = CV_MAKETYPE(dtype, cn);
    wtype = CV_MAKETYPE(wtype, cn);
1496

1497 1498
    if( haveMask )
    {
1499 1500 1501
        int mtype = _mask.type();
        CV_Assert( (mtype == CV_8UC1 || mtype == CV_8SC1) && _mask.sameSize(*psrc1) );
        reallocate = !_dst.sameSize(*psrc1) || _dst.type() != dtype;
1502
    }
1503

1504 1505 1506
    _dst.createSameSize(*psrc1, dtype);
    if( reallocate )
        _dst.setTo(0.);
1507

1508 1509 1510 1511
    if( use_opencl &&
        ocl_arithm_op(*psrc1, *psrc2, _dst, _mask, wtype,
                      usrdata, oclop, haveScalar))
        return;
1512

1513 1514 1515 1516 1517 1518 1519 1520 1521
    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();
1522

1523 1524 1525 1526 1527 1528
    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);
1529
    BinaryFunc func = tab[CV_MAT_DEPTH(wtype)];
1530

1531 1532 1533 1534
    if( !haveScalar )
    {
        const Mat* arrays[] = { &src1, &src2, &dst, &mask, 0 };
        uchar* ptrs[4];
1535

1536 1537
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = total;
1538

1539 1540 1541 1542 1543 1544 1545 1546 1547 1548 1549 1550 1551 1552
        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;
1553

1554
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1555
        {
1556
            for( size_t j = 0; j < total; j += blocksize )
1557
            {
1558
                int bsz = (int)MIN(total - j, blocksize);
1559 1560 1561 1562 1563 1564 1565 1566 1567 1568 1569 1570 1571 1572 1573
                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;
                }
1574

1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594
                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;
1595 1596
            }
        }
1597 1598 1599 1600 1601
    }
    else
    {
        const Mat* arrays[] = { &src1, &dst, &mask, 0 };
        uchar* ptrs[3];
1602

1603 1604
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
1605

1606 1607 1608 1609 1610 1611 1612 1613 1614 1615
        _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;
1616

1617
        convertAndUnrollScalar( src2, wtype, buf2, blocksize);
1618

1619
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1620
        {
1621 1622
            for( size_t j = 0; j < total; j += blocksize )
            {
1623
                int bsz = (int)MIN(total - j, blocksize);
1624 1625 1626 1627
                Size bszn(bsz*cn, 1);
                const uchar *sptr1 = ptrs[0];
                const uchar* sptr2 = buf2;
                uchar* dptr = ptrs[1];
1628

1629 1630 1631 1632 1633
                if( cvtsrc1 )
                {
                    cvtsrc1( sptr1, 0, 0, 0, buf1, 0, bszn, 0 );
                    sptr1 = buf1;
                }
1634

1635 1636
                if( swapped12 )
                    std::swap(sptr1, sptr2);
1637

1638 1639 1640 1641 1642 1643 1644 1645 1646 1647 1648 1649 1650 1651 1652 1653 1654 1655 1656 1657 1658
                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;
            }
1659 1660 1661
        }
    }
}
1662

1663
static BinaryFunc* getAddTab()
1664
{
1665 1666 1667 1668 1669 1670 1671 1672
    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
    };
1673

1674 1675 1676 1677
    return addTab;
}

static BinaryFunc* getSubTab()
1678
{
1679 1680 1681 1682 1683 1684 1685 1686 1687 1688 1689
    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;
}
1690

1691
static BinaryFunc* getAbsDiffTab()
1692
{
1693 1694 1695 1696 1697 1698 1699 1700 1701 1702 1703
    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;
}
1704 1705

}
1706

1707 1708
void cv::add( InputArray src1, InputArray src2, OutputArray dst,
          InputArray mask, int dtype )
1709
{
1710
    arithm_op(src1, src2, dst, mask, dtype, getAddTab(), false, 0, OCL_OP_ADD );
1711 1712
}

