arithm.cpp 119.4 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13
/*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.
14
// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44
// 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*/

/* ////////////////////////////////////////////////////////////////////
//
45
//  Arithmetic and logical operations: +, -, *, /, &, |, ^, ~, abs ...
46 47 48 49
//
// */

#include "precomp.hpp"
V
Vadim Pisarevsky 已提交
50
#include "opencl_kernels.hpp"
51 52 53 54

namespace cv
{

55 56 57 58 59
#if ARITHM_USE_IPP
struct IPPArithmInitializer
{
    IPPArithmInitializer(void)
    {
60
        ippStaticInit();
61 62
    }
};
63

64 65
IPPArithmInitializer ippArithmInitializer;
#endif
66

67
struct NOP {};
68

69 70 71 72 73 74 75 76 77 78 79 80 81
#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)
82
{
83
#if CV_SSE2
84
    VOp vop;
85
#endif
86
    Op op;
87

88 89 90
    for( ; sz.height--; src1 += step1/sizeof(src1[0]),
                        src2 += step2/sizeof(src2[0]),
                        dst += step/sizeof(dst[0]) )
91 92
    {
        int x = 0;
93

94
#if CV_SSE2
95
        if( USE_SSE2 )
96
        {
97
            for( ; x <= sz.width - 32/(int)sizeof(T); x += 32/sizeof(T) )
98
            {
99 100 101 102 103 104
                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);
105
            }
106
        }
V
Victoria Zhislina 已提交
107
#endif
108
#if CV_SSE2
109
        if( USE_SSE2 )
110
        {
111
            for( ; x <= sz.width - 8/(int)sizeof(T); x += 8/sizeof(T) )
112
            {
113 114 115
                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);
116
            }
117
        }
118 119
#endif
#if CV_ENABLE_UNROLLED
120
        for( ; x <= sz.width - 4; x += 4 )
121
        {
122 123 124 125 126 127
            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;
128
        }
129
#endif
130

131 132
        for( ; x < sz.width; x++ )
            dst[x] = op(src1[x], src2[x]);
133
    }
134
}
135

136 137 138
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)
139
{
140
#if CV_SSE2
141
    Op32 op32;
142
#endif
143
    Op op;
144

145 146 147
    for( ; sz.height--; src1 += step1/sizeof(src1[0]),
        src2 += step2/sizeof(src2[0]),
        dst += step/sizeof(dst[0]) )
148 149
    {
        int x = 0;
150

151 152 153 154
#if CV_SSE2
        if( USE_SSE2 )
        {
            if( (((size_t)src1|(size_t)src2|(size_t)dst)&15) == 0 )
155
            {
156 157
                for( ; x <= sz.width - 8; x += 8 )
                {
158 159 160 161 162 163
                    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);
164
                }
165
            }
166 167
        }
#endif
168
#if CV_SSE2
169 170
        if( USE_SSE2 )
        {
171 172 173 174 175 176 177 178 179
            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);
            }
180
        }
181
#endif
V
Victoria Zhislina 已提交
182
#if CV_ENABLE_UNROLLED
183 184
        for( ; x <= sz.width - 4; x += 4 )
        {
185 186
            T v0 = op(src1[x], src2[x]);
            T v1 = op(src1[x+1], src2[x+1]);
187 188 189 190 191
            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;
        }
V
Victoria Zhislina 已提交
192
#endif
193

194 195 196 197 198
        for( ; x < sz.width; x++ )
            dst[x] = op(src1[x], src2[x]);
    }
}

199 200

template<typename T, class Op, class Op64>
201 202
void vBinOp64(const T* src1, size_t step1, const T* src2, size_t step2,
               T* dst, size_t step, Size sz)
203
{
204
#if CV_SSE2
205
    Op64 op64;
206
#endif
207
    Op op;
208

209 210 211 212 213
    for( ; sz.height--; src1 += step1/sizeof(src1[0]),
        src2 += step2/sizeof(src2[0]),
        dst += step/sizeof(dst[0]) )
    {
        int x = 0;
214

215 216 217 218
#if CV_SSE2
        if( USE_SSE2 )
        {
            if( (((size_t)src1|(size_t)src2|(size_t)dst)&15) == 0 )
219
            {
220 221 222 223 224 225 226 227 228
                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);
                }
229
            }
230 231 232
        }
#endif

233 234
        for( ; x <= sz.width - 4; x += 4 )
        {
235 236
            T v0 = op(src1[x], src2[x]);
            T v1 = op(src1[x+1], src2[x+1]);
237 238 239 240 241
            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;
        }
242

243 244
        for( ; x < sz.width; x++ )
            dst[x] = op(src1[x], src2[x]);
245
    }
246
}
247

248
#if CV_SSE2
249

250 251 252 253 254 255
#define FUNCTOR_LOADSTORE_CAST(name, template_arg, register_type, load_body, store_body)\
    template <>                                                                                  \
    struct name<template_arg>{                                                                   \
        typedef register_type reg_type;                                                          \
        static reg_type load(const template_arg * p) { return load_body ((const reg_type *)p);}; \
        static void store(template_arg * p, reg_type v) { store_body ((reg_type *)p, v);};       \
256
    }
257 258 259 260 261 262 263

#define FUNCTOR_LOADSTORE(name, template_arg, register_type, load_body, store_body)\
    template <>                                                                \
    struct name<template_arg>{                                                 \
        typedef register_type reg_type;                                        \
        static reg_type load(const template_arg * p) { return load_body (p);}; \
        static void store(template_arg * p, reg_type v) { store_body (p, v);}; \
264 265
    }

266 267 268 269 270 271 272 273 274 275 276
#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;                                                              \
        }                                                                      \
    }
277

278 279 280 281 282 283 284 285 286 287
#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;                                                              \
        }                                                                      \
288
    }
289

290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333
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,
334 335
        __m128i m = _mm_cmpgt_epi32(a, b);
        return _mm_xor_si128(a, _mm_and_si128(_mm_xor_si128(a, b), m));
336 337 338 339 340 341 342 343 344 345 346 347 348
    );
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,
349 350
        __m128i m = _mm_cmpgt_epi32(b, a);
        return _mm_xor_si128(a, _mm_and_si128(_mm_xor_si128(a, b), m));
351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376
    );
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,
377 378 379
        __m128i d = _mm_sub_epi32(a, b);
        __m128i m = _mm_cmpgt_epi32(b, a);
        return _mm_sub_epi32(_mm_xor_si128(d, m), m);
380 381
    );
FUNCTOR_CLOSURE_2arg(VAbsDiff,  float,
382
        return _mm_and_ps(_mm_sub_ps(a,b), *(const __m128*)v32f_absmask);
383 384
    );
FUNCTOR_CLOSURE_2arg(VAbsDiff, double,
385
        return _mm_and_pd(_mm_sub_pd(a,b), *(const __m128d*)v64f_absmask);
386 387 388 389 390 391 392 393 394 395
    );

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));
396
#endif
397

398 399
#if CV_SSE2
#define IF_SIMD(op) op
400
#else
401
#define IF_SIMD(op) NOP
402
#endif
403

404 405 406 407
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); }
408

409
template<typename T> struct OpAbsDiff
410
{
411 412 413 414
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()(T a, T b) const { return (T)std::abs(a - b); }
415 416
};

417 418
template<> inline short OpAbsDiff<short>::operator ()(short a, short b) const
{ return saturate_cast<short>(std::abs(a - b)); }
419

420 421
template<> inline schar OpAbsDiff<schar>::operator ()(schar a, schar b) const
{ return saturate_cast<schar>(std::abs(a - b)); }
422

423
template<typename T, typename WT=T> struct OpAbsDiffS
424
{
425 426 427 428
    typedef T type1;
    typedef WT type2;
    typedef T rtype;
    T operator()(T a, WT b) const { return saturate_cast<T>(std::abs(a - b)); }
429 430
};

431
template<typename T> struct OpAnd
432
{
433 434 435 436
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T b ) const { return a & b; }
437 438
};

439
template<typename T> struct OpOr
440
{
441 442 443 444
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T b ) const { return a | b; }
445 446
};

447
template<typename T> struct OpXor
448
{
449 450 451 452
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T b ) const { return a ^ b; }
453 454
};

455
template<typename T> struct OpNot
456
{
457 458 459 460
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T ) const { return ~a; }
461
};
462

463 464 465 466 467
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;
}
468

469 470 471 472 473
static void add8u( const uchar* src1, size_t step1,
                   const uchar* src2, size_t step2,
                   uchar* dst, size_t step, Size sz, void* )
{
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
474
           ippiAdd_8u_C1RSfs(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz, 0),
475
           (vBinOp<uchar, OpAdd<uchar>, IF_SIMD(VAdd<uchar>)>(src1, step1, src2, step2, dst, step, sz)));
476
}
477

