arithm.cpp 121.7 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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struct NOP {};
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#if CV_SSE2

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

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

#endif

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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template<typename T> struct OpNot
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{
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    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T ) const { return ~a; }
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};
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static inline void fixSteps(Size sz, size_t elemSize, size_t& step1, size_t& step2, size_t& step)
{
    if( sz.height == 1 )
        step1 = step2 = step = sz.width*elemSize;
}
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static void add8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
{
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#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviAdd_8u_C1RSfs(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz, 0))
        return;
#endif
    (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 (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviAdd_16u_C1RSfs(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz, 0))
        return;
#endif
    (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* )
491
{
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#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviAdd_16s_C1RSfs(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz, 0))
        return;
#endif
    (vBinOp<short, OpAdd<short>, IF_SIMD(VAdd<short>)>(src1, step1, src2, step2, dst, step, sz));
498
}
499

500 501 502
static void add32s( const int* src1, size_t step1,
                    const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* )
503
{
504
    vBinOp32<int, OpAdd<int>, IF_SIMD(VAdd<int>)>(src1, step1, src2, step2, dst, step, sz);
505
}
506

507 508 509
static void add32f( const float* src1, size_t step1,
                    const float* src2, size_t step2,
                    float* dst, size_t step, Size sz, void* )
510
{
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#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviAdd_32f_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz))
        return;
#endif
    (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
{
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#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviSub_8u_C1RSfs(src2, (int)step2, src1, (int)step1, dst, (int)step, (IppiSize&)sz, 0))
        return;
#endif
    (vBinOp<uchar, OpSub<uchar>, IF_SIMD(VSub<uchar>)>(src1, step1, src2, step2, dst, step, sz));
536
}
537

538 539 540
static void sub8s( const schar* src1, size_t step1,
                   const schar* src2, size_t step2,
                   schar* dst, size_t step, Size sz, void* )
541
{
542
    vBinOp<schar, OpSub<schar>, IF_SIMD(VSub<schar>)>(src1, step1, src2, step2, dst, step, sz);
543
}
544

545 546 547
static void sub16u( const ushort* src1, size_t step1,
                    const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* )
548
{
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#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviSub_16u_C1RSfs(src2, (int)step2, src1, (int)step1, dst, (int)step, (IppiSize&)sz, 0))
        return;
#endif
    (vBinOp<ushort, OpSub<ushort>, IF_SIMD(VSub<ushort>)>(src1, step1, src2, step2, dst, step, sz));
555
}
556

557 558 559
static void sub16s( const short* src1, size_t step1,
                    const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* )
560
{
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#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviSub_16s_C1RSfs(src2, (int)step2, src1, (int)step1, dst, (int)step, (IppiSize&)sz, 0))
        return;
#endif
    (vBinOp<short, OpSub<short>, IF_SIMD(VSub<short>)>(src1, step1, src2, step2, dst, step, sz));
567
}
568

569 570 571
static void sub32s( const int* src1, size_t step1,
                    const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* )
572
{
573
    vBinOp32<int, OpSub<int>, IF_SIMD(VSub<int>)>(src1, step1, src2, step2, dst, step, sz);
574
}
575

576 577 578
static void sub32f( const float* src1, size_t step1,
                   const float* src2, size_t step2,
                   float* dst, size_t step, Size sz, void* )
579
{
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#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviSub_32f_C1R(src2, (int)step2, src1, (int)step1, dst, (int)step, (IppiSize&)sz))
        return;
#endif
    (vBinOp32<float, OpSub<float>, IF_SIMD(VSub<float>)>(src1, step1, src2, step2, dst, step, sz));
586
}
587

588 589 590
static void sub64f( const double* src1, size_t step1,
                    const double* src2, size_t step2,
                    double* dst, size_t step, Size sz, void* )
591
{
592
    vBinOp64<double, OpSub<double>, IF_SIMD(VSub<double>)>(src1, step1, src2, step2, dst, step, sz);
593
}
594

595 596
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); }
597

598 599 600
static void max8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
601
{
602 603 604 605 606
#if (ARITHM_USE_IPP == 1)
    uchar* s1 = (uchar*)src1;
    uchar* s2 = (uchar*)src2;
    uchar* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
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    int i = 0;
    for(; i < sz.height; i++)
609
    {
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        if (0 > ippicvsMaxEvery_8u(s1, s2, d, sz.width))
            break;
        s1 += step1;
        s2 += step2;
        d  += step;
615
    }
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    if (i == sz.height)
        return;
618
#endif
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    vBinOp<uchar, OpMax<uchar>, IF_SIMD(VMax<uchar>)>(src1, step1, src2, step2, dst, step, sz);
620
}
621

622 623 624
static void max8s( const schar* src1, size_t step1,
                   const schar* src2, size_t step2,
                   schar* dst, size_t step, Size sz, void* )
625
{
626
    vBinOp<schar, OpMax<schar>, IF_SIMD(VMax<schar>)>(src1, step1, src2, step2, dst, step, sz);
627
}
628

629 630 631
static void max16u( const ushort* src1, size_t step1,
                    const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* )
632
{
633 634 635 636 637
#if (ARITHM_USE_IPP == 1)
    ushort* s1 = (ushort*)src1;
    ushort* s2 = (ushort*)src2;
    ushort* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
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    int i = 0;
    for(; i < sz.height; i++)
640
    {
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        if (0 > ippicvsMaxEvery_16u(s1, s2, d, sz.width))
            break;
        s1 = (ushort*)((uchar*)s1 + step1);
        s2 = (ushort*)((uchar*)s2 + step2);
        d  = (ushort*)((uchar*)d + step);
646
    }
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    if (i == sz.height)
        return;
649
#endif
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    vBinOp<ushort, OpMax<ushort>, IF_SIMD(VMax<ushort>)>(src1, step1, src2, step2, dst, step, sz);
651
}
652

653 654 655
static void max16s( const short* src1, size_t step1,
                    const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* )
656
{
657
    vBinOp<short, OpMax<short>, IF_SIMD(VMax<short>)>(src1, step1, src2, step2, dst, step, sz);
658
}
659

660 661 662
static void max32s( const int* src1, size_t step1,
                    const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* )
663
{
664
    vBinOp32<int, OpMax<int>, IF_SIMD(VMax<int>)>(src1, step1, src2, step2, dst, step, sz);
665
}
666

667 668 669
static void max32f( const float* src1, size_t step1,
                    const float* src2, size_t step2,
                    float* dst, size_t step, Size sz, void* )
670
{
671 672 673 674 675
#if (ARITHM_USE_IPP == 1)
    float* s1 = (float*)src1;
    float* s2 = (float*)src2;
    float* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
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    int i = 0;
    for(; i < sz.height; i++)
678
    {
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        if (0 > ippicvsMaxEvery_32f(s1, s2, d, sz.width))
            break;
        s1 = (float*)((uchar*)s1 + step1);
        s2 = (float*)((uchar*)s2 + step2);
        d  = (float*)((uchar*)d + step);
684
    }
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    if (i == sz.height)
        return;
687
#endif
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    vBinOp32<float, OpMax<float>, IF_SIMD(VMax<float>)>(src1, step1, src2, step2, dst, step, sz);
689
}
690

691 692 693
static void max64f( const double* src1, size_t step1,
                    const double* src2, size_t step2,
                    double* dst, size_t step, Size sz, void* )
694
{
695
    vBinOp64<double, OpMax<double>, IF_SIMD(VMax<double>)>(src1, step1, src2, step2, dst, step, sz);
696
}
697

698 699 700
static void min8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
701
{
702 703 704 705 706
#if (ARITHM_USE_IPP == 1)
    uchar* s1 = (uchar*)src1;
    uchar* s2 = (uchar*)src2;
    uchar* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
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    int i = 0;
    for(; i < sz.height; i++)
709
    {
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        if (0 > ippicvsMinEvery_8u(s1, s2, d, sz.width))
            break;
        s1 += step1;
        s2 += step2;
        d  += step;
715
    }
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    if (i == sz.height)
        return;
718
#endif
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    vBinOp<uchar, OpMin<uchar>, IF_SIMD(VMin<uchar>)>(src1, step1, src2, step2, dst, step, sz);
720
}
721

722 723 724 725
static void min8s( const schar* src1, size_t step1,
                   const schar* src2, size_t step2,
                   schar* dst, size_t step, Size sz, void* )
{
726
    vBinOp<schar, OpMin<schar>, IF_SIMD(VMin<schar>)>(src1, step1, src2, step2, dst, step, sz);
727
}
728

729 730 731 732
static void min16u( const ushort* src1, size_t step1,
                    const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* )
{
733 734 735 736 737
#if (ARITHM_USE_IPP == 1)
    ushort* s1 = (ushort*)src1;
    ushort* s2 = (ushort*)src2;
    ushort* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
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    int i = 0;
    for(; i < sz.height; i++)
740
    {
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        if (0 > ippicvsMinEvery_16u(s1, s2, d, sz.width))
            break;
        s1 = (ushort*)((uchar*)s1 + step1);
        s2 = (ushort*)((uchar*)s2 + step2);
        d  = (ushort*)((uchar*)d + step);
746
    }
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747 748
    if (i == sz.height)
        return;
749
#endif
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    vBinOp<ushort, OpMin<ushort>, IF_SIMD(VMin<ushort>)>(src1, step1, src2, step2, dst, step, sz);
751
}
752

753 754 755 756
static void min16s( const short* src1, size_t step1,
                    const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* )
{
757
    vBinOp<short, OpMin<short>, IF_SIMD(VMin<short>)>(src1, step1, src2, step2, dst, step, sz);
758
}
759

760 761 762
static void min32s( const int* src1, size_t step1,
                    const int* src2, size_t step2,
                    int* dst, size_t step, Size sz, void* )
763
{
764
    vBinOp32<int, OpMin<int>, IF_SIMD(VMin<int>)>(src1, step1, src2, step2, dst, step, sz);
765
}
766