1713 1714
void cv::subtract( InputArray src1, InputArray src2, OutputArray dst,
               InputArray mask, int dtype )
1715
{
A
Andrey Kamaev 已提交
1716
#ifdef HAVE_TEGRA_OPTIMIZATION
1717
    if (mask.empty() && src1.depth() == CV_8U && src2.depth() == CV_8U)
1718
    {
1719 1720 1721 1722 1723 1724 1725 1726 1727 1728 1729 1730 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742
        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;
            }
        }
1743
    }
A
Andrey Kamaev 已提交
1744
#endif
1745
    arithm_op(src1, src2, dst, mask, dtype, getSubTab(), false, 0, OCL_OP_SUB );
1746 1747
}

1748
void cv::absdiff( InputArray src1, InputArray src2, OutputArray dst )
1749
{
1750
    arithm_op(src1, src2, dst, noArray(), -1, getAbsDiffTab(), false, 0, OCL_OP_ABSDIFF);
1751
}
1752 1753 1754 1755 1756

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

1757 1758 1759
namespace cv
{

1760
template<typename T, typename WT> static void
1761 1762
mul_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, WT scale )
1763
{
1764 1765 1766
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1767

1768
    if( scale == (WT)1. )
1769
    {
1770
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1771
        {
V
Victoria Zhislina 已提交
1772
            int i=0;
1773
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1774
            for(; i <= size.width - 4; i += 4 )
1775
            {
1776 1777 1778 1779 1780 1781
                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;
1782 1783 1784

                t0 = saturate_cast<T>(src1[i+2] * src2[i+2]);
                t1 = saturate_cast<T>(src1[i+3] * src2[i+3]);
1785 1786
                dst[i+2] = t0;
                dst[i+3] = t1;
1787
            }
V
Victoria Zhislina 已提交
1788
            #endif
1789 1790 1791 1792 1793 1794
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(src1[i] * src2[i]);
        }
    }
    else
    {
1795
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1796
        {
V
Victoria Zhislina 已提交
1797
            int i = 0;
1798
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1799
            for(; i <= size.width - 4; i += 4 )
1800 1801 1802 1803 1804 1805 1806 1807 1808
            {
                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
1809
            #endif
1810 1811 1812 1813 1814 1815 1816
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(scale*(WT)src1[i]*src2[i]);
        }
    }
}

template<typename T> static void
1817 1818
div_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, double scale )
1819
{
1820 1821 1822
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1823

1824
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1825 1826
    {
        int i = 0;
1827
        #if CV_ENABLE_UNROLLED
1828 1829 1830 1831 1832 1833 1834 1835 1836
        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;
1837

1838 1839 1840 1841
                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));
1842

1843 1844 1845 1846 1847 1848 1849 1850 1851
                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;
1852

1853 1854 1855 1856
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1857
        #endif
1858 1859 1860 1861 1862 1863
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(src1[i]*scale/src2[i]) : 0;
    }
}

template<typename T> static void
1864 1865
recip_( const T*, size_t, const T* src2, size_t step2,
        T* dst, size_t step, Size size, double scale )
1866
{
1867 1868
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1869

1870
    for( ; size.height--; src2 += step2, dst += step )
1871 1872
    {
        int i = 0;
1873
        #if CV_ENABLE_UNROLLED
1874 1875 1876 1877 1878 1879 1880 1881 1882
        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;
1883

1884 1885 1886 1887
                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);
1888

1889 1890 1891 1892 1893 1894 1895 1896 1897
                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;
1898

1899 1900 1901 1902
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1903
        #endif
1904 1905 1906 1907
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(scale/src2[i]) : 0;
    }
}
1908 1909


1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938
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);
}
1939

1940 1941 1942 1943 1944
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);
}
1945

1946 1947 1948 1949 1950
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);
}
1951

1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 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
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);
}
2020

2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037
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);
}
2038 2039


2040
static BinaryFunc* getMulTab()
2041
{
2042 2043 2044 2045 2046 2047 2048 2049 2050
    static BinaryFunc mulTab[] =
    {
        (BinaryFunc)mul8u, (BinaryFunc)mul8s, (BinaryFunc)mul16u,
        (BinaryFunc)mul16s, (BinaryFunc)mul32s, (BinaryFunc)mul32f,
        (BinaryFunc)mul64f, 0
    };

    return mulTab;
}
2051

2052
static BinaryFunc* getDivTab()
2053
{
2054 2055 2056 2057 2058 2059
    static BinaryFunc divTab[] =
    {
        (BinaryFunc)div8u, (BinaryFunc)div8s, (BinaryFunc)div16u,
        (BinaryFunc)div16s, (BinaryFunc)div32s, (BinaryFunc)div32f,
        (BinaryFunc)div64f, 0
    };
2060