478 479 480
static void add8s( const schar* src1, size_t step1,
                   const schar* src2, size_t step2,
                   schar* dst, size_t step, Size sz, void* )
481
{
482
    vBinOp<schar, OpAdd<schar>, IF_SIMD(VAdd<schar>)>(src1, step1, src2, step2, dst, step, sz);
483
}
484

485 486 487
static void add16u( const ushort* src1, size_t step1,
                    const ushort* src2, size_t step2,
                    ushort* dst, size_t step, Size sz, void* )
488
{
489
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
490
           ippiAdd_16u_C1RSfs(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz, 0),
491
           (vBinOp<ushort, OpAdd<ushort>, IF_SIMD(VAdd<ushort>)>(src1, step1, src2, step2, dst, step, sz)));
492
}
493

494 495 496
static void add16s( const short* src1, size_t step1,
                    const short* src2, size_t step2,
                    short* dst, size_t step, Size sz, void* )
497
{
498
    IF_IPP(fixSteps(sz, sizeof(dst[0]), step1, step2, step);
499
           ippiAdd_16s_C1RSfs(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)sz, 0),
500
           (vBinOp<short, OpAdd<short>, IF_SIMD(VAdd<short>)>(src1, step1, src2, step2, dst, step, sz)));
501
}
502

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

857

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

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

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

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

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

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

915 916 917

enum { OCL_OP_ADD=0, OCL_OP_SUB=1, OCL_OP_RSUB=2, OCL_OP_ABSDIFF=3, OCL_OP_MUL=4,
       OCL_OP_MUL_SCALE=5, OCL_OP_DIV_SCALE=6, OCL_OP_RECIP_SCALE=7, OCL_OP_ADDW=8,
I
Ilya Lavrenov 已提交
918 919
       OCL_OP_AND=9, OCL_OP_OR=10, OCL_OP_XOR=11, OCL_OP_NOT=12, OCL_OP_MIN=13, OCL_OP_MAX=14,
       OCL_OP_RDIV_SCALE=15 };
920 921 922

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
923
    "OP_ADDW", "OP_AND", "OP_OR", "OP_XOR", "OP_NOT", "OP_MIN", "OP_MAX", "OP_RDIV_SCALE", 0 };
924 925 926

static bool ocl_binary_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                          InputArray _mask, bool bitwise, int oclop, bool haveScalar )
927
{
928 929 930 931 932
    bool haveMask = !_mask.empty();
    int srctype = _src1.type();
    int srcdepth = CV_MAT_DEPTH(srctype);
    int cn = CV_MAT_CN(srctype);

933 934 935 936
    bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;

    if( oclop < 0 || ((haveMask || haveScalar) && (cn > 4 || cn == 3)) ||
            (!doubleSupport && srcdepth == CV_64F))
937 938 939 940
        return false;

    char opts[1024];
    int kercn = haveMask || haveScalar ? cn : 1;
941
    sprintf(opts, "-D %s%s -D %s -D dstT=%s%s",
942 943
            (haveMask ? "MASK_" : ""), (haveScalar ? "UNARY_OP" : "BINARY_OP"), oclop2str[oclop],
            bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, kercn)) :
944
            ocl::typeToStr(CV_MAKETYPE(srcdepth, kercn)), doubleSupport ? " -D DOUBLE_SUPPORT" : "");
945 946 947 948 949

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

I
Ilya Lavrenov 已提交
950 951 952
    UMat src1 = _src1.getUMat(), src2;
    UMat dst = _dst.getUMat(), mask = _mask.getUMat();

953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005
    int cscale = cn/kercn;
    ocl::KernelArg src1arg = ocl::KernelArg::ReadOnlyNoSize(src1, cscale);
    ocl::KernelArg dstarg = haveMask ? ocl::KernelArg::ReadWrite(dst, cscale) :
                                       ocl::KernelArg::WriteOnly(dst, cscale);
    ocl::KernelArg maskarg = ocl::KernelArg::ReadOnlyNoSize(mask, 1);

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

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

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

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

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

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


static void binary_op( InputArray _src1, InputArray _src2, OutputArray _dst,
                       InputArray _mask, const BinaryFunc* tab,
                       bool bitwise, int oclop )
{
    const _InputArray *psrc1 = &_src1, *psrc2 = &_src2;
    int kind1 = psrc1->kind(), kind2 = psrc2->kind();
    int type1 = psrc1->type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
    int type2 = psrc2->type(), depth2 = CV_MAT_DEPTH(type2), cn2 = CV_MAT_CN(type2);
    int dims1 = psrc1->dims(), dims2 = psrc2->dims();
    Size sz1 = dims1 <= 2 ? psrc1->size() : Size();
    Size sz2 = dims2 <= 2 ? psrc2->size() : Size();
    bool use_opencl = (kind1 == _InputArray::UMAT || kind2 == _InputArray::UMAT) &&
                        ocl::useOpenCL() && dims1 <= 2 && dims2 <= 2;
1006 1007
    bool haveMask = !_mask.empty(), haveScalar = false;
    BinaryFunc func;
1008

1009
    if( dims1 <= 2 && dims2 <= 2 && kind1 == kind2 && sz1 == sz2 && type1 == type2 && !haveMask )
1010
    {
1011 1012 1013
        _dst.create(sz1, type1);
        if( use_opencl && ocl_binary_op(*psrc1, *psrc2, _dst, _mask, bitwise, oclop, false) )
            return;
1014 1015 1016
        if( bitwise )
        {
            func = *tab;
1017
            cn = (int)CV_ELEM_SIZE(type1);
1018 1019
        }
        else
1020
            func = tab[depth1];
1021

1022
        Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat();
1023
        Size sz = getContinuousSize(src1, src2, dst);
1024
        size_t len = sz.width*(size_t)cn;
1025 1026 1027 1028 1029 1030
        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;
        }
1031
    }
1032

1033 1034 1035 1036
    if( oclop == OCL_OP_NOT )
        haveScalar = true;
    else if( (kind1 == _InputArray::MATX) + (kind2 == _InputArray::MATX) == 1 ||
        !psrc1->sameSize(*psrc2) || type1 != type2 )
1037
    {
1038 1039
        if( checkScalar(*psrc1, type2, kind1, kind2) )
        {
1040
            // src1 is a scalar; swap it with src2
1041 1042 1043 1044 1045 1046 1047
            swap(psrc1, psrc2);
            swap(type1, type2);
            swap(depth1, depth2);
            swap(cn, cn2);
            swap(sz1, sz2);
        }
        else if( !checkScalar(*psrc2, type1, kind2, kind1) )
1048 1049 1050 1051 1052
            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;
    }
1053 1054 1055 1056
    else
    {
        CV_Assert( psrc1->sameSize(*psrc2) && type1 == type2 );
    }
1057

1058
    size_t esz = CV_ELEM_SIZE(type1);
1059 1060
    size_t blocksize0 = (BLOCK_SIZE + esz-1)/esz;
    BinaryFunc copymask = 0;
1061
    bool reallocate = false;
1062

1063 1064
    if( haveMask )
    {
1065 1066
        int mtype = _mask.type();
        CV_Assert( (mtype == CV_8U || mtype == CV_8S) && _mask.sameSize(*psrc1));
1067
        copymask = getCopyMaskFunc(esz);
1068
        reallocate = !_dst.sameSize(*psrc1) || _dst.type() != type1;
1069
    }
1070

1071 1072
    AutoBuffer<uchar> _buf;
    uchar *scbuf = 0, *maskbuf = 0;
1073

1074
    _dst.createSameSize(*psrc1, type1);
1075
    // if this is mask operation and dst has been reallocated,
1076
    // we have to clear the destination
1077
    if( haveMask && reallocate )
1078 1079 1080 1081 1082 1083 1084
        _dst.setTo(0.);

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

    Mat src1 = psrc1->getMat(), src2 = psrc2->getMat();
    Mat dst = _dst.getMat(), mask = _mask.getMat();
1085

1086 1087 1088
    if( bitwise )
    {
        func = *tab;
1089
        cn = (int)esz;
1090 1091 1092
    }
    else
    {
1093
        func = tab[depth1];
1094
    }
1095

1096
    if( !haveScalar )
1097
    {
1098 1099
        const Mat* arrays[] = { &src1, &src2, &dst, &mask, 0 };
        uchar* ptrs[4];
1100

1101 1102
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = total;
1103

1104 1105
        if( blocksize*cn > INT_MAX )
            blocksize = INT_MAX/cn;
1106