767 768 769
static void min32f( const float* src1, size_t step1,
                    const float* src2, size_t step2,
                    float* dst, size_t step, Size sz, void* )
770
{
771 772 773 774 775
#if (ARITHM_USE_IPP == 1)
    float* s1 = (float*)src1;
    float* s2 = (float*)src2;
    float* d  = dst;
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
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    int i = 0;
    for(; i < sz.height; i++)
778
    {
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        if (0 > ippicvsMinEvery_32f(s1, s2, d, sz.width))
            break;
        s1 = (float*)((uchar*)s1 + step1);
        s2 = (float*)((uchar*)s2 + step2);
        d  = (float*)((uchar*)d + step);
784
    }
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785 786
    if (i == sz.height)
        return;
787
#endif
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788
    vBinOp32<float, OpMin<float>, IF_SIMD(VMin<float>)>(src1, step1, src2, step2, dst, step, sz);
789
}
790

791 792 793
static void min64f( const double* src1, size_t step1,
                    const double* src2, size_t step2,
                    double* dst, size_t step, Size sz, void* )
794
{
795
    vBinOp64<double, OpMin<double>, IF_SIMD(VMin<double>)>(src1, step1, src2, step2, dst, step, sz);
796
}
797

798 799 800
static void absdiff8u( const uchar* src1, size_t step1,
                       const uchar* src2, size_t step2,
                       uchar* dst, size_t step, Size sz, void* )
801
{
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802 803 804 805 806 807
#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviAbsDiff_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz))
        return;
#endif
    (vBinOp<uchar, OpAbsDiff<uchar>, IF_SIMD(VAbsDiff<uchar>)>(src1, step1, src2, step2, dst, step, sz));
808
}
809

810 811 812 813
static void absdiff8s( const schar* src1, size_t step1,
                       const schar* src2, size_t step2,
                       schar* dst, size_t step, Size sz, void* )
{
814
    vBinOp<schar, OpAbsDiff<schar>, IF_SIMD(VAbsDiff<schar>)>(src1, step1, src2, step2, dst, step, sz);
815
}
816

817 818 819 820
static void absdiff16u( const ushort* src1, size_t step1,
                        const ushort* src2, size_t step2,
                        ushort* dst, size_t step, Size sz, void* )
{
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821 822 823 824 825 826
#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviAbsDiff_16u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz))
        return;
#endif
    (vBinOp<ushort, OpAbsDiff<ushort>, IF_SIMD(VAbsDiff<ushort>)>(src1, step1, src2, step2, dst, step, sz));
827
}
828

829 830 831 832
static void absdiff16s( const short* src1, size_t step1,
                        const short* src2, size_t step2,
                        short* dst, size_t step, Size sz, void* )
{
833
    vBinOp<short, OpAbsDiff<short>, IF_SIMD(VAbsDiff<short>)>(src1, step1, src2, step2, dst, step, sz);
834
}
835

836 837 838 839
static void absdiff32s( const int* src1, size_t step1,
                        const int* src2, size_t step2,
                        int* dst, size_t step, Size sz, void* )
{
840
    vBinOp32<int, OpAbsDiff<int>, IF_SIMD(VAbsDiff<int>)>(src1, step1, src2, step2, dst, step, sz);
841
}
842

843 844 845 846
static void absdiff32f( const float* src1, size_t step1,
                        const float* src2, size_t step2,
                        float* dst, size_t step, Size sz, void* )
{
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847 848 849 850 851 852
#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviAbsDiff_32f_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz))
        return;
#endif
    (vBinOp32<float, OpAbsDiff<float>, IF_SIMD(VAbsDiff<float>)>(src1, step1, src2, step2, dst, step, sz));
853
}
854

855 856 857 858
static void absdiff64f( const double* src1, size_t step1,
                        const double* src2, size_t step2,
                        double* dst, size_t step, Size sz, void* )
{
859
    vBinOp64<double, OpAbsDiff<double>, IF_SIMD(VAbsDiff<double>)>(src1, step1, src2, step2, dst, step, sz);
860 861
}

862

863 864 865 866
static void and8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
{
V
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867 868 869 870 871 872
#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviAnd_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz))
        return;
#endif
    (vBinOp<uchar, OpAnd<uchar>, IF_SIMD(VAnd<uchar>)>(src1, step1, src2, step2, dst, step, sz));
873 874 875 876 877 878
}

static void or8u( const uchar* src1, size_t step1,
                  const uchar* src2, size_t step2,
                  uchar* dst, size_t step, Size sz, void* )
{
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879 880 881 882 883 884
#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviOr_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz))
        return;
#endif
    (vBinOp<uchar, OpOr<uchar>, IF_SIMD(VOr<uchar>)>(src1, step1, src2, step2, dst, step, sz));
885 886 887 888 889 890
}

static void xor8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
{
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891 892 893 894 895 896
#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step);
    if (0 <= ippicviXor_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz))
        return;
#endif
    (vBinOp<uchar, OpXor<uchar>, IF_SIMD(VXor<uchar>)>(src1, step1, src2, step2, dst, step, sz));
897
}
898 899 900 901 902

static void not8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
{
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903 904 905 906 907 908
#if (ARITHM_USE_IPP == 1)
    fixSteps(sz, sizeof(dst[0]), step1, step2, step); (void *)src2;
    if (0 <= ippicviNot_8u_C1R(src1, (int)step1, dst, (int)step, (IppiSize&)sz))
        return;
#endif
    (vBinOp<uchar, OpNot<uchar>, IF_SIMD(VNot<uchar>)>(src1, step1, src2, step2, dst, step, sz));
909
}
910

911 912 913
/****************************************************************************************\
*                                   logical operations                                   *
\****************************************************************************************/
914

915
void convertAndUnrollScalar( const Mat& sc, int buftype, uchar* scbuf, size_t blocksize )
916 917 918 919 920 921 922 923 924 925 926 927 928 929 930
{
    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];
}
931

932 933 934

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,
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Ilya Lavrenov 已提交
935 936
       OCL_OP_AND=9, OCL_OP_OR=10, OCL_OP_XOR=11, OCL_OP_NOT=12, OCL_OP_MIN=13, OCL_OP_MAX=14,
       OCL_OP_RDIV_SCALE=15 };
937

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Ilya Lavrenov 已提交
938 939
#ifdef HAVE_OPENCL

940 941
static const char* oclop2str[] = { "OP_ADD", "OP_SUB", "OP_RSUB", "OP_ABSDIFF",
    "OP_MUL", "OP_MUL_SCALE", "OP_DIV_SCALE", "OP_RECIP_SCALE",
I
Ilya Lavrenov 已提交
942
    "OP_ADDW", "OP_AND", "OP_OR", "OP_XOR", "OP_NOT", "OP_MIN", "OP_MAX", "OP_RDIV_SCALE", 0 };
943 944 945

static bool ocl_binary_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                          InputArray _mask, bool bitwise, int oclop, bool haveScalar )
946
{
947 948 949 950 951
    bool haveMask = !_mask.empty();
    int srctype = _src1.type();
    int srcdepth = CV_MAT_DEPTH(srctype);
    int cn = CV_MAT_CN(srctype);

952
    bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
953
    if( oclop < 0 || ((haveMask || haveScalar) && cn > 4) ||
I
Ilya Lavrenov 已提交
954
            (!doubleSupport && srcdepth == CV_64F && !bitwise))
955 956 957
        return false;

    char opts[1024];
I
Ilya Lavrenov 已提交
958
    int kercn = haveMask || haveScalar ? cn : ocl::predictOptimalVectorWidth(_src1, _src2, _dst);
959 960 961
    int scalarcn = kercn == 3 ? 4 : kercn;

    sprintf(opts, "-D %s%s -D %s -D dstT=%s%s -D dstT_C1=%s -D workST=%s -D cn=%d",
I
Ilya Lavrenov 已提交
962
            haveMask ? "MASK_" : "", haveScalar ? "UNARY_OP" : "BINARY_OP", oclop2str[oclop],
963
            bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, kercn)) :
I
Ilya Lavrenov 已提交
964
                ocl::typeToStr(CV_MAKETYPE(srcdepth, kercn)), doubleSupport ? " -D DOUBLE_SUPPORT" : "",
965
            bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, 1)) :
I
Ilya Lavrenov 已提交
966
                ocl::typeToStr(CV_MAKETYPE(srcdepth, 1)),
967
            bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, scalarcn)) :
I
Ilya Lavrenov 已提交
968
                ocl::typeToStr(CV_MAKETYPE(srcdepth, scalarcn)),
969
            kercn);
970 971

    ocl::Kernel k("KF", ocl::core::arithm_oclsrc, opts);
I
Ilya Lavrenov 已提交
972
    if (k.empty())
973 974
        return false;

I
Ilya Lavrenov 已提交
975 976 977
    UMat src1 = _src1.getUMat(), src2;
    UMat dst = _dst.getUMat(), mask = _mask.getUMat();

I
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978 979 980
    ocl::KernelArg src1arg = ocl::KernelArg::ReadOnlyNoSize(src1, cn, kercn);
    ocl::KernelArg dstarg = haveMask ? ocl::KernelArg::ReadWrite(dst, cn, kercn) :
                                       ocl::KernelArg::WriteOnly(dst, cn, kercn);
981 982 983 984
    ocl::KernelArg maskarg = ocl::KernelArg::ReadOnlyNoSize(mask, 1);

    if( haveScalar )
    {
985
        size_t esz = CV_ELEM_SIZE1(srctype)*scalarcn;
986 987 988 989 990 991 992 993
        double buf[4] = {0,0,0,0};

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

I
Ilya Lavrenov 已提交
994
        ocl::KernelArg scalararg = ocl::KernelArg(0, 0, 0, 0, buf, esz);
995 996 997 998 999 1000 1001 1002 1003

        if( !haveMask )
            k.args(src1arg, dstarg, scalararg);
        else
            k.args(src1arg, maskarg, dstarg, scalararg);
    }
    else
    {
        src2 = _src2.getUMat();
I
Ilya Lavrenov 已提交
1004
        ocl::KernelArg src2arg = ocl::KernelArg::ReadOnlyNoSize(src2, cn, kercn);
1005 1006 1007 1008 1009 1010 1011

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

I
Ilya Lavrenov 已提交
1012
    size_t globalsize[] = { src1.cols * cn / kercn, src1.rows };
1013 1014 1015
    return k.run(2, globalsize, 0, false);
}

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Ilya Lavrenov 已提交
1016
#endif
1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028