2061 2062 2063 2064
    return divTab;
}

static BinaryFunc* getRecipTab()
2065
{
2066 2067 2068 2069 2070 2071
    static BinaryFunc recipTab[] =
    {
        (BinaryFunc)recip8u, (BinaryFunc)recip8s, (BinaryFunc)recip16u,
        (BinaryFunc)recip16s, (BinaryFunc)recip32s, (BinaryFunc)recip32f,
        (BinaryFunc)recip64f, 0
    };
2072

2073 2074
    return recipTab;
}
2075

2076
}
2077

2078
void cv::multiply(InputArray src1, InputArray src2,
2079
                  OutputArray dst, double scale, int dtype)
2080
{
2081
    arithm_op(src1, src2, dst, noArray(), dtype, getMulTab(),
I
Ilya Lavrenov 已提交
2082
              true, &scale, std::abs(scale - 1.0) < DBL_EPSILON ? OCL_OP_MUL : OCL_OP_MUL_SCALE);
2083
}
2084

2085
void cv::divide(InputArray src1, InputArray src2,
2086 2087
                OutputArray dst, double scale, int dtype)
{
2088
    arithm_op(src1, src2, dst, noArray(), dtype, getDivTab(), true, &scale, OCL_OP_DIV_SCALE);
2089 2090
}

2091
void cv::divide(double scale, InputArray src2,
2092 2093
                OutputArray dst, int dtype)
{
2094
    arithm_op(src2, src2, dst, noArray(), dtype, getRecipTab(), true, &scale, OCL_OP_RECIP_SCALE);
2095 2096
}

2097 2098 2099 2100
/****************************************************************************************\
*                                      addWeighted                                       *
\****************************************************************************************/

2101 2102 2103
namespace cv
{

2104
template<typename T, typename WT> static void
2105 2106 2107 2108 2109 2110 2111 2112 2113 2114
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 )
2115
    {
2116
        int x = 0;
2117
        #if CV_ENABLE_UNROLLED
2118
        for( ; x <= size.width - 4; x += 4 )
2119
        {
2120 2121 2122
            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;
2123

2124 2125 2126
            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;
2127
        }
V
Victoria Zhislina 已提交
2128
        #endif
2129 2130
        for( ; x < size.width; x++ )
            dst[x] = saturate_cast<T>(src1[x]*alpha + src2[x]*beta + gamma);
2131 2132 2133 2134 2135
    }
}


static void
2136 2137 2138 2139 2140 2141 2142
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];
2143

2144
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2145
    {
2146
        int x = 0;
2147

2148 2149
#if CV_SSE2
        if( USE_SSE2 )
2150
        {
2151 2152
            __m128 a4 = _mm_set1_ps(alpha), b4 = _mm_set1_ps(beta), g4 = _mm_set1_ps(gamma);
            __m128i z = _mm_setzero_si128();
2153

2154
            for( ; x <= size.width - 8; x += 8 )
2155
            {
2156 2157
                __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);
2158

2159 2160 2161 2162
                __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));
2163

2164 2165 2166
                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);
2167

2168 2169
                u = _mm_packs_epi32(_mm_cvtps_epi32(u0), _mm_cvtps_epi32(u1));
                u = _mm_packus_epi16(u, u);
2170

2171
                _mm_storel_epi64((__m128i*)(dst + x), u);
2172 2173
            }
        }
2174
#endif
2175
        #if CV_ENABLE_UNROLLED
2176
        for( ; x <= size.width - 4; x += 4 )
2177
        {
2178 2179 2180
            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;
2181

2182 2183
            dst[x] = saturate_cast<uchar>(t0);
            dst[x+1] = saturate_cast<uchar>(t1);
2184

2185 2186
            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;
2187

2188 2189 2190
            dst[x+2] = saturate_cast<uchar>(t0);
            dst[x+3] = saturate_cast<uchar>(t1);
        }
V
Victoria Zhislina 已提交
2191
        #endif
2192

2193 2194 2195 2196
        for( ; x < size.width; x++ )
        {
            float t0 = CV_8TO32F(src1[x])*alpha + CV_8TO32F(src2[x])*beta + gamma;
            dst[x] = saturate_cast<uchar>(t0);
2197 2198 2199 2200
        }
    }
}