1107 1108 1109 1110 1111 1112
        if( haveMask )
        {
            blocksize = std::min(blocksize, blocksize0);
            _buf.allocate(blocksize*esz);
            maskbuf = _buf;
        }
1113

1114
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1115
        {
1116
            for( size_t j = 0; j < total; j += blocksize )
1117
            {
1118
                int bsz = (int)MIN(total - j, blocksize);
1119

1120
                func( ptrs[0], 0, ptrs[1], 0, haveMask ? maskbuf : ptrs[2], 0, Size(bsz*cn, 1), 0 );
1121
                if( haveMask )
1122
                {
1123 1124
                    copymask( maskbuf, 0, ptrs[3], 0, ptrs[2], 0, Size(bsz, 1), &esz );
                    ptrs[3] += bsz;
1125
                }
1126

1127 1128
                bsz *= (int)esz;
                ptrs[0] += bsz; ptrs[1] += bsz; ptrs[2] += bsz;
1129 1130
            }
        }
1131 1132 1133 1134 1135
    }
    else
    {
        const Mat* arrays[] = { &src1, &dst, &mask, 0 };
        uchar* ptrs[3];
1136

1137 1138
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
1139

1140 1141 1142
        _buf.allocate(blocksize*(haveMask ? 2 : 1)*esz + 32);
        scbuf = _buf;
        maskbuf = alignPtr(scbuf + blocksize*esz, 16);
1143

1144
        convertAndUnrollScalar( src2, src1.type(), scbuf, blocksize);
1145

1146
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1147
        {
1148
            for( size_t j = 0; j < total; j += blocksize )
1149
            {
1150
                int bsz = (int)MIN(total - j, blocksize);
1151

1152
                func( ptrs[0], 0, scbuf, 0, haveMask ? maskbuf : ptrs[1], 0, Size(bsz*cn, 1), 0 );
1153
                if( haveMask )
1154
                {
1155 1156
                    copymask( maskbuf, 0, ptrs[2], 0, ptrs[1], 0, Size(bsz, 1), &esz );
                    ptrs[2] += bsz;
1157
                }
1158

1159 1160
                bsz *= (int)esz;
                ptrs[0] += bsz; ptrs[1] += bsz;
1161 1162 1163 1164
            }
        }
    }
}
1165

1166
static BinaryFunc* getMaxTab()
V
Vadim Pisarevsky 已提交
1167
{
1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178
    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;
}
1179

1180
static BinaryFunc* getMinTab()
1181
{
1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192
    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;
}
1193

V
Vadim Pisarevsky 已提交
1194
}
1195

1196
void cv::bitwise_and(InputArray a, InputArray b, OutputArray c, InputArray mask)
1197
{
A
Andrey Kamaev 已提交
1198
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(and8u);
1199
    binary_op(a, b, c, mask, &f, true, OCL_OP_AND);
1200 1201
}

1202
void cv::bitwise_or(InputArray a, InputArray b, OutputArray c, InputArray mask)
1203
{
A
Andrey Kamaev 已提交
1204
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(or8u);
1205
    binary_op(a, b, c, mask, &f, true, OCL_OP_OR);
1206 1207
}

1208
void cv::bitwise_xor(InputArray a, InputArray b, OutputArray c, InputArray mask)
1209
{
A
Andrey Kamaev 已提交
1210
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(xor8u);
1211
    binary_op(a, b, c, mask, &f, true, OCL_OP_XOR);
1212 1213
}

1214
void cv::bitwise_not(InputArray a, OutputArray c, InputArray mask)
1215
{
A
Andrey Kamaev 已提交
1216
    BinaryFunc f = (BinaryFunc)GET_OPTIMIZED(not8u);
1217
    binary_op(a, a, c, mask, &f, true, OCL_OP_NOT);
1218 1219
}

1220
void cv::max( InputArray src1, InputArray src2, OutputArray dst )
1221
{
1222
    binary_op(src1, src2, dst, noArray(), getMaxTab(), false, OCL_OP_MAX );
1223 1224
}

1225
void cv::min( InputArray src1, InputArray src2, OutputArray dst )
1226
{
1227
    binary_op(src1, src2, dst, noArray(), getMinTab(), false, OCL_OP_MIN );
1228 1229
}

1230
void cv::max(const Mat& src1, const Mat& src2, Mat& dst)
1231
{
1232
    OutputArray _dst(dst);
1233
    binary_op(src1, src2, _dst, noArray(), getMaxTab(), false, OCL_OP_MAX );
1234 1235
}

1236 1237 1238
void cv::min(const Mat& src1, const Mat& src2, Mat& dst)
{
    OutputArray _dst(dst);
1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251
    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 );
1252
}
1253 1254


1255 1256 1257
/****************************************************************************************\
*                                      add/subtract                                      *
\****************************************************************************************/
1258

1259 1260
namespace cv
{
1261

1262 1263
static int actualScalarDepth(const double* data, int len)
{
1264 1265
    int i = 0, minval = INT_MAX, maxval = INT_MIN;
    for(; i < len; ++i)
1266
    {
1267 1268 1269 1270 1271
        int ival = cvRound(data[i]);
        if( ival != data[i] )
            break;
        minval = MIN(minval, ival);
        maxval = MAX(maxval, ival);
1272
    }
1273
    return i < len ? CV_64F :
A
Andrey Kamaev 已提交
1274 1275 1276 1277
        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 :
1278
        CV_32S;
1279 1280
}

1281 1282 1283 1284 1285

static bool ocl_arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
                          InputArray _mask, int wtype,
                          void* usrdata, int oclop,
                          bool haveScalar )
1286
{
I
Ilya Lavrenov 已提交
1287
    bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
1288
    int type1 = _src1.type(), depth1 = CV_MAT_DEPTH(type1), cn = CV_MAT_CN(type1);
1289
    bool haveMask = !_mask.empty();
1290

I
Ilya Lavrenov 已提交
1291
    if( ((haveMask || haveScalar) && (cn > 4 || cn == 3)) )
1292 1293
        return false;

1294
    int dtype = _dst.type(), ddepth = CV_MAT_DEPTH(dtype), wdepth = std::max(CV_32S, CV_MAT_DEPTH(wtype));
I
Ilya Lavrenov 已提交
1295 1296 1297
    if (!doubleSupport)
        wdepth = std::min(wdepth, CV_32F);

1298
    wtype = CV_MAKETYPE(wdepth, cn);
1299
    int type2 = haveScalar ? wtype : _src2.type(), depth2 = CV_MAT_DEPTH(type2);
I
Ilya Lavrenov 已提交
1300 1301
    if (!doubleSupport && (depth2 == CV_64F || depth1 == CV_64F))
        return false;
1302

I
Ilya Lavrenov 已提交
1303
    int kercn = haveMask || haveScalar ? cn : 1;
1304

I
Ilya Lavrenov 已提交
1305
    char cvtstr[4][32], opts[1024];
1306
    sprintf(opts, "-D %s%s -D %s -D srcT1=%s -D srcT2=%s "
I
Ilya Lavrenov 已提交
1307
            "-D dstT=%s -D workT=%s -D scaleT=%s -D convertToWT1=%s "
I
Ilya Lavrenov 已提交
1308
            "-D convertToWT2=%s -D convertToDT=%s%s",
1309 1310 1311 1312 1313
            (haveMask ? "MASK_" : ""), (haveScalar ? "UNARY_OP" : "BINARY_OP"),
            oclop2str[oclop], ocl::typeToStr(CV_MAKETYPE(depth1, kercn)),
            ocl::typeToStr(CV_MAKETYPE(depth2, kercn)),
            ocl::typeToStr(CV_MAKETYPE(ddepth, kercn)),
            ocl::typeToStr(CV_MAKETYPE(wdepth, kercn)),
I
Ilya Lavrenov 已提交
1314
            ocl::typeToStr(CV_MAKETYPE(wdepth, 1)),
1315 1316
            ocl::convertTypeStr(depth1, wdepth, kercn, cvtstr[0]),
            ocl::convertTypeStr(depth2, wdepth, kercn, cvtstr[1]),
I
Ilya Lavrenov 已提交
1317 1318
            ocl::convertTypeStr(wdepth, ddepth, kercn, cvtstr[2]),
            doubleSupport ? " -D DOUBLE_SUPPORT" : "");
1319

I
Ilya Lavrenov 已提交
1320
    size_t usrdata_esz = CV_ELEM_SIZE(wdepth);
1321 1322 1323 1324
    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
1325
        oclop == OCL_OP_RDIV_SCALE || oclop == OCL_OP_RECIP_SCALE ? 1 : oclop == OCL_OP_ADDW ? 3 : 0;
1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336
    if( n > 0 && wdepth == CV_32F )
    {
        for( i = 0; i < n; i++ )
            usrdata_f[i] = (float)usrdata_d[i];
        usrdata_p = (const uchar*)usrdata_f;
    }