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();
I
Ilya Lavrenov 已提交
1029
#ifdef HAVE_OPENCL
1030
    bool use_opencl = (kind1 == _InputArray::UMAT || kind2 == _InputArray::UMAT) &&
I
Ilya Lavrenov 已提交
1031 1032
            dims1 <= 2 && dims2 <= 2;
#endif
1033 1034
    bool haveMask = !_mask.empty(), haveScalar = false;
    BinaryFunc func;
1035

1036
    if( dims1 <= 2 && dims2 <= 2 && kind1 == kind2 && sz1 == sz2 && type1 == type2 && !haveMask )
1037
    {
1038
        _dst.create(sz1, type1);
I
Ilya Lavrenov 已提交
1039 1040 1041
        CV_OCL_RUN(use_opencl,
                   ocl_binary_op(*psrc1, *psrc2, _dst, _mask, bitwise, oclop, false))

1042 1043 1044
        if( bitwise )
        {
            func = *tab;
1045
            cn = (int)CV_ELEM_SIZE(type1);
1046 1047
        }
        else
1048
            func = tab[depth1];
1049

1050
        Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat();
1051
        Size sz = getContinuousSize(src1, src2, dst);
1052
        size_t len = sz.width*(size_t)cn;
1053 1054 1055 1056 1057 1058
        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;
        }
1059
    }
1060

1061 1062 1063 1064
    if( oclop == OCL_OP_NOT )
        haveScalar = true;
    else if( (kind1 == _InputArray::MATX) + (kind2 == _InputArray::MATX) == 1 ||
        !psrc1->sameSize(*psrc2) || type1 != type2 )
1065
    {
1066 1067
        if( checkScalar(*psrc1, type2, kind1, kind2) )
        {
1068
            // src1 is a scalar; swap it with src2
1069 1070 1071 1072 1073 1074 1075
            swap(psrc1, psrc2);
            swap(type1, type2);
            swap(depth1, depth2);
            swap(cn, cn2);
            swap(sz1, sz2);
        }
        else if( !checkScalar(*psrc2, type1, kind2, kind1) )
1076 1077 1078 1079 1080
            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;
    }
1081 1082 1083 1084
    else
    {
        CV_Assert( psrc1->sameSize(*psrc2) && type1 == type2 );
    }
1085

1086
    size_t esz = CV_ELEM_SIZE(type1);
1087 1088
    size_t blocksize0 = (BLOCK_SIZE + esz-1)/esz;
    BinaryFunc copymask = 0;
1089
    bool reallocate = false;
1090

1091 1092
    if( haveMask )
    {
1093 1094
        int mtype = _mask.type();
        CV_Assert( (mtype == CV_8U || mtype == CV_8S) && _mask.sameSize(*psrc1));
1095
        copymask = getCopyMaskFunc(esz);
1096
        reallocate = !_dst.sameSize(*psrc1) || _dst.type() != type1;
1097
    }
1098

1099 1100
    AutoBuffer<uchar> _buf;
    uchar *scbuf = 0, *maskbuf = 0;
1101

1102
    _dst.createSameSize(*psrc1, type1);
1103
    // if this is mask operation and dst has been reallocated,
1104
    // we have to clear the destination
1105
    if( haveMask && reallocate )
1106 1107
        _dst.setTo(0.);

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Ilya Lavrenov 已提交
1108 1109 1110
    CV_OCL_RUN(use_opencl,
               ocl_binary_op(*psrc1, *psrc2, _dst, _mask, bitwise, oclop, haveScalar))

1111 1112 1113

    Mat src1 = psrc1->getMat(), src2 = psrc2->getMat();
    Mat dst = _dst.getMat(), mask = _mask.getMat();
1114

1115 1116 1117
    if( bitwise )
    {
        func = *tab;
1118
        cn = (int)esz;
1119 1120
    }
    else
1121
        func = tab[depth1];
1122

1123
    if( !haveScalar )
1124
    {
1125 1126
        const Mat* arrays[] = { &src1, &src2, &dst, &mask, 0 };
        uchar* ptrs[4];
1127

1128 1129
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = total;
1130

1131 1132
        if( blocksize*cn > INT_MAX )
            blocksize = INT_MAX/cn;
1133

1134 1135 1136 1137 1138 1139
        if( haveMask )
        {
            blocksize = std::min(blocksize, blocksize0);
            _buf.allocate(blocksize*esz);
            maskbuf = _buf;
        }
1140

1141
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1142
        {
1143
            for( size_t j = 0; j < total; j += blocksize )
1144
            {
1145
                int bsz = (int)MIN(total - j, blocksize);
1146

1147
                func( ptrs[0], 0, ptrs[1], 0, haveMask ? maskbuf : ptrs[2], 0, Size(bsz*cn, 1), 0 );
1148
                if( haveMask )
1149
                {
1150 1151
                    copymask( maskbuf, 0, ptrs[3], 0, ptrs[2], 0, Size(bsz, 1), &esz );
                    ptrs[3] += bsz;
1152
                }
1153

1154 1155
                bsz *= (int)esz;
                ptrs[0] += bsz; ptrs[1] += bsz; ptrs[2] += bsz;
1156 1157
            }
        }
1158 1159 1160 1161 1162
    }
    else
    {
        const Mat* arrays[] = { &src1, &dst, &mask, 0 };
        uchar* ptrs[3];
1163

1164 1165
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
1166

1167 1168 1169
        _buf.allocate(blocksize*(haveMask ? 2 : 1)*esz + 32);
        scbuf = _buf;
        maskbuf = alignPtr(scbuf + blocksize*esz, 16);
1170

1171
        convertAndUnrollScalar( src2, src1.type(), scbuf, blocksize);
1172

1173
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1174
        {
1175
            for( size_t j = 0; j < total; j += blocksize )
1176
            {
1177
                int bsz = (int)MIN(total - j, blocksize);
1178

1179
                func( ptrs[0], 0, scbuf, 0, haveMask ? maskbuf : ptrs[1], 0, Size(bsz*cn, 1), 0 );
1180
                if( haveMask )
1181
                {
1182 1183
                    copymask( maskbuf, 0, ptrs[2], 0, ptrs[1], 0, Size(bsz, 1), &esz );
                    ptrs[2] += bsz;
1184
                }
1185

1186 1187
                bsz *= (int)esz;
                ptrs[0] += bsz; ptrs[1] += bsz;
1188 1189 1190 1191
            }
        }
    }
}
1192

1193
static BinaryFunc* getMaxTab()
V
Vadim Pisarevsky 已提交
1194
{
1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205
    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;
}
1206

1207
static BinaryFunc* getMinTab()
1208
{
1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219
    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;
}
1220

V
Vadim Pisarevsky 已提交
1221
}
1222

1223
void cv::bitwise_and(InputArray a, InputArray b, OutputArray c, InputArray mask)
1224
{
A
Andrey Kamaev 已提交
1225
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(and8u);
1226
    binary_op(a, b, c, mask, &f, true, OCL_OP_AND);
1227 1228
}

1229
void cv::bitwise_or(InputArray a, InputArray b, OutputArray c, InputArray mask)
1230
{
A
Andrey Kamaev 已提交
1231
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(or8u);
1232
    binary_op(a, b, c, mask, &f, true, OCL_OP_OR);
1233 1234
}

1235
void cv::bitwise_xor(InputArray a, InputArray b, OutputArray c, InputArray mask)
1236
{
A
Andrey Kamaev 已提交
1237
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(xor8u);
1238
    binary_op(a, b, c, mask, &f, true, OCL_OP_XOR);
1239 1240
}

1241
void cv::bitwise_not(InputArray a, OutputArray c, InputArray mask)
1242
{
A
Andrey Kamaev 已提交
1243
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(not8u);
1244
    binary_op(a, a, c, mask, &f, true, OCL_OP_NOT);
1245 1246
}

1247
void cv::max( InputArray src1, InputArray src2, OutputArray dst )
1248
{
1249
    binary_op(src1, src2, dst, noArray(), getMaxTab(), false, OCL_OP_MAX );
1250 1251
}

1252
void cv::min( InputArray src1, InputArray src2, OutputArray dst )
1253
{
1254
    binary_op(src1, src2, dst, noArray(), getMinTab(), false, OCL_OP_MIN );
1255 1256
}

1257
void cv::max(const Mat& src1, const Mat& src2, Mat& dst)
1258
{
1259
    OutputArray _dst(dst);
1260
    binary_op(src1, src2, _dst, noArray(), getMaxTab(), false, OCL_OP_MAX );
1261 1262
}

1263 1264 1265
void cv::min(const Mat& src1, const Mat& src2, Mat& dst)
{
    OutputArray _dst(dst);
1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278
    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 );
1279
}
1280 1281


1282 1283 1284
/****************************************************************************************\
*                                      add/subtract                                      *
\****************************************************************************************/
1285

1286 1287
namespace cv
{
1288

1289 1290
static int actualScalarDepth(const double* data, int len)
{
1291 1292
    int i = 0, minval = INT_MAX, maxval = INT_MIN;
    for(; i < len; ++i)
1293
    {
1294 1295 1296 1297 1298
        int ival = cvRound(data[i]);
        if( ival != data[i] )
            break;
        minval = MIN(minval, ival);
        maxval = MAX(maxval, ival);
1299
    }
1300
    return i < len ? CV_64F :
A
Andrey Kamaev 已提交
1301 1302 1303 1304
        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 :
1305
        CV_32S;
1306 1307
}

I
Ilya Lavrenov 已提交
1308
#ifdef HAVE_OPENCL
1309 1310 1311 1312 1313

static bool ocl_arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                          InputArray _mask, int wtype,
                          void* usrdata, int oclop,
                          bool haveScalar )
1314
{
I
Ilya Lavrenov 已提交
1315
    bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
1316
    int type1 = _src1.type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
1317
    bool haveMask = !_mask.empty();
1318

1319
    if ( (haveMask || haveScalar) && cn > 4 )
1320 1321
        return false;

1322
    int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), wdepth = std::max(CV_32S, CV_MAT_DEPTH(wtype));
I
Ilya Lavrenov 已提交
1323 1324 1325
    if (!doubleSupport)
        wdepth = std::min(wdepth, CV_32F);