2201 2202
static void addWeighted8s( const schar* src1, size_t step1, const schar* src2, size_t step2,
                           schar* dst, size_t step, Size sz, void* scalars )
2203
{
2204
    addWeighted_<schar, float>(src1, step1, src2, step2, dst, step, sz, scalars);
2205 2206
}

2207 2208
static void addWeighted16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                            ushort* dst, size_t step, Size sz, void* scalars )
2209
{
2210 2211
    addWeighted_<ushort, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2212

2213 2214
static void addWeighted16s( const short* src1, size_t step1, const short* src2, size_t step2,
                            short* dst, size_t step, Size sz, void* scalars )
2215
{
2216 2217
    addWeighted_<short, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2218

2219 2220
static void addWeighted32s( const int* src1, size_t step1, const int* src2, size_t step2,
                            int* dst, size_t step, Size sz, void* scalars )
2221
{
2222
    addWeighted_<int, double>(src1, step1, src2, step2, dst, step, sz, scalars);
2223 2224
}

2225 2226
static void addWeighted32f( const float* src1, size_t step1, const float* src2, size_t step2,
                            float* dst, size_t step, Size sz, void* scalars )
2227
{
2228 2229
    addWeighted_<float, double>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2230

2231 2232 2233 2234 2235
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
2236

2237
static BinaryFunc* getAddWeightedTab()
2238
{
2239 2240 2241 2242 2243 2244 2245 2246 2247
    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;
}
2248

2249
}
2250

2251
void cv::addWeighted( InputArray src1, double alpha, InputArray src2,
2252 2253 2254
                      double beta, double gamma, OutputArray dst, int dtype )
{
    double scalars[] = {alpha, beta, gamma};
2255
    arithm_op(src1, src2, dst, noArray(), dtype, getAddWeightedTab(), true, scalars, OCL_OP_ADDW);
2256 2257
}

2258

2259
/****************************************************************************************\
2260
*                                          compare                                       *
2261 2262
\****************************************************************************************/

2263
namespace cv
2264 2265
{

2266 2267 2268
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)
2269
{
2270 2271 2272
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    if( code == CMP_GE || code == CMP_LT )
2273
    {
2274 2275 2276
        std::swap(src1, src2);
        std::swap(step1, step2);
        code = code == CMP_GE ? CMP_LE : CMP_GT;
2277
    }
2278

2279
    if( code == CMP_GT || code == CMP_LE )
2280
    {
2281 2282 2283 2284
        int m = code == CMP_GT ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2285
            #if CV_ENABLE_UNROLLED
2286 2287 2288 2289 2290 2291 2292 2293 2294 2295
            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
2296
            #endif
2297 2298
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2299
               }
2300
    }
2301
    else if( code == CMP_EQ || code == CMP_NE )
2302
    {
2303 2304 2305 2306
        int m = code == CMP_EQ ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2307
            #if CV_ENABLE_UNROLLED
2308 2309 2310 2311 2312 2313 2314 2315 2316 2317
            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
2318
            #endif
2319 2320 2321
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
2322
    }
2323
}
2324

K
kdrobnyh 已提交
2325 2326 2327 2328 2329 2330 2331 2332 2333 2334 2335
#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
2336

2337 2338
static void cmp8u(const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2339
{
K
kdrobnyh 已提交
2340 2341 2342 2343 2344 2345 2346 2347 2348
#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
2349
  //vz optimized  cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2350
    int code = *(int*)_cmpop;
2351 2352 2353 2354 2355 2356 2357 2358 2359 2360 2361 2362 2363 2364 2365
    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;
2366 2367
            #if CV_SSE2
            if( USE_SSE2 ){
2368 2369
                __m128i m128 = code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
                __m128i c128 = _mm_set1_epi8 (-128);
2370 2371 2372 2373 2374 2375 2376 2377 2378 2379 2380 2381 2382
                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);

                }
            }
2383 2384
           #endif

2385
            for( ; x < size.width; x++ ){
2386
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2387
            }
2388 2389 2390 2391 2392
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2393
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2394 2395
        {
            int x = 0;
2396 2397
            #if CV_SSE2
            if( USE_SSE2 ){
2398
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
2399 2400 2401 2402 2403 2404 2405 2406
                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);
                }
            }
2407 2408 2409 2410 2411
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2412 2413
}