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

I
Ilya Lavrenov 已提交
1337 1338 1339
    UMat src1 = _src1.getUMat(), src2;
    UMat dst = _dst.getUMat(), mask = _mask.getUMat();

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

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

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

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

        if( !haveMask )
I
Ilya Lavrenov 已提交
1358 1359 1360 1361 1362 1363 1364 1365 1366
        {
            if(n == 0)
                k.args(src1arg, dstarg, scalararg);
            else if(n == 1)
                k.args(src1arg, dstarg, scalararg,
                       ocl::KernelArg(0, 0, 0, usrdata_p, usrdata_esz));
            else
                CV_Error(Error::StsNotImplemented, "unsupported number of extra parameters");
        }
1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393
        else
            k.args(src1arg, maskarg, dstarg, scalararg);
    }
    else
    {
        src2 = _src2.getUMat();
        ocl::KernelArg src2arg = ocl::KernelArg::ReadOnlyNoSize(src2, cscale);

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

I
Ilya Lavrenov 已提交
1394
    size_t globalsize[] = { src1.cols * cscale, src1.rows };
1395
    return k.run(2, globalsize, NULL, false);
1396 1397 1398 1399 1400 1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411
}


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
1412
    bool use_opencl = _dst.isUMat() && ocl::useOpenCL() && dims1 <= 2 && dims2 <= 2;
1413 1414 1415 1416 1417 1418
    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
1419
        ((src1Scalar && src2Scalar) || (!src1Scalar && !src2Scalar)) )
V
Vadim Pisarevsky 已提交
1420
    {
1421 1422 1423 1424 1425 1426
        _dst.createSameSize(*psrc1, type1);
        if( use_opencl &&
            ocl_arithm_op(*psrc1, *psrc2, _dst, _mask,
                          (!usrdata ? type1 : std::max(depth1, CV_32F)),
                          usrdata, oclop, false))
            return;
1427

1428
        Mat src1 = psrc1->getMat(), src2 = psrc2->getMat(), dst = _dst.getMat();
1429
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
1430
        tab[depth1](src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, usrdata);
V
Vadim Pisarevsky 已提交
1431 1432
        return;
    }
1433

1434
    bool haveScalar = false, swapped12 = false;
1435 1436

    if( dims1 != dims2 || sz1 != sz2 || cn != cn2 ||
1437
        ((kind1 == _InputArray::MATX || kind2 == _InputArray::MATX) &&
1438
         (sz1 == Size(1,4) || sz2 == Size(1,4))) )
1439
    {
1440
        if( checkScalar(*psrc1, type2, kind1, kind2) )
1441 1442
        {
            // src1 is a scalar; swap it with src2
1443 1444 1445 1446 1447 1448
            swap(psrc1, psrc2);
            swap(sz1, sz2);
            swap(type1, type2);
            swap(depth1, depth2);
            swap(cn, cn2);
            swap(dims1, dims2);
1449
            swapped12 = true;
1450 1451
            if( oclop == OCL_OP_SUB )
                oclop = OCL_OP_RSUB;
I
Ilya Lavrenov 已提交
1452 1453
            if ( oclop == OCL_OP_DIV_SCALE )
                oclop = OCL_OP_RDIV_SCALE;
1454
        }
1455
        else if( !checkScalar(*psrc2, type1, kind2, kind1) )
1456
            CV_Error( CV_StsUnmatchedSizes,
1457 1458
                     "The operation is neither 'array op array' "
                     "(where arrays have the same size and the same number of channels), "
1459 1460
                     "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
1461
        CV_Assert(type2 == CV_64F && (sz2.height == 1 || sz2.height == 4));
A
Andrey Kamaev 已提交
1462

1463 1464
        if (!muldiv)
        {
1465 1466 1467
            Mat sc = psrc2->getMat();
            depth2 = actualScalarDepth(sc.ptr<double>(), cn);
            if( depth2 == CV_64F && (depth1 < CV_32S || depth1 == CV_32F) )
1468 1469
                depth2 = CV_32F;
        }
A
Andrey Kamaev 已提交
1470
        else
1471
            depth2 = CV_64F;
1472
    }
1473

1474 1475 1476 1477 1478 1479
    if( dtype < 0 )
    {
        if( _dst.fixedType() )
            dtype = _dst.type();
        else
        {
1480
            if( !haveScalar && type1 != type2 )
1481 1482 1483
                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");
1484
            dtype = type1;
1485 1486 1487
        }
    }
    dtype = CV_MAT_DEPTH(dtype);
1488

1489 1490 1491 1492 1493 1494 1495
    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);
1496

1497 1498 1499 1500 1501 1502 1503 1504 1505 1506 1507
        // 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);
    }
1508

1509 1510
    dtype = CV_MAKETYPE(dtype, cn);
    wtype = CV_MAKETYPE(wtype, cn);
1511

1512 1513
    if( haveMask )
    {
1514 1515 1516
        int mtype = _mask.type();
        CV_Assert( (mtype == CV_8UC1 || mtype == CV_8SC1) && _mask.sameSize(*psrc1) );
        reallocate = !_dst.sameSize(*psrc1) || _dst.type() != dtype;
1517
    }
1518

1519 1520 1521
    _dst.createSameSize(*psrc1, dtype);
    if( reallocate )
        _dst.setTo(0.);
1522

1523 1524 1525 1526
    if( use_opencl &&
        ocl_arithm_op(*psrc1, *psrc2, _dst, _mask, wtype,
                      usrdata, oclop, haveScalar))
        return;
1527

1528 1529 1530 1531 1532 1533 1534 1535 1536
    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();
1537

1538 1539 1540 1541 1542 1543
    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);
1544
    BinaryFunc func = tab[CV_MAT_DEPTH(wtype)];
1545

1546 1547 1548 1549
    if( !haveScalar )
    {
        const Mat* arrays[] = { &src1, &src2, &dst, &mask, 0 };
        uchar* ptrs[4];
1550

1551 1552
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = total;
1553

1554 1555 1556 1557 1558 1559 1560 1561 1562 1563 1564 1565 1566 1567
        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;
1568

1569
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1570
        {
1571
            for( size_t j = 0; j < total; j += blocksize )
1572
            {
1573
                int bsz = (int)MIN(total - j, blocksize);
1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586 1587 1588
                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;
                }
1589

1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609
                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;
1610 1611
            }
        }
1612 1613 1614 1615 1616
    }
    else
    {
        const Mat* arrays[] = { &src1, &dst, &mask, 0 };
        uchar* ptrs[3];
1617

1618 1619
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
1620

1621 1622 1623 1624 1625 1626 1627 1628 1629 1630
        _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;
1631

1632
        convertAndUnrollScalar( src2, wtype, buf2, blocksize);
1633

1634
        for( size_t i = 0; i < it.nplanes; i++, ++it )
1635
        {
1636 1637
            for( size_t j = 0; j < total; j += blocksize )
            {
1638
                int bsz = (int)MIN(total - j, blocksize);
1639 1640 1641 1642
                Size bszn(bsz*cn, 1);
                const uchar *sptr1 = ptrs[0];
                const uchar* sptr2 = buf2;
                uchar* dptr = ptrs[1];
1643

1644 1645 1646 1647 1648
                if( cvtsrc1 )
                {
                    cvtsrc1( sptr1, 0, 0, 0, buf1, 0, bszn, 0 );
                    sptr1 = buf1;
                }
1649

1650 1651
                if( swapped12 )
                    std::swap(sptr1, sptr2);
1652

1653 1654 1655 1656 1657 1658 1659 1660 1661 1662 1663 1664 1665 1666 1667 1668 1669 1670 1671 1672 1673
                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;
            }
1674 1675 1676
        }
    }
}
1677

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

1689 1690 1691 1692
    return addTab;
}

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

1706
static BinaryFunc* getAbsDiffTab()
1707
{
1708 1709 1710 1711 1712 1713 1714 1715 1716 1717 1718
    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;
}
1719 1720

}
1721

1722 1723
void cv::add( InputArray src1, InputArray src2, OutputArray dst,
          InputArray mask, int dtype )
1724
{
1725
    arithm_op(src1, src2, dst, mask, dtype, getAddTab(), false, 0, OCL_OP_ADD );
1726 1727
}