1326
    wtype = CV_MAKETYPE(wdepth, cn);
1327
    int type2 = haveScalar ? wtype : _src2.type(), depth2 = CV_MAT_DEPTH(type2);
I
Ilya Lavrenov 已提交
1328 1329
    if (!doubleSupport && (depth2 == CV_64F || depth1 == CV_64F))
        return false;
1330

I
Ilya Lavrenov 已提交
1331
    int kercn = haveMask || haveScalar ? cn : ocl::predictOptimalVectorWidth(_src1, _src2, _dst);
1332
    int scalarcn = kercn == 3 ? 4 : kercn;
1333

I
Ilya Lavrenov 已提交
1334
    char cvtstr[4][32], opts[1024];
1335
    sprintf(opts, "-D %s%s -D %s -D srcT1=%s -D srcT1_C1=%s -D srcT2=%s -D srcT2_C1=%s "
I
Ilya Lavrenov 已提交
1336
            "-D dstT=%s -D dstT_C1=%s -D workT=%s -D workST=%s -D scaleT=%s -D wdepth=%d -D convertToWT1=%s "
1337
            "-D convertToWT2=%s -D convertToDT=%s%s -D cn=%d",
1338 1339
            (haveMask ? "MASK_" : ""), (haveScalar ? "UNARY_OP" : "BINARY_OP"),
            oclop2str[oclop], ocl::typeToStr(CV_MAKETYPE(depth1, kercn)),
1340 1341 1342
            ocl::typeToStr(depth1), ocl::typeToStr(CV_MAKETYPE(depth2, kercn)),
            ocl::typeToStr(depth2), ocl::typeToStr(CV_MAKETYPE(ddepth, kercn)),
            ocl::typeToStr(ddepth), ocl::typeToStr(CV_MAKETYPE(wdepth, kercn)),
1343
            ocl::typeToStr(CV_MAKETYPE(wdepth, scalarcn)),
1344
            ocl::typeToStr(wdepth), wdepth,
1345 1346
            ocl::convertTypeStr(depth1, wdepth, kercn, cvtstr[0]),
            ocl::convertTypeStr(depth2, wdepth, kercn, cvtstr[1]),
I
Ilya Lavrenov 已提交
1347
            ocl::convertTypeStr(wdepth, ddepth, kercn, cvtstr[2]),
1348
            doubleSupport ? " -D DOUBLE_SUPPORT" : "", kercn);
1349

I
Ilya Lavrenov 已提交
1350
    size_t usrdata_esz = CV_ELEM_SIZE(wdepth);
1351 1352 1353 1354
    const uchar* usrdata_p = (const uchar*)usrdata;
    const double* usrdata_d = (const double*)usrdata;
    float usrdata_f[3];
    int i, n = oclop == OCL_OP_MUL_SCALE || oclop == OCL_OP_DIV_SCALE ||
I
Ilya Lavrenov 已提交
1355
        oclop == OCL_OP_RDIV_SCALE || oclop == OCL_OP_RECIP_SCALE ? 1 : oclop == OCL_OP_ADDW ? 3 : 0;
1356 1357 1358 1359 1360 1361 1362 1363
    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);
1364
    if (k.empty())
1365 1366
        return false;

I
Ilya Lavrenov 已提交
1367 1368 1369
    UMat src1 = _src1.getUMat(), src2;
    UMat dst = _dst.getUMat(), mask = _mask.getUMat();

I
Ilya Lavrenov 已提交
1370 1371 1372
    ocl::KernelArg src1arg = ocl::KernelArg::ReadOnlyNoSize(src1, cn, kercn);
    ocl::KernelArg dstarg = haveMask ? ocl::KernelArg::ReadWrite(dst, cn, kercn) :
                                       ocl::KernelArg::WriteOnly(dst, cn, kercn);
1373 1374 1375 1376
    ocl::KernelArg maskarg = ocl::KernelArg::ReadOnlyNoSize(mask, 1);

    if( haveScalar )
    {
1377
        size_t esz = CV_ELEM_SIZE1(wtype)*scalarcn;
1378 1379 1380 1381 1382
        double buf[4]={0,0,0,0};
        Mat src2sc = _src2.getMat();

        if( !src2sc.empty() )
            convertAndUnrollScalar(src2sc, wtype, (uchar*)buf, 1);
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Ilya Lavrenov 已提交
1383
        ocl::KernelArg scalararg = ocl::KernelArg(0, 0, 0, 0, buf, esz);
1384 1385

        if( !haveMask )
I
Ilya Lavrenov 已提交
1386 1387 1388 1389 1390
        {
            if(n == 0)
                k.args(src1arg, dstarg, scalararg);
            else if(n == 1)
                k.args(src1arg, dstarg, scalararg,
I
Ilya Lavrenov 已提交
1391
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p, usrdata_esz));
I
Ilya Lavrenov 已提交
1392 1393 1394
            else
                CV_Error(Error::StsNotImplemented, "unsupported number of extra parameters");
        }
1395 1396 1397 1398 1399 1400
        else
            k.args(src1arg, maskarg, dstarg, scalararg);
    }
    else
    {
        src2 = _src2.getUMat();
I
Ilya Lavrenov 已提交
1401
        ocl::KernelArg src2arg = ocl::KernelArg::ReadOnlyNoSize(src2, cn, kercn);
1402 1403 1404

        if( !haveMask )
        {
1405
            if (n == 0)
1406
                k.args(src1arg, src2arg, dstarg);
1407
            else if (n == 1)
1408
                k.args(src1arg, src2arg, dstarg,
I
Ilya Lavrenov 已提交
1409
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p, usrdata_esz));
1410
            else if (n == 3)
1411
                k.args(src1arg, src2arg, dstarg,
I
Ilya Lavrenov 已提交
1412 1413 1414
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p, usrdata_esz),
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p + usrdata_esz, usrdata_esz),
                       ocl::KernelArg(0, 0, 0, 0, usrdata_p + usrdata_esz*2, usrdata_esz));
1415 1416 1417 1418 1419 1420 1421
            else
                CV_Error(Error::StsNotImplemented, "unsupported number of extra parameters");
        }
        else
            k.args(src1arg, src2arg, maskarg, dstarg);
    }

I
Ilya Lavrenov 已提交
1422
    size_t globalsize[] = { src1.cols * cn / kercn, src1.rows };
1423
    return k.run(2, globalsize, NULL, false);
1424 1425
}

I
Ilya Lavrenov 已提交
1426
#endif
1427 1428 1429 1430 1431 1432 1433 1434 1435 1436 1437 1438 1439 1440

static void arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                      InputArray _mask, int dtype, BinaryFunc* tab, bool muldiv=false,
                      void* usrdata=0, int oclop=-1 )
{
    const _InputArray *psrc1 = &_src1, *psrc2 = &_src2;
    int kind1 = psrc1->kind(), kind2 = psrc2->kind();
    bool haveMask = !_mask.empty();
    bool reallocate = false;
    int type1 = psrc1->type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
    int type2 = psrc2->type(), depth2 = CV_MAT_DEPTH(type2), cn2 = CV_MAT_CN(type2);
    int wtype, dims1 = psrc1->dims(), dims2 = psrc2->dims();
    Size sz1 = dims1 <= 2 ? psrc1->size() : Size();
    Size sz2 = dims2 <= 2 ? psrc2->size() : Size();
I
Ilya Lavrenov 已提交
1441 1442 1443
#ifdef HAVE_OPENCL
    bool use_opencl = _dst.isUMat() && dims1 <= 2 && dims2 <= 2;
#endif
1444 1445 1446 1447 1448 1449
    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
1450
        ((src1Scalar && src2Scalar) || (!src1Scalar && !src2Scalar)) )
V
Vadim Pisarevsky 已提交
1451
    {
1452
        _dst.createSameSize(*psrc1, type1);
I
Ilya Lavrenov 已提交
1453
        CV_OCL_RUN(use_opencl,
1454 1455 1456
            ocl_arithm_op(*psrc1, *psrc2, _dst, _mask,
                          (!usrdata ? type1 : std::max(depth1, CV_32F)),
                          usrdata, oclop, false))
1457

1458
        Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat();
1459
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
1460
        tab[depth1](src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, usrdata);
V
Vadim Pisarevsky 已提交
1461 1462
        return;
    }
1463

1464
    bool haveScalar = false, swapped12 = false;
1465 1466

    if( dims1 != dims2 || sz1 != sz2 || cn != cn2 ||
1467 1468
        (kind1 == _InputArray::MATX && (sz1 == Size(1,4) || sz1 == Size(1,1))) ||
        (kind2 == _InputArray::MATX && (sz2 == Size(1,4) || sz2 == Size(1,1))) )
1469
    {
1470
        if( checkScalar(*psrc1, type2, kind1, kind2) )
1471 1472
        {
            // src1 is a scalar; swap it with src2
1473 1474 1475 1476 1477 1478
            swap(psrc1, psrc2);
            swap(sz1, sz2);
            swap(type1, type2);
            swap(depth1, depth2);
            swap(cn, cn2);
            swap(dims1, dims2);
1479
            swapped12 = true;
1480 1481
            if( oclop == OCL_OP_SUB )
                oclop = OCL_OP_RSUB;
I
Ilya Lavrenov 已提交
1482 1483
            if ( oclop == OCL_OP_DIV_SCALE )
                oclop = OCL_OP_RDIV_SCALE;
1484
        }
1485
        else if( !checkScalar(*psrc2, type1, kind2, kind1) )
1486
            CV_Error( CV_StsUnmatchedSizes,
1487 1488
                     "The operation is neither 'array op array' "
                     "(where arrays have the same size and the same number of channels), "
1489 1490
                     "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
1491
        CV_Assert(type2 == CV_64F && (sz2.height == 1 || sz2.height == 4));
A
Andrey Kamaev 已提交
1492

1493 1494
        if (!muldiv)
        {
1495 1496 1497
            Mat sc = psrc2->getMat();
            depth2 = actualScalarDepth(sc.ptr<double>(), cn);
            if( depth2 == CV_64F && (depth1 < CV_32S || depth1 == CV_32F) )
1498 1499
                depth2 = CV_32F;
        }
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Andrey Kamaev 已提交
1500
        else
1501
            depth2 = CV_64F;
1502
    }
1503