2414 2415
static void cmp8s(const schar* src1, size_t step1, const schar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2416
{
2417
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2418 2419
}

2420 2421
static void cmp16u(const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2422
{
K
kdrobnyh 已提交
2423 2424 2425 2426 2427 2428 2429 2430 2431
#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
2432
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2433 2434
}

2435 2436
static void cmp16s(const short* src1, size_t step1, const short* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2437
{
K
kdrobnyh 已提交
2438 2439 2440 2441 2442 2443 2444 2445 2446
#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
2447 2448
   //vz optimized cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);

2449
    int code = *(int*)_cmpop;
2450 2451 2452 2453 2454 2455 2456 2457 2458 2459 2460 2461 2462 2463 2464
    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;
2465 2466
            #if CV_SSE2
            if( USE_SSE2){//
2467
                __m128i m128 =  code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2468 2469 2470 2471 2472 2473 2474 2475 2476 2477 2478 2479 2480 2481 2482 2483 2484 2485 2486 2487 2488 2489
                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;
                }
            }
2490 2491
           #endif

2492
            for( ; x < size.width; x++ ){
2493
                 dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2494
            }
2495 2496 2497 2498 2499
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2500
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2501 2502
        {
            int x = 0;
2503 2504
            #if CV_SSE2
            if( USE_SSE2 ){
2505
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2506 2507 2508 2509 2510 2511 2512 2513 2514 2515 2516 2517 2518 2519 2520 2521 2522 2523 2524 2525 2526 2527
                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;
                }
            }
2528 2529 2530 2531 2532
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2533 2534
}

2535 2536 2537 2538 2539
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);
}
2540

2541 2542
static void cmp32f(const float* src1, size_t step1, const float* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2543
{
K
kdrobnyh 已提交
2544 2545 2546 2547 2548 2549 2550 2551 2552
#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
2553 2554
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
}
2555

2556 2557
static void cmp64f(const double* src1, size_t step1, const double* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2558
{
2559
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2560 2561
}

2562
static BinaryFunc getCmpFunc(int depth)
2563
{
2564 2565 2566 2567 2568 2569 2570 2571
    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
    };
2572

2573 2574
    return cmpTab[depth];
}
2575

2576
static double getMinVal(int depth)
2577
{
2578 2579 2580
    static const double tab[] = {0, -128, 0, -32768, INT_MIN, -FLT_MAX, -DBL_MAX, 0};
    return tab[depth];
}
2581

2582
static double getMaxVal(int depth)
2583
{
2584 2585 2586
    static const double tab[] = {255, 127, 65535, 32767, INT_MAX, FLT_MAX, DBL_MAX, 0};
    return tab[depth];
}
2587

I
Ilya Lavrenov 已提交
2588 2589 2590 2591 2592 2593 2594 2595 2596 2597 2598 2599 2600 2601 2602 2603 2604 2605 2606 2607 2608 2609 2610 2611 2612 2613 2614 2615 2616 2617 2618 2619 2620 2621
static bool ocl_compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op)
{
    if ( !((_src1.isMat() || _src1.isUMat()) && (_src2.isMat() || _src2.isUMat())) )
        return false;

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

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

    _dst.create(size, CV_8UC(cn));
    UMat dst = _dst.getUMat();

    const char * const operationMap[] = { "==", ">", ">=", "<", "<=", "!=" };
    ocl::Kernel k("KF", ocl::core::arithm_oclsrc,
                  format("-D BINARY_OP -D srcT1=%s -D workT=srcT1"
                         " -D OP_CMP -D CMP_OPERATOR=%s%s",
                         ocl::typeToStr(CV_MAKE_TYPE(depth, 1)),
                         operationMap[op],
                         doubleSupport ? " -D DOUBLE_SUPPORT" : ""));

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

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

2622 2623
}

2624
void cv::compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op)
2625 2626 2627
{
    CV_Assert( op == CMP_LT || op == CMP_LE || op == CMP_EQ ||
               op == CMP_NE || op == CMP_GE || op == CMP_GT );
2628