1728 1729
void cv::subtract( InputArray src1, InputArray src2, OutputArray dst,
               InputArray mask, int dtype )
1730
{
A
Andrey Kamaev 已提交
1731
#ifdef HAVE_TEGRA_OPTIMIZATION
1732
    if (mask.empty() && src1.depth() == CV_8U && src2.depth() == CV_8U)
1733
    {
1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757
        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;
            }
        }
1758
    }
A
Andrey Kamaev 已提交
1759
#endif
1760
    arithm_op(src1, src2, dst, mask, dtype, getSubTab(), false, 0, OCL_OP_SUB );
1761 1762
}

1763
void cv::absdiff( InputArray src1, InputArray src2, OutputArray dst )
1764
{
1765
    arithm_op(src1, src2, dst, noArray(), -1, getAbsDiffTab(), false, 0, OCL_OP_ABSDIFF);
1766
}
1767 1768 1769 1770 1771

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

1772 1773 1774
namespace cv
{

1775
template<typename T, typename WT> static void
1776 1777
mul_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, WT scale )
1778
{
1779 1780 1781
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1782

1783
    if( scale == (WT)1. )
1784
    {
1785
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1786
        {
V
Victoria Zhislina 已提交
1787
            int i=0;
1788
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1789
            for(; i <= size.width - 4; i += 4 )
1790
            {
1791 1792 1793 1794 1795 1796
                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;
1797 1798 1799

                t0 = saturate_cast<T>(src1[i+2] * src2[i+2]);
                t1 = saturate_cast<T>(src1[i+3] * src2[i+3]);
1800 1801
                dst[i+2] = t0;
                dst[i+3] = t1;
1802
            }
V
Victoria Zhislina 已提交
1803
            #endif
1804 1805 1806 1807 1808 1809
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(src1[i] * src2[i]);
        }
    }
    else
    {
1810
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1811
        {
V
Victoria Zhislina 已提交
1812
            int i = 0;
1813
            #if CV_ENABLE_UNROLLED
V
Victoria Zhislina 已提交
1814
            for(; i <= size.width - 4; i += 4 )
1815 1816 1817 1818 1819 1820 1821 1822 1823
            {
                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
1824
            #endif
1825 1826 1827 1828 1829 1830 1831
            for( ; i < size.width; i++ )
                dst[i] = saturate_cast<T>(scale*(WT)src1[i]*src2[i]);
        }
    }
}

template<typename T> static void
1832 1833
div_( const T* src1, size_t step1, const T* src2, size_t step2,
      T* dst, size_t step, Size size, double scale )
1834
{
1835 1836 1837
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1838

1839
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
1840 1841
    {
        int i = 0;
1842
        #if CV_ENABLE_UNROLLED
1843 1844 1845 1846 1847 1848 1849 1850 1851
        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;
1852

1853 1854 1855 1856
                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));
1857

1858 1859 1860 1861 1862 1863 1864 1865 1866
                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;
1867

1868 1869 1870 1871
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1872
        #endif
1873 1874 1875 1876 1877 1878
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(src1[i]*scale/src2[i]) : 0;
    }
}

template<typename T> static void
1879 1880
recip_( const T*, size_t, const T* src2, size_t step2,
        T* dst, size_t step, Size size, double scale )
1881
{
1882 1883
    step2 /= sizeof(src2[0]);
    step /= sizeof(dst[0]);
1884

1885
    for( ; size.height--; src2 += step2, dst += step )
1886 1887
    {
        int i = 0;
1888
        #if CV_ENABLE_UNROLLED
1889 1890 1891 1892 1893 1894 1895 1896 1897
        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;
1898

1899 1900 1901 1902
                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);
1903

1904 1905 1906 1907 1908 1909 1910 1911 1912
                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;
1913

1914 1915 1916 1917
                dst[i] = z0; dst[i+1] = z1;
                dst[i+2] = z2; dst[i+3] = z3;
            }
        }
V
Victoria Zhislina 已提交
1918
        #endif
1919 1920 1921 1922
        for( ; i < size.width; i++ )
            dst[i] = src2[i] != 0 ? saturate_cast<T>(scale/src2[i]) : 0;
    }
}
1923 1924


1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953
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);
}
1954

1955 1956 1957 1958 1959
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);
}
1960

1961 1962 1963 1964 1965
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);
}
1966

1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034
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);
}
2035

2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052
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);
}
2053 2054


2055
static BinaryFunc* getMulTab()
2056
{
2057 2058 2059 2060 2061 2062 2063 2064 2065
    static BinaryFunc mulTab[] =
    {
        (BinaryFunc)mul8u, (BinaryFunc)mul8s, (BinaryFunc)mul16u,
        (BinaryFunc)mul16s, (BinaryFunc)mul32s, (BinaryFunc)mul32f,
        (BinaryFunc)mul64f, 0
    };

    return mulTab;
}
2066

2067
static BinaryFunc* getDivTab()
2068
{
2069 2070 2071 2072 2073 2074
    static BinaryFunc divTab[] =
    {
        (BinaryFunc)div8u, (BinaryFunc)div8s, (BinaryFunc)div16u,
        (BinaryFunc)div16s, (BinaryFunc)div32s, (BinaryFunc)div32f,
        (BinaryFunc)div64f, 0
    };
2075

2076 2077 2078 2079
    return divTab;
}

static BinaryFunc* getRecipTab()
2080
{
2081 2082 2083 2084 2085 2086
    static BinaryFunc recipTab[] =
    {
        (BinaryFunc)recip8u, (BinaryFunc)recip8s, (BinaryFunc)recip16u,
        (BinaryFunc)recip16s, (BinaryFunc)recip32s, (BinaryFunc)recip32f,
        (BinaryFunc)recip64f, 0
    };
2087

2088 2089
    return recipTab;
}
2090

2091
}
2092

2093
void cv::multiply(InputArray src1, InputArray src2,
2094
                  OutputArray dst, double scale, int dtype)
2095
{
2096
    arithm_op(src1, src2, dst, noArray(), dtype, getMulTab(),
I
Ilya Lavrenov 已提交
2097
              true, &scale, std::abs(scale - 1.0) < DBL_EPSILON ? OCL_OP_MUL : OCL_OP_MUL_SCALE);
2098
}
2099

2100
void cv::divide(InputArray src1, InputArray src2,
2101 2102
                OutputArray dst, double scale, int dtype)
{
2103
    arithm_op(src1, src2, dst, noArray(), dtype, getDivTab(), true, &scale, OCL_OP_DIV_SCALE);
2104 2105
}

2106
void cv::divide(double scale, InputArray src2,
2107 2108
                OutputArray dst, int dtype)
{
2109
    arithm_op(src2, src2, dst, noArray(), dtype, getRecipTab(), true, &scale, OCL_OP_RECIP_SCALE);
2110 2111
}

2112 2113 2114 2115
/****************************************************************************************\
*                                      addWeighted                                       *
\****************************************************************************************/

2116 2117 2118
namespace cv
{

2119
template<typename T, typename WT> static void
2120 2121 2122 2123 2124 2125 2126 2127 2128 2129
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 )
2130
    {
2131
        int x = 0;
2132
        #if CV_ENABLE_UNROLLED
2133
        for( ; x <= size.width - 4; x += 4 )
2134
        {
2135 2136 2137
            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;
2138

2139 2140 2141
            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;
2142
        }
V
Victoria Zhislina 已提交
2143
        #endif
2144 2145
        for( ; x < size.width; x++ )
            dst[x] = saturate_cast<T>(src1[x]*alpha + src2[x]*beta + gamma);
2146 2147 2148 2149 2150
    }
}


static void
2151 2152 2153 2154 2155 2156 2157
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];
2158

2159
    for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2160
    {
2161
        int x = 0;
2162

2163 2164
#if CV_SSE2
        if( USE_SSE2 )
2165
        {
2166 2167
            __m128 a4 = _mm_set1_ps(alpha), b4 = _mm_set1_ps(beta), g4 = _mm_set1_ps(gamma);
            __m128i z = _mm_setzero_si128();
2168

2169
            for( ; x <= size.width - 8; x += 8 )
2170
            {
2171 2172
                __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);
2173

2174 2175 2176 2177
                __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));
2178

2179 2180 2181
                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);
2182

2183 2184
                u = _mm_packs_epi32(_mm_cvtps_epi32(u0), _mm_cvtps_epi32(u1));
                u = _mm_packus_epi16(u, u);
2185

2186
                _mm_storel_epi64((__m128i*)(dst + x), u);
2187 2188
            }
        }
2189
#endif
2190
        #if CV_ENABLE_UNROLLED
2191
        for( ; x <= size.width - 4; x += 4 )
2192
        {
2193 2194 2195
            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;
2196

2197 2198
            dst[x] = saturate_cast<uchar>(t0);
            dst[x+1] = saturate_cast<uchar>(t1);
2199