1504 1505 1506 1507 1508 1509
    if( dtype < 0 )
    {
        if( _dst.fixedType() )
            dtype = _dst.type();
        else
        {
1510
            if( !haveScalar && type1 != type2 )
1511 1512 1513
                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");
1514
            dtype = type1;
1515 1516 1517
        }
    }
    dtype = CV_MAT_DEPTH(dtype);
1518

1519 1520 1521 1522 1523 1524 1525
    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);
1526

1527 1528 1529 1530 1531 1532 1533 1534 1535 1536 1537
        // 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);
    }
1538

1539 1540
    dtype = CV_MAKETYPE(dtype, cn);
    wtype = CV_MAKETYPE(wtype, cn);
1541

1542 1543
    if( haveMask )
    {
1544 1545 1546
        int mtype = _mask.type();
        CV_Assert( (mtype == CV_8UC1 || mtype == CV_8SC1) && _mask.sameSize(*psrc1) );
        reallocate = !_dst.sameSize(*psrc1) || _dst.type() != dtype;
1547
    }
1548

1549 1550 1551
    _dst.createSameSize(*psrc1, dtype);
    if( reallocate )
        _dst.setTo(0.);
1552

I
Ilya Lavrenov 已提交
1553 1554 1555
    CV_OCL_RUN(use_opencl,
               ocl_arithm_op(*psrc1, *psrc2, _dst, _mask, wtype,
               usrdata, oclop, haveScalar))
1556

1557 1558 1559 1560 1561 1562 1563 1564 1565
    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();
1566

1567 1568 1569 1570 1571 1572
    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);
1573
    BinaryFunc func = tab[CV_MAT_DEPTH(wtype)];
1574

1575 1576 1577 1578
    if( !haveScalar )
    {
        const Mat* arrays[] = { &src1, &src2, &dst, &mask, 0 };
        uchar* ptrs[4];
1579

1580 1581
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = total;
1582

1583 1584 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596
        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;
1597

1598
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1599
        {
1600
            for( size_t j = 0; j < total; j += blocksize )
1601
            {
1602
                int bsz = (int)MIN(total - j, blocksize);
1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616 1617
                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;
                }
1618

1619 1620 1621 1622 1623 1624 1625 1626 1627 1628 1629 1630 1631 1632 1633 1634 1635 1636 1637 1638
                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;
1639 1640
            }
        }
1641 1642 1643 1644 1645
    }
    else
    {
        const Mat* arrays[] = { &src1, &dst, &mask, 0 };
        uchar* ptrs[3];
1646

1647 1648
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
1649

1650 1651 1652 1653 1654 1655 1656 1657 1658 1659
        _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;
1660

1661
        convertAndUnrollScalar( src2, wtype, buf2, blocksize);
1662

1663
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1664
        {
1665 1666
            for( size_t j = 0; j < total; j += blocksize )
            {
1667
                int bsz = (int)MIN(total - j, blocksize);
1668 1669 1670 1671
                Size bszn(bsz*cn, 1);
                const uchar *sptr1 = ptrs[0];
                const uchar* sptr2 = buf2;
                uchar* dptr = ptrs[1];
1672

1673 1674 1675 1676 1677
                if( cvtsrc1 )
                {
                    cvtsrc1( sptr1, 0, 0, 0, buf1, 0, bszn, 0 );
                    sptr1 = buf1;
                }
1678

1679 1680
                if( swapped12 )
                    std::swap(sptr1, sptr2);
1681

1682 1683 1684 1685 1686 1687 1688 1689 1690 1691 1692 1693 1694 1695 1696 1697 1698 1699 1700 1701 1702
                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;
            }
1703 1704 1705
        }
    }
}
1706

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

1718 1719 1720 1721
    return addTab;
}

static BinaryFunc* getSubTab()
1722
{
1723 1724 1725 1726 1727 1728 1729 1730 1731 1732 1733
    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;
}
1734

1735
static BinaryFunc* getAbsDiffTab()
1736
{
1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747
    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;
}
1748 1749

}
1750

1751 1752
void cv::add( InputArray src1, InputArray src2, OutputArray dst,
          InputArray mask, int dtype )
1753
{
1754
    arithm_op(src1, src2, dst, mask, dtype, getAddTab(), false, 0, OCL_OP_ADD );
1755 1756
}

1757 1758
void cv::subtract( InputArray src1, InputArray src2, OutputArray dst,
               InputArray mask, int dtype )
1759
{
A
Andrey Kamaev 已提交
1760
#ifdef HAVE_TEGRA_OPTIMIZATION
1761
    if (mask.empty() && src1.depth() == CV_8U && src2.depth() == CV_8U)
1762
    {
1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786
        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;
            }
        }
1787
    }
A
Andrey Kamaev 已提交
1788
#endif
1789
    arithm_op(src1, src2, dst, mask, dtype, getSubTab(), false, 0, OCL_OP_SUB );
1790 1791
}

1792
void cv::absdiff( InputArray src1, InputArray src2, OutputArray dst )
1793
{
1794
    arithm_op(src1, src2, dst, noArray(), -1, getAbsDiffTab(), false, 0, OCL_OP_ABSDIFF);
1795
}
1796 1797 1798 1799 1800

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

1801 1802 1803
namespace cv
{

1804
template<typename T, typename WT> static void
1805 1806
mul_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, WT scale )
1807
{
1808 1809 1810
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1811

1812
    if( scale == (WT)1. )
1813
    {
1814
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1815
        {
V
Victoria Zhislina 已提交
1816
            int i=0;
1817
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1818
            for(; i <= size.width - 4; i += 4 )
1819
            {
1820 1821 1822 1823 1824 1825
                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;
1826 1827 1828

                t0 = saturate_cast<T>(src1[i+2] * src2[i+2]);
                t1 = saturate_cast<T>(src1[i+3] * src2[i+3]);
1829 1830
                dst[i+2] = t0;
                dst[i+3] = t1;
1831
            }
V
Victoria Zhislina 已提交
1832
            #endif
1833 1834 1835 1836 1837 1838
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(src1[i] * src2[i]);
        }
    }
    else
    {
1839
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1840
        {
V
Victoria Zhislina 已提交
1841
            int i = 0;
1842
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1843
            for(; i <= size.width - 4; i += 4 )
1844 1845 1846 1847 1848 1849 1850 1851 1852
            {
                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
1853
            #endif
1854 1855 1856 1857 1858 1859 1860
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(scale*(WT)src1[i]*src2[i]);
        }
    }
}

template<typename T> static void
1861 1862
div_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, double scale )
1863
{
1864 1865 1866
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1867

1868
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1869 1870
    {
        int i = 0;
1871
        #if CV_ENABLE_UNROLLED
1872 1873 1874 1875 1876 1877 1878 1879 1880
        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;
1881

1882 1883 1884 1885
                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));
1886

1887 1888 1889 1890 1891 1892 1893 1894 1895
                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;
1896

1897 1898 1899 1900
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1901
        #endif
1902 1903 1904 1905 1906 1907
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(src1[i]*scale/src2[i]) : 0;
    }
}

template<typename T> static void
1908 1909
recip_( const T*, size_t, const T* src2, size_t step2,
        T* dst, size_t step, Size size, double scale )
1910
{
1911 1912
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1913

1914
    for( ; size.height--; src2 += step2, dst += step )
1915 1916
    {
        int i = 0;
1917
        #if CV_ENABLE_UNROLLED
1918 1919 1920 1921 1922 1923 1924 1925 1926
        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;
1927

1928 1929 1930 1931
                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);
1932

1933 1934 1935 1936 1937 1938 1939 1940 1941
                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;
1942

1943 1944 1945 1946
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1947
        #endif
1948 1949 1950 1951
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(scale/src2[i]) : 0;
    }
}
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
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);
}
1983

1984 1985 1986 1987 1988
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);
}
1989

1990 1991 1992 1993 1994
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);
}
1995

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 2053 2054 2055 2056 2057 2058 2059 2060 2061 2062 2063
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);
}
2064

2065 2066 2067 2068 2069 2070 2071 2072 2073 2074 2075 2076 2077 2078 2079 2080 2081
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);
}
2082 2083


2084
static BinaryFunc* getMulTab()
2085
{
2086 2087 2088 2089 2090 2091 2092 2093 2094
    static BinaryFunc mulTab[] =
    {
        (BinaryFunc)mul8u, (BinaryFunc)mul8s, (BinaryFunc)mul16u,
        (BinaryFunc)mul16s, (BinaryFunc)mul32s, (BinaryFunc)mul32f,
        (BinaryFunc)mul64f, 0
    };

    return mulTab;
}
2095

2096
static BinaryFunc* getDivTab()
2097
{
2098 2099 2100 2101 2102 2103
    static BinaryFunc divTab[] =
    {
        (BinaryFunc)div8u, (BinaryFunc)div8s, (BinaryFunc)div16u,
        (BinaryFunc)div16s, (BinaryFunc)div32s, (BinaryFunc)div32f,
        (BinaryFunc)div64f, 0
    };
2104

2105 2106 2107 2108
    return divTab;
}

static BinaryFunc* getRecipTab()
2109
{
2110 2111 2112 2113 2114 2115
    static BinaryFunc recipTab[] =
    {
        (BinaryFunc)recip8u, (BinaryFunc)recip8s, (BinaryFunc)recip16u,
        (BinaryFunc)recip16s, (BinaryFunc)recip32s, (BinaryFunc)recip32f,
        (BinaryFunc)recip64f, 0
    };
2116

2117 2118
    return recipTab;
}
2119

2120
}
2121

2122
void cv::multiply(InputArray src1, InputArray src2,
2123
                  OutputArray dst, double scale, int dtype)
2124
{
2125
    arithm_op(src1, src2, dst, noArray(), dtype, getMulTab(),
I
Ilya Lavrenov 已提交
2126
              true, &scale, std::abs(scale - 1.0) < DBL_EPSILON ? OCL_OP_MUL : OCL_OP_MUL_SCALE);
2127
}
2128

2129
void cv::divide(InputArray src1, InputArray src2,
2130 2131
                OutputArray dst, double scale, int dtype)
{
2132
    arithm_op(src1, src2, dst, noArray(), dtype, getDivTab(), true, &scale, OCL_OP_DIV_SCALE);
2133 2134
}