2629 2630
    if (ocl::useOpenCL() && _dst.isUMat() &&
            ocl_compare(_src1, _src2, _dst, op))
I
Ilya Lavrenov 已提交
2631 2632
        return;

2633 2634
    int kind1 = _src1.kind(), kind2 = _src2.kind();
    Mat src1 = _src1.getMat(), src2 = _src2.getMat();
2635

2636
    if( kind1 == kind2 && src1.dims <= 2 && src2.dims <= 2 && src1.size() == src2.size() && src1.type() == src2.type() )
2637
    {
2638 2639
        int cn = src1.channels();
        _dst.create(src1.size(), CV_8UC(cn));
2640 2641
        Mat dst = _dst.getMat();
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
2642
        getCmpFunc(src1.depth())(src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, &op);
2643 2644
        return;
    }
2645

2646
    bool haveScalar = false;
2647

2648
    if( (kind1 == _InputArray::MATX) + (kind2 == _InputArray::MATX) == 1 ||
2649 2650 2651
        src1.size != src2.size || src1.type() != src2.type() )
    {
        if( checkScalar(src1, src2.type(), kind1, kind2) )
2652
        {
2653 2654 2655 2656 2657 2658 2659 2660 2661 2662 2663
            // src1 is a scalar; swap it with src2
            swap(src1, src2);
            op = op == CMP_LT ? CMP_GT : op == CMP_LE ? CMP_GE :
                op == CMP_GE ? CMP_LE : op == CMP_GT ? CMP_LT : op;
        }
        else if( !checkScalar(src2, src1.type(), kind2, kind1) )
            CV_Error( CV_StsUnmatchedSizes,
                     "The operation is neither 'array op array' (where arrays have the same size and the same type), "
                     "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
    }
2664

2665

2666
    int cn = src1.channels(), depth1 = src1.depth(), depth2 = src2.depth();
2667

2668 2669 2670
    _dst.create(src1.dims, src1.size, CV_8UC(cn));
    src1 = src1.reshape(1); src2 = src2.reshape(1);
    Mat dst = _dst.getMat().reshape(1);
2671

2672 2673
    size_t esz = src1.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
2674
    BinaryFunc func = getCmpFunc(depth1);
2675

2676
    if( !haveScalar )
2677
    {
2678 2679
        const Mat* arrays[] = { &src1, &src2, &dst, 0 };
        uchar* ptrs[3];
2680

2681 2682
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size;
2683

2684 2685
        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 );
2686
    }
2687
    else
2688
    {
2689 2690
        const Mat* arrays[] = { &src1, &dst, 0 };
        uchar* ptrs[2];
2691

2692 2693
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
2694

2695 2696 2697 2698 2699 2700
        AutoBuffer<uchar> _buf(blocksize*esz);
        uchar *buf = _buf;

        if( depth1 > CV_32S )
            convertAndUnrollScalar( src2, depth1, buf, blocksize );
        else
2701
        {
2702 2703 2704 2705 2706 2707 2708
            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;
            }
2709

2710 2711 2712 2713 2714
            if( fval > getMaxVal(depth1) )
            {
                dst = Scalar::all(op == CMP_LT || op == CMP_LE || op == CMP_NE ? 255 : 0);
                return;
            }
2715

2716 2717 2718 2719 2720 2721 2722 2723 2724 2725 2726 2727 2728 2729 2730
            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);
        }
2731

2732
        for( size_t i = 0; i < it.nplanes; i++, ++it )
2733
        {
2734 2735
            for( size_t j = 0; j < total; j += blocksize )
            {
2736
                int bsz = (int)MIN(total - j, blocksize);
2737 2738 2739 2740 2741
                func( ptrs[0], 0, buf, 0, ptrs[1], 0, Size(bsz, 1), &op);
                ptrs[0] += bsz*esz;
                ptrs[1] += bsz;
            }
        }
2742
    }
2743
}
2744

2745 2746 2747
/****************************************************************************************\
*                                        inRange                                         *
\****************************************************************************************/
2748

2749 2750
namespace cv
{
2751

2752 2753 2754 2755 2756 2757 2758 2759
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]);
2760