2200 2201
            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;
2202

2203 2204 2205
            dst[x+2] = saturate_cast<uchar>(t0);
            dst[x+3] = saturate_cast<uchar>(t1);
        }
V
Victoria Zhislina 已提交
2206
        #endif
2207

2208 2209 2210 2211
        for( ; x < size.width; x++ )
        {
            float t0 = CV_8TO32F(src1[x])*alpha + CV_8TO32F(src2[x])*beta + gamma;
            dst[x] = saturate_cast<uchar>(t0);
2212 2213 2214 2215
        }
    }
}

2216 2217
static void addWeighted8s( const schar* src1, size_t step1, const schar* src2, size_t step2,
                           schar* dst, size_t step, Size sz, void* scalars )
2218
{
2219
    addWeighted_<schar, float>(src1, step1, src2, step2, dst, step, sz, scalars);
2220 2221
}

2222 2223
static void addWeighted16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                            ushort* dst, size_t step, Size sz, void* scalars )
2224
{
2225 2226
    addWeighted_<ushort, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2227

2228 2229
static void addWeighted16s( const short* src1, size_t step1, const short* src2, size_t step2,
                            short* dst, size_t step, Size sz, void* scalars )
2230
{
2231 2232
    addWeighted_<short, float>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2233

2234 2235
static void addWeighted32s( const int* src1, size_t step1, const int* src2, size_t step2,
                            int* dst, size_t step, Size sz, void* scalars )
2236
{
2237
    addWeighted_<int, double>(src1, step1, src2, step2, dst, step, sz, scalars);
2238 2239
}

2240 2241
static void addWeighted32f( const float* src1, size_t step1, const float* src2, size_t step2,
                            float* dst, size_t step, Size sz, void* scalars )
2242
{
2243 2244
    addWeighted_<float, double>(src1, step1, src2, step2, dst, step, sz, scalars);
}
2245

2246 2247 2248 2249 2250
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
2251

2252
static BinaryFunc* getAddWeightedTab()
2253
{
2254 2255 2256 2257 2258 2259 2260 2261 2262
    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;
}
2263

2264
}
2265

2266
void cv::addWeighted( InputArray src1, double alpha, InputArray src2,
2267 2268 2269
                      double beta, double gamma, OutputArray dst, int dtype )
{
    double scalars[] = {alpha, beta, gamma};
2270
    arithm_op(src1, src2, dst, noArray(), dtype, getAddWeightedTab(), true, scalars, OCL_OP_ADDW);
2271 2272
}

2273

2274
/****************************************************************************************\
2275
*                                          compare                                       *
2276 2277
\****************************************************************************************/

2278
namespace cv
2279 2280
{

2281 2282 2283
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)
2284
{
2285 2286 2287
    step1 /= sizeof(src1[0]);
    step2 /= sizeof(src2[0]);
    if( code == CMP_GE || code == CMP_LT )
2288
    {
2289 2290 2291
        std::swap(src1, src2);
        std::swap(step1, step2);
        code = code == CMP_GE ? CMP_LE : CMP_GT;
2292
    }
2293

2294
    if( code == CMP_GT || code == CMP_LE )
2295
    {
2296 2297 2298 2299
        int m = code == CMP_GT ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2300
            #if CV_ENABLE_UNROLLED
2301 2302 2303 2304 2305 2306 2307 2308 2309 2310
            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
2311
            #endif
2312 2313
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2314
               }
2315
    }
2316
    else if( code == CMP_EQ || code == CMP_NE )
2317
    {
2318 2319 2320 2321
        int m = code == CMP_EQ ? 0 : 255;
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
        {
            int x = 0;
2322
            #if CV_ENABLE_UNROLLED
2323 2324 2325 2326 2327 2328 2329 2330 2331 2332
            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
2333
            #endif
2334 2335 2336
            for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
2337
    }
2338
}
2339

K
kdrobnyh 已提交
2340 2341 2342 2343 2344 2345 2346 2347 2348 2349 2350
#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
2351

2352 2353
static void cmp8u(const uchar* src1, size_t step1, const uchar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2354
{
K
kdrobnyh 已提交
2355 2356 2357 2358 2359 2360 2361 2362 2363
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  >= 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
        if( ippiCompare_8u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op) >= 0 )
            return;
    }
#endif
2364
  //vz optimized  cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2365
    int code = *(int*)_cmpop;
2366 2367 2368 2369 2370 2371 2372 2373 2374 2375 2376 2377 2378 2379 2380
    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;
2381 2382
            #if CV_SSE2
            if( USE_SSE2 ){
2383 2384
                __m128i m128 = code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
                __m128i c128 = _mm_set1_epi8 (-128);
2385 2386 2387 2388 2389 2390 2391 2392 2393 2394 2395 2396 2397
                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);

                }
            }
2398 2399
           #endif

2400
            for( ; x < size.width; x++ ){
2401
                dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2402
            }
2403 2404 2405 2406 2407
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2408
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2409 2410
        {
            int x = 0;
2411 2412
            #if CV_SSE2
            if( USE_SSE2 ){
2413
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi8 (-1);
2414 2415 2416 2417 2418 2419 2420 2421
                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);
                }
            }
2422 2423 2424 2425 2426
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2427 2428
}

2429 2430
static void cmp8s(const schar* src1, size_t step1, const schar* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2431
{
2432
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2433 2434
}

2435 2436
static void cmp16u(const ushort* src1, size_t step1, const ushort* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2437
{
K
kdrobnyh 已提交
2438 2439 2440 2441 2442 2443 2444 2445 2446
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  >= 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
        if( ippiCompare_16u_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op) >= 0 )
            return;
    }
#endif
2447
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2448 2449
}

2450 2451
static void cmp16s(const short* src1, size_t step1, const short* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2452
{
K
kdrobnyh 已提交
2453 2454 2455 2456 2457 2458 2459 2460 2461
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  > 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
        if( ippiCompare_16s_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op) >= 0 )
            return;
    }
#endif
2462 2463
   //vz optimized cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);

2464
    int code = *(int*)_cmpop;
2465 2466 2467 2468 2469 2470 2471 2472 2473 2474 2475 2476 2477 2478 2479
    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;
2480 2481
            #if CV_SSE2
            if( USE_SSE2){//
2482
                __m128i m128 =  code == CMP_GT ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2483 2484 2485 2486 2487 2488 2489 2490 2491 2492 2493 2494 2495 2496 2497 2498 2499 2500 2501 2502 2503 2504
                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;
                }
            }
2505 2506
           #endif

2507
            for( ; x < size.width; x++ ){
2508
                 dst[x] = (uchar)(-(src1[x] > src2[x]) ^ m);
2509
            }
2510 2511 2512 2513 2514
        }
    }
    else if( code == CMP_EQ || code == CMP_NE )
    {
        int m = code == CMP_EQ ? 0 : 255;
2515
        for( ; size.height--; src1 += step1, src2 += step2, dst += step )
2516 2517
        {
            int x = 0;
2518 2519
            #if CV_SSE2
            if( USE_SSE2 ){
2520
                __m128i m128 =  code == CMP_EQ ? _mm_setzero_si128() : _mm_set1_epi16 (-1);
2521 2522 2523 2524 2525 2526 2527 2528 2529 2530 2531 2532 2533 2534 2535 2536 2537 2538 2539 2540 2541 2542
                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;
                }
            }
2543 2544 2545 2546 2547
           #endif
           for( ; x < size.width; x++ )
                dst[x] = (uchar)(-(src1[x] == src2[x]) ^ m);
        }
    }
2548 2549
}

2550 2551 2552 2553 2554
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);
}
2555

2556 2557
static void cmp32f(const float* src1, size_t step1, const float* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2558
{
K
kdrobnyh 已提交
2559 2560 2561 2562 2563 2564 2565 2566 2567
#if ARITHM_USE_IPP
    IppCmpOp op = convert_cmp(*(int *)_cmpop);
    if( op  >= 0 )
    {
        fixSteps(size, sizeof(dst[0]), step1, step2, step);
        if( ippiCompare_32f_C1R(src1, (int)step1, src2, (int)step2, dst, (int)step, (IppiSize&)size, op) >= 0 )
            return;
    }
#endif
2568 2569
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
}
2570

2571 2572
static void cmp64f(const double* src1, size_t step1, const double* src2, size_t step2,
                  uchar* dst, size_t step, Size size, void* _cmpop)
2573
{
2574
    cmp_(src1, step1, src2, step2, dst, step, size, *(int*)_cmpop);
2575 2576
}