2135
void cv::divide(double scale, InputArray src2,
2136 2137
                OutputArray dst, int dtype)
{
2138
    arithm_op(src2, src2, dst, noArray(), dtype, getRecipTab(), true, &scale, OCL_OP_RECIP_SCALE);
2139 2140
}

2141 2142 2143 2144
/****************************************************************************************\
*                                      addWeighted                                       *
\****************************************************************************************/

2145 2146 2147
namespace cv
{

2148
template<typename T, typename WT> static void
2149 2150 2151 2152 2153 2154 2155 2156 2157 2158
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 )
2159
    {
2160
        int x = 0;
2161
        #if CV_ENABLE_UNROLLED
2162
        for( ; x <= size.width - 4; x += 4 )
2163
        {
2164 2165 2166
            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;
2167

2168 2169 2170
            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;
2171
        }
V
Victoria Zhislina 已提交
2172
        #endif
2173 2174
        for( ; x < size.width; x++ )
            dst[x] = saturate_cast<T>(src1[x]*alpha + src2[x]*beta + gamma);
2175 2176 2177 2178 2179
    }
}


static void
2180 2181 2182 2183 2184 2185 2186
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];
2187

2188
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2189
    {
2190
        int x = 0;
2191

2192 2193
#if CV_SSE2
        if( USE_SSE2 )
2194
        {
2195 2196
            __m128 a4 = _mm_set1_ps(alpha), b4 = _mm_set1_ps(beta), g4 = _mm_set1_ps(gamma);
            __m128i z = _mm_setzero_si128();
2197

2198
            for( ; x <= size.width - 8; x += 8 )
2199
            {
2200 2201
                __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);
2202

2203 2204 2205 2206
                __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));
2207

2208 2209 2210
                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);
2211

2212 2213
                u = _mm_packs_epi32(_mm_cvtps_epi32(u0), _mm_cvtps_epi32(u1));
                u = _mm_packus_epi16(u, u);
2214

2215
                _mm_storel_epi64((__m128i*)(dst + x), u);
2216 2217
            }
        }
2218
#endif
2219
        #if CV_ENABLE_UNROLLED
2220
        for( ; x <= size.width - 4; x += 4 )
2221
        {
2222 2223 2224
            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;
2225

2226 2227
            dst[x] = saturate_cast<uchar>(t0);
            dst[x+1] = saturate_cast<uchar>(t1);
2228

2229 2230
            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;
2231

2232 2233 2234
            dst[x+2] = saturate_cast<uchar>(t0);
            dst[x+3] = saturate_cast<uchar>(t1);
        }
V
Victoria Zhislina 已提交
2235
        #endif
2236

2237 2238 2239 2240
        for( ; x < size.width; x++ )
        {
            float t0 = CV_8TO32F(src1[x])*alpha + CV_8TO32F(src2[x])*beta + gamma;
            dst[x] = saturate_cast<uchar>(t0);
2241 2242 2243 2244
        }
    }
}

2245 2246
static void addWeighted8s( const schar* src1, size_t step1, const schar* src2, size_t step2,
                           schar* dst, size_t step, Size sz, void* scalars )
2247
{
2248
    addWeighted_<schar, float>(src1, step1, src2, step2, dst, step, sz, scalars);
2249 2250
}

2251 2252
static void addWeighted16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                            ushort* dst, size_t step, Size sz, void* scalars )
2253
{
2254 2255
    addWeighted_<ushort, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2256

2257 2258
static void addWeighted16s( const short* src1, size_t step1, const short* src2, size_t step2,
                            short* dst, size_t step, Size sz, void* scalars )
2259
{
2260 2261
    addWeighted_<short, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2262

2263 2264
static void addWeighted32s( const int* src1, size_t step1, const int* src2, size_t step2,
                            int* dst, size_t step, Size sz, void* scalars )
2265
{
2266
    addWeighted_<int, double>(src1, step1, src2, step2, dst, step, sz, scalars);
2267 2268
}

2269 2270
static void addWeighted32f( const float* src1, size_t step1, const float* src2, size_t step2,
                            float* dst, size_t step, Size sz, void* scalars )
2271
{
2272 2273
    addWeighted_<float, double>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2274

2275 2276 2277 2278 2279
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
2280

2281
static BinaryFunc* getAddWeightedTab()
2282
{
2283 2284 2285 2286 2287 2288 2289 2290 2291
    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;
}
2292

2293
}
2294

2295
void cv::addWeighted( InputArray src1, double alpha, InputArray src2,
2296 2297 2298
                      double beta, double gamma, OutputArray dst, int dtype )
{
    double scalars[] = {alpha, beta, gamma};
2299
    arithm_op(src1, src2, dst, noArray(), dtype, getAddWeightedTab(), true, scalars, OCL_OP_ADDW);
2300 2301
}

2302

2303
/****************************************************************************************\
2304
*                                          compare                                       *
2305 2306
\****************************************************************************************/

2307
namespace cv
2308 2309
{

2310 2311 2312
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)
2313
{
2314 2315 2316
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    if( code == CMP_GE || code == CMP_LT )
2317
    {
2318 2319 2320
        std::swap(src1, src2);
        std::swap(step1, step2);
        code = code == CMP_GE ? CMP_LE : CMP_GT;
2321
    }
2322

2323
    if( code == CMP_GT || code == CMP_LE )
2324
    {
2325 2326 2327 2328
        int m = code == CMP_GT ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2329
            #if CV_ENABLE_UNROLLED
2330 2331 2332 2333 2334 2335 2336 2337 2338 2339
            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
2340
            #endif
2341 2342
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2343
               }
2344
    }
2345
    else if( code == CMP_EQ || code == CMP_NE )
2346
    {
2347 2348 2349 2350
        int m = code == CMP_EQ ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2351
            #if CV_ENABLE_UNROLLED
2352 2353 2354 2355 2356 2357 2358 2359 2360 2361
            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;
            }
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2362
            #endif
2363 2364 2365
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
2366
    }
2367
}
2368

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2369 2370 2371 2372 2373 2374 2375 2376 2377 2378 2379
#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
2380

2381 2382
static void cmp8u(const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2383
{
K
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2384 2385 2386 2387 2388
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  >= 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
V
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2389
        if (0 <= ippicviCompare_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op))
K
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2390 2391 2392
            return;
    }
#endif
2393
  //vz optimized  cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2394
    int code = *(int*)_cmpop;
2395 2396 2397 2398 2399 2400 2401 2402 2403 2404 2405 2406 2407 2408 2409
    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;
2410 2411
            #if CV_SSE2
            if( USE_SSE2 ){
2412 2413
                __m128i m128 = code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
                __m128i c128 = _mm_set1_epi8 (-128);
2414 2415 2416 2417 2418 2419 2420 2421 2422 2423 2424 2425 2426
                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);

                }
            }
2427 2428
           #endif

2429
            for( ; x < size.width; x++ ){
2430
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2431
            }
2432 2433 2434 2435 2436
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2437
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2438 2439
        {
            int x = 0;
2440 2441
            #if CV_SSE2
            if( USE_SSE2 ){
2442
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
2443 2444 2445 2446 2447 2448 2449 2450
                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);
                }
            }
2451 2452 2453 2454 2455
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2456 2457
}

2458 2459
static void cmp8s(const schar* src1, size_t step1, const schar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2460
{
2461
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2462 2463
}

2464 2465
static void cmp16u(const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2466
{
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2467 2468 2469 2470 2471
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  >= 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
V
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2472
        if (0 <= ippicviCompare_16u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op))
K
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2473 2474 2475
            return;
    }
#endif
2476
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2477 2478
}

2479 2480
static void cmp16s(const short* src1, size_t step1, const short* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2481
{
K
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2482 2483 2484 2485 2486
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  > 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
V
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2487
        if (0 <= ippicviCompare_16s_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op))
K
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2488 2489 2490
            return;
    }
#endif
2491 2492
   //vz optimized cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);

2493
    int code = *(int*)_cmpop;
2494 2495 2496 2497 2498 2499 2500 2501 2502 2503 2504 2505 2506 2507 2508
    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;
2509 2510
            #if CV_SSE2
            if( USE_SSE2){//
2511
                __m128i m128 =  code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2512 2513 2514 2515 2516 2517 2518 2519 2520 2521 2522 2523 2524 2525 2526 2527 2528 2529 2530 2531 2532 2533
                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;
                }
            }
2534 2535
           #endif

2536
            for( ; x < size.width; x++ ){
2537
                 dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2538
            }
2539 2540 2541 2542 2543
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2544
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2545 2546
        {
            int x = 0;
2547 2548
            #if CV_SSE2
            if( USE_SSE2 ){
2549
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2550 2551 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 2562 2563 2564 2565 2566 2567 2568 2569 2570 2571
                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;
                }
            }
2572 2573 2574 2575 2576
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2577 2578
}

2579 2580 2581 2582 2583
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);
}
2584

2585 2586
static void cmp32f(const float* src1, size_t step1, const float* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2587
{
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2588 2589 2590 2591 2592
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  >= 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
V
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2593
        if (0 <= ippicviCompare_32f_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op))
K
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2594 2595 2596
            return;
    }
#endif
2597 2598
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
}
2599

2600 2601
static void cmp64f(const double* src1, size_t step1, const double* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2602
{
2603
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2604 2605
}

2606
static BinaryFunc getCmpFunc(int depth)
2607
{
2608 2609 2610 2611 2612 2613 2614 2615
    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
    };
2616

2617 2618
    return cmpTab[depth];
}
2619

2620
static double getMinVal(int depth)
2621
{
2622 2623 2624
    static const double tab[] = {0, -128, 0, -32768, INT_MIN, -FLT_MAX, -DBL_MAX, 0};
    return tab[depth];
}
2625

2626
static double getMaxVal(int depth)
2627
{
2628 2629 2630
    static const double tab[] = {255, 127, 65535, 32767, INT_MAX, FLT_MAX, DBL_MAX, 0};
    return tab[depth];
}
2631

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2632 2633
#ifdef HAVE_OPENCL

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2634
static bool ocl_compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op, bool haveScalar)
I
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2635
{
A
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2636 2637
    const ocl::Device& dev = ocl::Device::getDefault();
    bool doubleSupport = dev.doubleFPConfig() > 0;
I
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2638 2639
    int type1 = _src1.type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1),
            type2 = _src2.type(), depth2 = CV_MAT_DEPTH(type2);
A
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2640