2761
    for( ; size.height--; src1 += step1, src2 += step2, src3 += step3, dst += step )
V
Vadim Pisarevsky 已提交
2762
    {
2763
        int x = 0;
2764
        #if CV_ENABLE_UNROLLED
2765
        for( ; x <= size.width - 4; x += 4 )
V
Vadim Pisarevsky 已提交
2766
        {
2767 2768 2769 2770 2771 2772 2773
            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
2774
        }
V
Victoria Zhislina 已提交
2775
        #endif
2776 2777
        for( ; x < size.width; x++ )
            dst[x] = (uchar)-(src2[x] <= src1[x] && src1[x] <= src3[x]);
V
Vadim Pisarevsky 已提交
2778
    }
2779 2780
}

2781

2782 2783
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)
2784
{
2785 2786
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2787

2788 2789
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)
2790
{
2791 2792
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2793

2794 2795
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)
2796
{
2797 2798
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2799

2800 2801 2802 2803
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);
2804 2805
}

2806 2807
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)
2808
{
2809 2810
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2811

2812 2813 2814 2815
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);
2816 2817
}

2818 2819
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)
2820
{
2821
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
2822
}
2823

2824 2825 2826 2827 2828 2829 2830 2831 2832 2833 2834 2835 2836 2837 2838 2839
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];
2840

2841 2842 2843 2844
    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
2845
    }
2846
}
2847

2848 2849
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 );
2850

2851
static InRangeFunc getInRangeFunc(int depth)
2852
{
2853 2854 2855 2856 2857 2858 2859 2860 2861
    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];
}
2862

2863 2864
}

2865 2866
void cv::inRange(InputArray _src, InputArray _lowerb,
                 InputArray _upperb, OutputArray _dst)
2867 2868 2869
{
    int skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
    Mat src = _src.getMat(), lb = _lowerb.getMat(), ub = _upperb.getMat();
2870

2871
    bool lbScalar = false, ubScalar = false;
2872

2873
    if( (lkind == _InputArray::MATX && skind != _InputArray::MATX) ||
2874 2875 2876 2877 2878 2879 2880
        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;
    }
2881

2882
    if( (ukind == _InputArray::MATX && skind != _InputArray::MATX) ||
2883 2884 2885 2886 2887 2888 2889
        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;
    }
2890

2891
    CV_Assert( ((int)lbScalar ^ (int)ubScalar) == 0 );
2892

2893
    int cn = src.channels(), depth = src.depth();
2894

2895 2896
    size_t esz = src.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
2897

2898 2899
    _dst.create(src.dims, src.size, CV_8U);
    Mat dst = _dst.getMat();
2900
    InRangeFunc func = getInRangeFunc(depth);
2901

2902 2903 2904
    const Mat* arrays_sc[] = { &src, &dst, 0 };
    const Mat* arrays_nosc[] = { &src, &dst, &lb, &ub, 0 };
    uchar* ptrs[4];
2905

2906 2907
    NAryMatIterator it(lbScalar && ubScalar ? arrays_sc : arrays_nosc, ptrs);
    size_t total = it.size, blocksize = std::min(total, blocksize0);
2908

2909 2910 2911
    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);
2912

2913 2914 2915 2916
    if( lbScalar && ubScalar )
    {
        lbuf = buf;
        ubuf = buf = alignPtr(buf + blocksize*esz, 16);
2917

2918 2919
        CV_Assert( lb.type() == ub.type() );
        int scdepth = lb.depth();
2920

2921 2922 2923 2924
        if( scdepth != depth && depth < CV_32S )
        {
            int* ilbuf = (int*)alignPtr(buf + blocksize*esz, 16);
            int* iubuf = ilbuf + cn;
2925

2926 2927 2928
            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);
2929
            int minval = cvRound(getMinVal(depth)), maxval = cvRound(getMaxVal(depth));
2930

2931 2932 2933 2934 2935 2936 2937 2938
            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);
        }
2939

2940 2941 2942
        convertAndUnrollScalar( lb, src.type(), lbuf, blocksize );
        convertAndUnrollScalar( ub, src.type(), ubuf, blocksize );
    }
2943