2577
static BinaryFunc getCmpFunc(int depth)
2578
{
2579 2580 2581 2582 2583 2584 2585 2586
    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
    };
2587

2588 2589
    return cmpTab[depth];
}
2590

2591
static double getMinVal(int depth)
2592
{
2593 2594 2595
    static const double tab[] = {0, -128, 0, -32768, INT_MIN, -FLT_MAX, -DBL_MAX, 0};
    return tab[depth];
}
2596

2597
static double getMaxVal(int depth)
2598
{
2599 2600 2601
    static const double tab[] = {255, 127, 65535, 32767, INT_MAX, FLT_MAX, DBL_MAX, 0};
    return tab[depth];
}
2602

I
Ilya Lavrenov 已提交
2603 2604 2605 2606 2607 2608 2609 2610 2611 2612 2613 2614 2615 2616 2617 2618 2619
static bool ocl_compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op)
{
    if ( !((_src1.isMat() || _src1.isUMat()) && (_src2.isMat() || _src2.isUMat())) )
        return false;

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

    const char * const operationMap[] = { "==", ">", ">=", "<", "<=", "!=" };
    ocl::Kernel k("KF", ocl::core::arithm_oclsrc,
                  format("-D BINARY_OP -D srcT1=%s -D workT=srcT1"
                         " -D OP_CMP -D CMP_OPERATOR=%s%s",
                         ocl::typeToStr(CV_MAKE_TYPE(depth, 1)),
                         operationMap[op],
                         doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
I
Ilya Lavrenov 已提交
2620 2621 2622 2623 2624 2625 2626 2627 2628 2629
    if (k.empty())
        return false;

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

    _dst.create(size, CV_8UC(cn));
    UMat dst = _dst.getUMat();
I
Ilya Lavrenov 已提交
2630 2631 2632 2633 2634 2635 2636 2637 2638

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

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

2639 2640
}

2641
void cv::compare(InputArray _src1, InputArray _src2, OutputArray _dst, int op)
2642 2643 2644
{
    CV_Assert( op == CMP_LT || op == CMP_LE || op == CMP_EQ ||
               op == CMP_NE || op == CMP_GE || op == CMP_GT );
2645

2646
    if (ocl::useOpenCL() && _src1.dims() <= 2 && _src2.dims() <= 2 && _dst.isUMat() &&
2647
            ocl_compare(_src1, _src2, _dst, op))
I
Ilya Lavrenov 已提交
2648 2649
        return;

2650 2651
    int kind1 = _src1.kind(), kind2 = _src2.kind();
    Mat src1 = _src1.getMat(), src2 = _src2.getMat();
2652

2653
    if( kind1 == kind2 && src1.dims <= 2 && src2.dims <= 2 && src1.size() == src2.size() && src1.type() == src2.type() )
2654
    {
2655 2656
        int cn = src1.channels();
        _dst.create(src1.size(), CV_8UC(cn));
2657 2658
        Mat dst = _dst.getMat();
        Size sz = getContinuousSize(src1, src2, dst, src1.channels());
2659
        getCmpFunc(src1.depth())(src1.data, src1.step, src2.data, src2.step, dst.data, dst.step, sz, &op);
2660 2661
        return;
    }
2662

2663
    bool haveScalar = false;
2664

2665
    if( (kind1 == _InputArray::MATX) + (kind2 == _InputArray::MATX) == 1 ||
2666 2667 2668
        src1.size != src2.size || src1.type() != src2.type() )
    {
        if( checkScalar(src1, src2.type(), kind1, kind2) )
2669
        {
2670 2671 2672 2673 2674 2675 2676 2677 2678 2679 2680
            // src1 is a scalar; swap it with src2
            swap(src1, src2);
            op = op == CMP_LT ? CMP_GT : op == CMP_LE ? CMP_GE :
                op == CMP_GE ? CMP_LE : op == CMP_GT ? CMP_LT : op;
        }
        else if( !checkScalar(src2, src1.type(), kind2, kind1) )
            CV_Error( CV_StsUnmatchedSizes,
                     "The operation is neither 'array op array' (where arrays have the same size and the same type), "
                     "nor 'array op scalar', nor 'scalar op array'" );
        haveScalar = true;
    }
2681

2682

2683
    int cn = src1.channels(), depth1 = src1.depth(), depth2 = src2.depth();
2684

2685 2686 2687
    _dst.create(src1.dims, src1.size, CV_8UC(cn));
    src1 = src1.reshape(1); src2 = src2.reshape(1);
    Mat dst = _dst.getMat().reshape(1);
2688

2689 2690
    size_t esz = src1.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
2691
    BinaryFunc func = getCmpFunc(depth1);
2692

2693
    if( !haveScalar )
2694
    {
2695 2696
        const Mat* arrays[] = { &src1, &src2, &dst, 0 };
        uchar* ptrs[3];
2697

2698 2699
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size;
2700

2701 2702
        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 );
2703
    }
2704
    else
2705
    {
2706 2707
        const Mat* arrays[] = { &src1, &dst, 0 };
        uchar* ptrs[2];
2708

2709 2710
        NAryMatIterator it(arrays, ptrs);
        size_t total = it.size, blocksize = std::min(total, blocksize0);
2711

2712 2713 2714 2715 2716 2717
        AutoBuffer<uchar> _buf(blocksize*esz);
        uchar *buf = _buf;

        if( depth1 > CV_32S )
            convertAndUnrollScalar( src2, depth1, buf, blocksize );
        else
2718
        {
2719 2720 2721 2722 2723 2724 2725
            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;
            }
2726

2727 2728 2729 2730 2731
            if( fval > getMaxVal(depth1) )
            {
                dst = Scalar::all(op == CMP_LT || op == CMP_LE || op == CMP_NE ? 255 : 0);
                return;
            }
2732

2733 2734 2735 2736 2737 2738 2739 2740 2741 2742 2743 2744 2745 2746 2747
            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);
        }
2748

2749
        for( size_t i = 0; i < it.nplanes; i++, ++it )
2750
        {
2751 2752
            for( size_t j = 0; j < total; j += blocksize )
            {
2753
                int bsz = (int)MIN(total - j, blocksize);
2754 2755 2756 2757 2758
                func( ptrs[0], 0, buf, 0, ptrs[1], 0, Size(bsz, 1), &op);
                ptrs[0] += bsz*esz;
                ptrs[1] += bsz;
            }
        }
2759
    }
2760
}
2761

2762 2763 2764
/****************************************************************************************\
*                                        inRange                                         *
\****************************************************************************************/
2765

2766 2767
namespace cv
{
2768

2769 2770 2771 2772 2773 2774 2775 2776
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]);
2777

2778
    for( ; size.height--; src1 += step1, src2 += step2, src3 += step3, dst += step )
V
Vadim Pisarevsky 已提交
2779
    {
2780
        int x = 0;
2781
        #if CV_ENABLE_UNROLLED
2782
        for( ; x <= size.width - 4; x += 4 )
V
Vadim Pisarevsky 已提交
2783
        {
2784 2785 2786 2787 2788 2789 2790
            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
2791
        }
V
Victoria Zhislina 已提交
2792
        #endif
2793 2794
        for( ; x < size.width; x++ )
            dst[x] = (uchar)-(src2[x] <= src1[x] && src1[x] <= src3[x]);
V
Vadim Pisarevsky 已提交
2795
    }
2796 2797
}

2798

2799 2800
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)
2801
{
2802 2803
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2804

2805 2806
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)
2807
{
2808 2809
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2810

2811 2812
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)
2813
{
2814 2815
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2816

2817 2818 2819 2820
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);
2821 2822
}

2823 2824
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)
2825
{
2826 2827
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
}
2828

2829 2830 2831 2832
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);
2833 2834
}

2835 2836
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)
2837
{
2838
    inRange_(src1, step1, src2, step2, src3, step3, dst, step, size);
2839
}
2840

2841 2842 2843 2844 2845 2846 2847 2848 2849 2850 2851 2852 2853 2854 2855 2856
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];
2857

2858 2859 2860 2861
    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
2862
    }
2863
}
2864

2865 2866
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 );
2867

2868
static InRangeFunc getInRangeFunc(int depth)
2869
{
2870 2871 2872 2873 2874 2875 2876 2877 2878
    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];
}
2879

I
Ilya Lavrenov 已提交
2880 2881 2882 2883 2884 2885 2886 2887 2888 2889 2890 2891 2892 2893 2894 2895 2896 2897 2898 2899 2900 2901 2902 2903 2904 2905 2906 2907 2908 2909 2910 2911 2912 2913 2914 2915 2916 2917 2918 2919 2920 2921 2922 2923 2924 2925 2926 2927 2928 2929 2930 2931 2932 2933 2934 2935 2936 2937 2938 2939 2940 2941 2942 2943 2944 2945 2946 2947 2948 2949 2950 2951 2952 2953 2954 2955 2956 2957 2958 2959 2960 2961 2962 2963 2964 2965 2966 2967 2968 2969 2970 2971 2972 2973 2974 2975 2976 2977 2978 2979 2980 2981 2982 2983 2984 2985
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);
}