2641 2642 2643 2644
    if (!doubleSupport && depth1 == CV_64F)
        return false;

    if (!haveScalar && (!_src1.sameSize(_src2) || type1 != type2))
A
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2645
            return false;
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2646

A
Alexander Alekhin 已提交
2647
    int kercn = haveScalar ? cn : ocl::predictOptimalVectorWidth(_src1, _src2, _dst);
A
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2648
    // Workaround for bug with "?:" operator in AMD OpenCL compiler
I
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2649
    if (depth1 >= CV_16U)
A
Alexander Alekhin 已提交
2650 2651
        kercn = 1;

A
Alexander Alekhin 已提交
2652
    int scalarcn = kercn == 3 ? 4 : kercn;
I
Ilya Lavrenov 已提交
2653
    const char * const operationMap[] = { "==", ">", ">=", "<", "<=", "!=" };
I
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2654 2655
    char cvt[40];

I
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2656 2657 2658 2659 2660 2661 2662 2663 2664 2665 2666 2667 2668
    String opts = format("-D %s -D srcT1=%s -D dstT=%s -D workT=srcT1 -D cn=%d"
                         " -D convertToDT=%s -D OP_CMP -D CMP_OPERATOR=%s -D srcT1_C1=%s"
                         " -D srcT2_C1=%s -D dstT_C1=%s -D workST=%s%s",
                         haveScalar ? "UNARY_OP" : "BINARY_OP",
                         ocl::typeToStr(CV_MAKE_TYPE(depth1, kercn)),
                         ocl::typeToStr(CV_8UC(kercn)), kercn,
                         ocl::convertTypeStr(depth1, CV_8U, kercn, cvt),
                         operationMap[op], ocl::typeToStr(depth1),
                         ocl::typeToStr(depth1), ocl::typeToStr(CV_8U),
                         ocl::typeToStr(CV_MAKE_TYPE(depth1, scalarcn)),
                         doubleSupport ? " -D DOUBLE_SUPPORT" : "");

    ocl::Kernel k("KF", ocl::core::arithm_oclsrc, opts);
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2669 2670 2671
    if (k.empty())
        return false;

A
Alexander Alekhin 已提交
2672
    UMat src1 = _src1.getUMat();
I
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2673 2674 2675
    Size size = src1.size();
    _dst.create(size, CV_8UC(cn));
    UMat dst = _dst.getUMat();
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Ilya Lavrenov 已提交
2676

A
Alexander Alekhin 已提交
2677 2678
    if (haveScalar)
    {
I
Ilya Lavrenov 已提交
2679 2680 2681 2682 2683 2684 2685 2686 2687 2688 2689 2690
        size_t esz = CV_ELEM_SIZE1(type1) * scalarcn;
        double buf[4] = { 0, 0, 0, 0 };
        Mat src2 = _src2.getMat();

        if( depth1 > CV_32S )
            convertAndUnrollScalar( src2, depth1, (uchar *)buf, kercn );
        else
        {
            double fval = 0;
            getConvertFunc(depth2, CV_64F)(src2.data, 0, 0, 0, (uchar *)&fval, 0, Size(1, 1), 0);
            if( fval < getMinVal(depth1) )
                return dst.setTo(Scalar::all(op == CMP_GT || op == CMP_GE || op == CMP_NE ? 255 : 0)), true;
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2691

I
Ilya Lavrenov 已提交
2692 2693 2694 2695 2696 2697 2698 2699 2700 2701 2702 2703 2704 2705 2706
            if( fval > getMaxVal(depth1) )
                return dst.setTo(Scalar::all(op == CMP_LT || op == CMP_LE || op == CMP_NE ? 255 : 0)), true;

            int ival = cvRound(fval);
            if( fval != ival )
            {
                if( op == CMP_LT || op == CMP_GE )
                    ival = cvCeil(fval);
                else if( op == CMP_LE || op == CMP_GT )
                    ival = cvFloor(fval);
                else
                    return dst.setTo(Scalar::all(op == CMP_NE ? 255 : 0)), true;
            }
            convertAndUnrollScalar(Mat(1, 1, CV_32S, &ival), depth1, (uchar *)buf, kercn);
        }
A
Alexander Alekhin 已提交
2707 2708 2709 2710

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

        k.args(ocl::KernelArg::ReadOnlyNoSize(src1, cn, kercn),
I
Ilya Lavrenov 已提交
2711
               ocl::KernelArg::WriteOnly(dst, cn, kercn), scalararg);
A
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2712 2713 2714 2715 2716 2717 2718 2719 2720
    }
    else
    {
        UMat src2 = _src2.getUMat();

        k.args(ocl::KernelArg::ReadOnlyNoSize(src1),
               ocl::KernelArg::ReadOnlyNoSize(src2),
               ocl::KernelArg::WriteOnly(dst, cn, kercn));
    }
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Ilya Lavrenov 已提交
2721

I
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2722
    size_t globalsize[2] = { dst.cols * cn / kercn, dst.rows };
I
Ilya Lavrenov 已提交
2723 2724 2725
    return k.run(2, globalsize, NULL, false);
}

I
Ilya Lavrenov 已提交
2726 2727
#endif

2728 2729
}

2730
void cv::compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op)
2731 2732 2733
{
    CV_Assert( op == CMP_LT || op == CMP_LE || op == CMP_EQ ||
               op == CMP_NE || op == CMP_GE || op == CMP_GT );
2734

A
Alexander Alekhin 已提交
2735 2736 2737 2738 2739 2740 2741 2742 2743 2744 2745 2746 2747 2748 2749 2750 2751 2752 2753 2754 2755
    bool haveScalar = false;

    if ((_src1.isMatx() + _src2.isMatx()) == 1
            || !_src1.sameSize(_src2)
            || _src1.type() != _src2.type())
    {
        if (checkScalar(_src1, _src2.type(), _src1.kind(), _src2.kind()))
        {
            op = op == CMP_LT ? CMP_GT : op == CMP_LE ? CMP_GE :
                op == CMP_GE ? CMP_LE : op == CMP_GT ? CMP_LT : op;
            // src1 is a scalar; swap it with src2
            compare(_src2, _src1, _dst, op);
            return;
        }
        else if( !checkScalar(_src2, _src1.type(), _src2.kind(), _src1.kind()) )
            CV_Error( CV_StsUnmatchedSizes,
                     "The operation is neither 'array op array' (where arrays have the same size and the same type), "
                     "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
    }

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Ilya Lavrenov 已提交
2756
    CV_OCL_RUN(_src1.dims() <= 2 && _src2.dims() <= 2 && _dst.isUMat(),
A
Alexander Alekhin 已提交
2757
               ocl_compare(_src1, _src2, _dst, op, haveScalar))
I
Ilya Lavrenov 已提交
2758

2759 2760
    int kind1 = _src1.kind(), kind2 = _src2.kind();
    Mat src1 = _src1.getMat(), src2 = _src2.getMat();
2761

2762
    if( kind1 == kind2 && src1.dims <= 2 && src2.dims <= 2 && src1.size() == src2.size() && src1.type() == src2.type() )
2763
    {
2764 2765
        int cn = src1.channels();
        _dst.create(src1.size(), CV_8UC(cn));
2766 2767
        Mat dst = _dst.getMat();
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
2768
        getCmpFunc(src1.depth())(src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, &op);
2769 2770
        return;
    }
2771

2772
    int cn = src1.channels(), depth1 = src1.depth(), depth2 = src2.depth();
2773

2774 2775 2776
    _dst.create(src1.dims, src1.size, CV_8UC(cn));
    src1 = src1.reshape(1); src2 = src2.reshape(1);
    Mat dst = _dst.getMat().reshape(1);
2777

2778 2779
    size_t esz = src1.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
2780
    BinaryFunc func = getCmpFunc(depth1);
2781

2782
    if( !haveScalar )
2783
    {
2784 2785
        const Mat* arrays[] = { &src1, &src2, &dst, 0 };
        uchar* ptrs[3];
2786

2787 2788
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size;
2789

2790 2791
        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 );
2792
    }
2793
    else
2794
    {
2795 2796
        const Mat* arrays[] = { &src1, &dst, 0 };
        uchar* ptrs[2];
2797

2798 2799
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
2800

2801 2802 2803 2804 2805 2806
        AutoBuffer<uchar> _buf(blocksize*esz);
        uchar *buf = _buf;

        if( depth1 > CV_32S )
            convertAndUnrollScalar( src2, depth1, buf, blocksize );
        else
2807
        {
2808 2809 2810 2811 2812 2813 2814
            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;
            }
2815

2816 2817 2818 2819 2820
            if( fval > getMaxVal(depth1) )
            {
                dst = Scalar::all(op == CMP_LT || op == CMP_LE || op == CMP_NE ? 255 : 0);
                return;
            }
2821

2822 2823 2824 2825 2826 2827 2828 2829 2830 2831 2832 2833 2834 2835 2836
            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);
        }
2837

2838
        for( size_t i = 0; i < it.nplanes; i++, ++it )
2839
        {
2840 2841
            for( size_t j = 0; j < total; j += blocksize )
            {
2842
                int bsz = (int)MIN(total - j, blocksize);
2843 2844 2845 2846 2847
                func( ptrs[0], 0, buf, 0, ptrs[1], 0, Size(bsz, 1), &op);
                ptrs[0] += bsz*esz;
                ptrs[1] += bsz;
            }
        }
2848
    }
2849
}
2850

2851 2852 2853
/****************************************************************************************\
*                                        inRange                                         *
\****************************************************************************************/
2854

2855 2856
namespace cv
{
2857

2858 2859 2860 2861 2862 2863 2864 2865
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]);
2866

2867
    for( ; size.height--; src1 += step1, src2 += step2, src3 += step3, dst += step )
V
Vadim Pisarevsky 已提交
2868
    {
2869
        int x = 0;
2870
        #if CV_ENABLE_UNROLLED
2871
        for( ; x <= size.width - 4; x += 4 )
V
Vadim Pisarevsky 已提交
2872
        {
2873 2874 2875 2876 2877 2878 2879
            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
2880
        }
V
Victoria Zhislina 已提交
2881
        #endif
2882 2883
        for( ; x < size.width; x++ )
            dst[x] = (uchar)-(src2[x] <= src1[x] && src1[x] <= src3[x]);
V
Vadim Pisarevsky 已提交
2884
    }
2885 2886
}