2944
    for( size_t i = 0; i < it.nplanes; i++, ++it )
V
Vadim Pisarevsky 已提交
2945
    {
2946 2947
        for( size_t j = 0; j < total; j += blocksize )
        {
2948
            int bsz = (int)MIN(total - j, blocksize);
2949 2950 2951 2952 2953 2954 2955 2956 2957 2958 2959 2960 2961 2962
            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));
2963
            if( cn > 1 )
2964 2965 2966 2967
                inRangeReduce(mbuf, ptrs[1], bsz, cn);
            ptrs[0] += delta;
            ptrs[1] += bsz;
        }
V
Vadim Pisarevsky 已提交
2968
    }
2969 2970 2971 2972 2973 2974 2975 2976 2977 2978
}

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

CV_IMPL void
cvNot( const CvArr* srcarr, CvArr* dstarr )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
2979
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
2980 2981 2982 2983 2984 2985 2986 2987 2988
    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;
2989
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
2990 2991 2992 2993 2994
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
    cv::bitwise_and( src1, src2, dst, mask );
}

2995

2996 2997 2998 2999 3000
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;
3001
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3002 3003 3004 3005 3006 3007 3008 3009 3010 3011 3012
    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;
3013
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3014 3015 3016 3017 3018 3019 3020 3021 3022 3023
    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;
3024
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3025 3026
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3027
    cv::bitwise_and( src, (const cv::Scalar&)s, dst, mask );
3028 3029 3030 3031 3032 3033 3034
}


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;
3035
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3036 3037
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3038
    cv::bitwise_or( src, (const cv::Scalar&)s, dst, mask );
3039 3040 3041 3042 3043 3044 3045
}


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;
3046
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3047 3048
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3049
    cv::bitwise_xor( src, (const cv::Scalar&)s, dst, mask );
3050 3051
}

3052

3053 3054 3055 3056
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;
3057
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3058 3059
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3060
    cv::add( src1, src2, dst, mask, dst.type() );
3061 3062
}

3063

3064 3065 3066 3067
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;
3068
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3069 3070
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3071
    cv::subtract( src1, src2, dst, mask, dst.type() );
3072 3073
}

3074

3075 3076 3077 3078
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;
3079
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3080 3081
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3082
    cv::add( src1, (const cv::Scalar&)value, dst, mask, dst.type() );
3083 3084
}

3085

3086 3087 3088 3089
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;
3090
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3091 3092
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3093
    cv::subtract( (const cv::Scalar&)value, src1, dst, mask, dst.type() );
3094 3095
}

3096

3097 3098 3099 3100 3101
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);
3102 3103
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::multiply( src1, src2, dst, scale, dst.type() );
3104 3105
}

3106

3107 3108 3109 3110 3111
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;
3112
    CV_Assert( src2.size == dst.size && src2.channels() == dst.channels() );
3113 3114

    if( srcarr1 )
3115
        cv::divide( cv::cvarrToMat(srcarr1), src2, dst, scale, dst.type() );
3116
    else
3117
        cv::divide( scale, src2, dst, dst.type() );
3118 3119 3120 3121 3122 3123 3124 3125 3126 3127
}


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);
3128 3129
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::addWeighted( src1, alpha, src2, beta, gamma, dst, dst.type() );
3130 3131 3132 3133 3134 3135 3136
}


CV_IMPL  void
cvAbsDiff( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3137
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3138 3139 3140 3141 3142 3143 3144 3145 3146

    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);
3147
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3148

3149
    cv::absdiff( src1, (const cv::Scalar&)scalar, dst );
3150 3151
}

3152

3153 3154 3155 3156 3157
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);
3158
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3159 3160 3161 3162

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

3163

3164 3165 3166 3167
CV_IMPL void
cvInRangeS( const void* srcarr1, CvScalar lowerb, CvScalar upperb, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3168
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3169

3170
    cv::inRange( src1, (const cv::Scalar&)lowerb, (const cv::Scalar&)upperb, dst );
3171 3172 3173 3174 3175 3176 3177
}


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);
3178
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3179 3180 3181 3182 3183 3184 3185 3186 3187

    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);
3188
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3189 3190 3191 3192 3193 3194 3195 3196 3197

    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);
3198
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3199 3200 3201 3202 3203 3204 3205 3206 3207

    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);
3208
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3209 3210 3211 3212

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

3213

3214 3215 3216 3217
CV_IMPL void
cvMinS( const void* srcarr1, double value, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3218
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3219 3220 3221 3222 3223 3224 3225 3226 3227

    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);
3228
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3229 3230 3231 3232 3233

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

/* End of file. */