2986 2987
}

2988 2989
void cv::inRange(InputArray _src, InputArray _lowerb,
                 InputArray _upperb, OutputArray _dst)
2990
{
I
Ilya Lavrenov 已提交
2991 2992 2993 2994
    if (ocl::useOpenCL() && _src.dims() <= 2 && _lowerb.dims() <= 2 &&
            _upperb.dims() <= 2 && _dst.isUMat() && ocl_inRange(_src, _lowerb, _upperb, _dst))
        return;

2995 2996
    int skind = _src.kind(), lkind = _lowerb.kind(), ukind = _upperb.kind();
    Mat src = _src.getMat(), lb = _lowerb.getMat(), ub = _upperb.getMat();
2997

2998
    bool lbScalar = false, ubScalar = false;
2999

3000
    if( (lkind == _InputArray::MATX && skind != _InputArray::MATX) ||
3001 3002 3003 3004 3005 3006 3007
        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;
    }
3008

3009
    if( (ukind == _InputArray::MATX && skind != _InputArray::MATX) ||
3010 3011 3012 3013 3014 3015 3016
        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;
    }
3017

I
Ilya Lavrenov 已提交
3018
    CV_Assert(lbScalar == ubScalar);
3019

3020
    int cn = src.channels(), depth = src.depth();
3021

3022 3023
    size_t esz = src.elemSize();
    size_t blocksize0 = (size_t)(BLOCK_SIZE + esz-1)/esz;
3024

I
Ilya Lavrenov 已提交
3025
    _dst.create(src.dims, src.size, CV_8UC1);
3026
    Mat dst = _dst.getMat();
3027
    InRangeFunc func = getInRangeFunc(depth);
3028

3029 3030 3031
    const Mat* arrays_sc[] = { &src, &dst, 0 };
    const Mat* arrays_nosc[] = { &src, &dst, &lb, &ub, 0 };
    uchar* ptrs[4];
3032

3033 3034
    NAryMatIterator it(lbScalar && ubScalar ? arrays_sc : arrays_nosc, ptrs);
    size_t total = it.size, blocksize = std::min(total, blocksize0);
3035

3036 3037 3038
    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);
3039

3040 3041 3042 3043
    if( lbScalar && ubScalar )
    {
        lbuf = buf;
        ubuf = buf = alignPtr(buf + blocksize*esz, 16);
3044

3045 3046
        CV_Assert( lb.type() == ub.type() );
        int scdepth = lb.depth();
3047

3048 3049 3050 3051
        if( scdepth != depth && depth < CV_32S )
        {
            int* ilbuf = (int*)alignPtr(buf + blocksize*esz, 16);
            int* iubuf = ilbuf + cn;
3052

3053 3054 3055
            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);
3056
            int minval = cvRound(getMinVal(depth)), maxval = cvRound(getMaxVal(depth));
3057

3058 3059 3060 3061 3062 3063 3064 3065
            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);
        }
3066

3067 3068 3069
        convertAndUnrollScalar( lb, src.type(), lbuf, blocksize );
        convertAndUnrollScalar( ub, src.type(), ubuf, blocksize );
    }
3070

3071
    for( size_t i = 0; i < it.nplanes; i++, ++it )
V
Vadim Pisarevsky 已提交
3072
    {
3073 3074
        for( size_t j = 0; j < total; j += blocksize )
        {
3075
            int bsz = (int)MIN(total - j, blocksize);
3076 3077 3078 3079 3080 3081 3082 3083 3084 3085 3086 3087 3088 3089
            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));
3090
            if( cn > 1 )
3091 3092 3093 3094
                inRangeReduce(mbuf, ptrs[1], bsz, cn);
            ptrs[0] += delta;
            ptrs[1] += bsz;
        }
V
Vadim Pisarevsky 已提交
3095
    }
3096 3097 3098 3099 3100 3101 3102 3103 3104 3105
}

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

CV_IMPL void
cvNot( const CvArr* srcarr, CvArr* dstarr )
{
    cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
3106
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3107 3108 3109 3110 3111 3112 3113 3114 3115
    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;
3116
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3117 3118 3119 3120 3121
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
    cv::bitwise_and( src1, src2, dst, mask );
}

3122

3123 3124 3125 3126 3127
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;
3128
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3129 3130 3131 3132 3133 3134 3135 3136 3137 3138 3139
    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;
3140
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3141 3142 3143 3144 3145 3146 3147 3148 3149 3150
    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;
3151
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3152 3153
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3154
    cv::bitwise_and( src, (const cv::Scalar&)s, dst, mask );
3155 3156 3157 3158 3159 3160 3161
}


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;
3162
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3163 3164
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3165
    cv::bitwise_or( src, (const cv::Scalar&)s, dst, mask );
3166 3167 3168 3169 3170 3171 3172
}


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;
3173
    CV_Assert( src.size == dst.size && src.type() == dst.type() );
3174 3175
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3176
    cv::bitwise_xor( src, (const cv::Scalar&)s, dst, mask );
3177 3178
}

3179

3180 3181 3182 3183
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;
3184
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3185 3186
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3187
    cv::add( src1, src2, dst, mask, dst.type() );
3188 3189
}

3190

3191 3192 3193 3194
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;
3195
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3196 3197
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3198
    cv::subtract( src1, src2, dst, mask, dst.type() );
3199 3200
}

3201

3202 3203 3204 3205
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;
3206
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3207 3208
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3209
    cv::add( src1, (const cv::Scalar&)value, dst, mask, dst.type() );
3210 3211
}

3212

3213 3214 3215 3216
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;
3217
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
3218 3219
    if( maskarr )
        mask = cv::cvarrToMat(maskarr);
3220
    cv::subtract( (const cv::Scalar&)value, src1, dst, mask, dst.type() );
3221 3222
}

3223

3224 3225 3226 3227 3228
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);
3229 3230
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::multiply( src1, src2, dst, scale, dst.type() );
3231 3232
}

3233

3234 3235 3236 3237 3238
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;
3239
    CV_Assert( src2.size == dst.size && src2.channels() == dst.channels() );
3240 3241

    if( srcarr1 )
3242
        cv::divide( cv::cvarrToMat(srcarr1), src2, dst, scale, dst.type() );
3243
    else
3244
        cv::divide( scale, src2, dst, dst.type() );
3245 3246 3247 3248 3249 3250 3251 3252 3253 3254
}


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);
3255 3256
    CV_Assert( src1.size == dst.size && src1.channels() == dst.channels() );
    cv::addWeighted( src1, alpha, src2, beta, gamma, dst, dst.type() );
3257 3258 3259 3260 3261 3262 3263
}


CV_IMPL  void
cvAbsDiff( const CvArr* srcarr1, const CvArr* srcarr2, CvArr* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3264
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3265 3266 3267 3268 3269 3270 3271 3272 3273

    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);
3274
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3275

3276
    cv::absdiff( src1, (const cv::Scalar&)scalar, dst );
3277 3278
}

3279

3280 3281 3282 3283 3284
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);
3285
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3286 3287 3288 3289

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

3290

3291 3292 3293 3294
CV_IMPL void
cvInRangeS( const void* srcarr1, CvScalar lowerb, CvScalar upperb, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3295
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3296

3297
    cv::inRange( src1, (const cv::Scalar&)lowerb, (const cv::Scalar&)upperb, dst );
3298 3299 3300 3301 3302 3303 3304
}


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);
3305
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3306 3307 3308 3309 3310 3311 3312 3313 3314

    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);
3315
    CV_Assert( src1.size == dst.size && dst.type() == CV_8U );
3316 3317 3318 3319 3320 3321 3322 3323 3324

    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);
3325
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3326 3327 3328 3329 3330 3331 3332 3333 3334

    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);
3335
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3336 3337 3338 3339

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

3340

3341 3342 3343 3344
CV_IMPL void
cvMinS( const void* srcarr1, double value, void* dstarr )
{
    cv::Mat src1 = cv::cvarrToMat(srcarr1), dst = cv::cvarrToMat(dstarr);
3345
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3346 3347 3348 3349 3350 3351 3352 3353 3354

    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);
3355
    CV_Assert( src1.size == dst.size && src1.type() == dst.type() );
3356 3357 3358 3359 3360

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

/* End of file. */