2887

2888 2889
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)
2890
{
2891 2892
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2893

2894 2895
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)
2896
{
2897 2898
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2899

2900 2901
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)
2902
{
2903 2904
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2905

2906 2907 2908 2909
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);
2910 2911
}

2912 2913
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)
2914
{
2915 2916
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2917

2918 2919 2920 2921
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);
2922 2923
}

2924 2925
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)
2926
{
2927
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
2928
}
2929

2930 2931 2932 2933 2934 2935 2936 2937 2938 2939 2940 2941 2942 2943 2944 2945
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];
2946

2947 2948 2949 2950
    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
2951
    }
2952
}
2953

2954 2955
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 );
2956

2957
static InRangeFunc getInRangeFunc(int depth)
2958
{
2959 2960 2961 2962 2963 2964 2965 2966 2967
    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];
}
2968

I
Ilya Lavrenov 已提交
2969 2970
#ifdef HAVE_OPENCL

I
Ilya Lavrenov 已提交
2971 2972 2973 2974 2975 2976 2977 2978 2979 2980 2981 2982 2983 2984 2985 2986 2987 2988 2989 2990 2991 2992 2993 2994 2995 2996 2997 2998 2999 3000 3001 3002 3003 3004 3005 3006 3007 3008 3009 3010 3011 3012 3013 3014 3015 3016 3017 3018 3019 3020 3021 3022 3023 3024 3025 3026 3027 3028 3029 3030 3031 3032 3033 3034 3035 3036 3037 3038 3039 3040 3041 3042 3043 3044 3045 3046 3047 3048 3049 3050 3051 3052 3053 3054 3055 3056 3057 3058 3059 3060 3061 3062 3063 3064 3065 3066 3067 3068 3069 3070 3071 3072 3073 3074 3075 3076
static bool ocl_inRange( InputArray _src, InputArray _lowerb,
                         InputArray _upperb, OutputArray _dst )
{
    int skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
    Size ssize = _src.size(), lsize = _lowerb.size(), usize = _upperb.size();
    int stype = _src.type(), ltype = _lowerb.type(), utype = _upperb.type();
    int sdepth = CV_MAT_DEPTH(stype), ldepth = CV_MAT_DEPTH(ltype), udepth = CV_MAT_DEPTH(utype);
    int cn = CV_MAT_CN(stype);
    bool lbScalar = false, ubScalar = false;

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

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

    if (lbScalar != ubScalar)
        return false;

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

I
Ilya Lavrenov 已提交
3077 3078
#endif

3079 3080
}

3081 3082
void cv::inRange(InputArray _src, InputArray _lowerb,
                 InputArray _upperb, OutputArray _dst)
3083
{
I
Ilya Lavrenov 已提交
3084 3085 3086
    CV_OCL_RUN(_src.dims() <= 2 && _lowerb.dims() <= 2 &&
               _upperb.dims() <= 2 && _dst.isUMat(),
               ocl_inRange(_src, _lowerb, _upperb, _dst))
I
Ilya Lavrenov 已提交
3087

3088 3089
    int skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
    Mat src = _src.getMat(), lb = _lowerb.getMat(), ub = _upperb.getMat();
3090

3091
    bool lbScalar = false, ubScalar = false;
3092

3093
    if( (lkind == _InputArray::MATX && skind != _InputArray::MATX) ||
3094 3095 3096 3097 3098 3099 3100
        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;
    }
3101

3102
    if( (ukind == _InputArray::MATX && skind != _InputArray::MATX) ||
3103 3104 3105 3106 3107 3108 3109
        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;
    }
3110

I
Ilya Lavrenov 已提交
3111
    CV_Assert(lbScalar == ubScalar);
3112

3113
    int cn = src.channels(), depth = src.depth();
3114

3115 3116
    size_t esz = src.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
3117

I
Ilya Lavrenov 已提交
3118
    _dst.create(src.dims, src.size, CV_8UC1);
3119
    Mat dst = _dst.getMat();
3120
    InRangeFunc func = getInRangeFunc(depth);
3121

3122 3123 3124
    const Mat* arrays_sc[] = { &src, &dst, 0 };
    const Mat* arrays_nosc[] = { &src, &dst, &lb, &ub, 0 };
    uchar* ptrs[4];
3125

3126 3127
    NAryMatIterator it(lbScalar && ubScalar ? arrays_sc : arrays_nosc, ptrs);
    size_t total = it.size, blocksize = std::min(total, blocksize0);
3128

3129 3130 3131
    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);
3132

3133 3134 3135 3136
    if( lbScalar && ubScalar )
    {
        lbuf = buf;
        ubuf = buf = alignPtr(buf + blocksize*esz, 16);
3137

3138 3139
        CV_Assert( lb.type() == ub.type() );
        int scdepth = lb.depth();
3140

3141 3142 3143 3144
        if( scdepth != depth && depth < CV_32S )
        {
            int* ilbuf = (int*)alignPtr(buf + blocksize*esz, 16);
            int* iubuf = ilbuf + cn;
3145

3146 3147 3148
            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);
3149
            int minval = cvRound(getMinVal(depth)), maxval = cvRound(getMaxVal(depth));
3150

3151 3152 3153 3154 3155 3156 3157 3158
            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);
        }
3159

3160 3161 3162
        convertAndUnrollScalar( lb, src.type(), lbuf, blocksize );
        convertAndUnrollScalar( ub, src.type(), ubuf, blocksize );
    }
3163

3164
    for( size_t i = 0; i < it.nplanes; i++, ++it )
V
Vadim Pisarevsky 已提交
3165
    {
3166 3167
        for( size_t j = 0; j < total; j += blocksize )
        {
3168
            int bsz = (int)MIN(total - j, blocksize);
3169 3170 3171 3172 3173 3174 3175 3176 3177 3178 3179 3180 3181 3182
            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));
3183
            if( cn > 1 )
3184 3185 3186 3187
                inRangeReduce(mbuf, ptrs[1], bsz, cn);
            ptrs[0] += delta;
            ptrs[1] += bsz;
        }
V
Vadim Pisarevsky 已提交
3188
    }
3189 3190 3191 3192 3193 3194 3195 3196 3197 3198
}

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

CV_IMPL void
cvNot( const CvArr* srcarr, CvArr* dstarr )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
3199
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3200 3201 3202 3203 3204 3205 3206 3207 3208
    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;
3209
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3210 3211 3212 3213 3214
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
    cv::bitwise_and( src1, src2, dst, mask );
}

3215

3216 3217 3218 3219 3220
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;
3221
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3222 3223 3224 3225 3226 3227 3228 3229 3230 3231 3232
    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;
3233
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3234 3235 3236 3237 3238 3239 3240 3241 3242 3243
    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;
3244
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3245 3246
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3247
    cv::bitwise_and( src, (const cv::Scalar&)s, dst, mask );
3248 3249 3250 3251 3252 3253 3254
}


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;
3255
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3256 3257
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3258
    cv::bitwise_or( src, (const cv::Scalar&)s, dst, mask );
3259 3260 3261 3262 3263 3264 3265
}


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;
3266
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3267 3268
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3269
    cv::bitwise_xor( src, (const cv::Scalar&)s, dst, mask );
3270 3271
}

3272

3273 3274 3275 3276
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;
3277
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3278 3279
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3280
    cv::add( src1, src2, dst, mask, dst.type() );
3281 3282
}

3283

3284 3285 3286 3287
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;
3288
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3289 3290
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3291
    cv::subtract( src1, src2, dst, mask, dst.type() );
3292 3293
}

3294

3295 3296 3297 3298
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;
3299
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3300 3301
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3302
    cv::add( src1, (const cv::Scalar&)value, dst, mask, dst.type() );
3303 3304
}

3305

3306 3307 3308 3309
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;
3310
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3311 3312
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3313
    cv::subtract( (const cv::Scalar&)value, src1, dst, mask, dst.type() );
3314 3315
}

3316

3317 3318 3319 3320 3321
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);
3322 3323
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::multiply( src1, src2, dst, scale, dst.type() );
3324 3325
}

3326

3327 3328 3329 3330 3331
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;
3332
    CV_Assert( src2.size == dst.size && src2.channels() == dst.channels() );
3333 3334

    if( srcarr1 )
3335
        cv::divide( cv::cvarrToMat(srcarr1), src2, dst, scale, dst.type() );
3336
    else
3337
        cv::divide( scale, src2, dst, dst.type() );
3338 3339 3340 3341 3342 3343 3344 3345 3346 3347
}


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);
3348 3349
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::addWeighted( src1, alpha, src2, beta, gamma, dst, dst.type() );
3350 3351 3352 3353 3354 3355 3356
}


CV_IMPL  void
cvAbsDiff( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3357
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3358 3359 3360 3361 3362 3363 3364 3365 3366

    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);
3367
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3368

3369
    cv::absdiff( src1, (const cv::Scalar&)scalar, dst );
3370 3371
}

3372

3373 3374 3375 3376 3377
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);
3378
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3379 3380 3381 3382

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

3383

3384 3385 3386 3387
CV_IMPL void
cvInRangeS( const void* srcarr1, CvScalar lowerb, CvScalar upperb, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3388
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3389

3390
    cv::inRange( src1, (const cv::Scalar&)lowerb, (const cv::Scalar&)upperb, dst );
3391 3392 3393 3394 3395 3396 3397
}


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);
3398
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3399 3400 3401 3402 3403 3404 3405 3406 3407

    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);
3408
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3409 3410 3411 3412 3413 3414 3415 3416 3417

    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);
3418
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3419 3420 3421 3422 3423 3424 3425 3426 3427

    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);
3428
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3429 3430 3431 3432

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

3433

3434 3435 3436 3437
CV_IMPL void
cvMinS( const void* srcarr1, double value, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3438
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3439 3440 3441 3442 3443 3444 3445 3446 3447

    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);
3448
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3449 3450 3451 3452 3453

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

/* End of file. */