operations.hpp 21 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 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 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594
/*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.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Copyright (C) 2015, Itseez Inc., all rights reserved.
// 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*/

#ifndef OPENCV_CORE_OPERATIONS_HPP
#define OPENCV_CORE_OPERATIONS_HPP

#ifndef __cplusplus
#  error operations.hpp header must be compiled as C++
#endif

#include <cstdio>

#if defined(__GNUC__) || defined(__clang__) // at least GCC 3.1+, clang 3.5+
#  if defined(__MINGW_PRINTF_FORMAT)  // https://sourceforge.net/p/mingw-w64/wiki2/gnu%20printf/.
#    define CV_FORMAT_PRINTF(string_idx, first_to_check) __attribute__ ((format (__MINGW_PRINTF_FORMAT, string_idx, first_to_check)))
#  else
#    define CV_FORMAT_PRINTF(string_idx, first_to_check) __attribute__ ((format (printf, string_idx, first_to_check)))
#  endif
#else
#  define CV_FORMAT_PRINTF(A, B)
#endif

//! @cond IGNORED

namespace cv
{

////////////////////////////// Matx methods depending on core API /////////////////////////////

namespace internal
{

template<typename _Tp, int m, int n> struct Matx_FastInvOp
{
    bool operator()(const Matx<_Tp, m, n>& a, Matx<_Tp, n, m>& b, int method) const
    {
        return invert(a, b, method) != 0;
    }
};

template<typename _Tp, int m> struct Matx_FastInvOp<_Tp, m, m>
{
    bool operator()(const Matx<_Tp, m, m>& a, Matx<_Tp, m, m>& b, int method) const
    {
        if (method == DECOMP_LU || method == DECOMP_CHOLESKY)
        {
            Matx<_Tp, m, m> temp = a;

            // assume that b is all 0's on input => make it a unity matrix
            for (int i = 0; i < m; i++)
                b(i, i) = (_Tp)1;

            if (method == DECOMP_CHOLESKY)
                return Cholesky(temp.val, m*sizeof(_Tp), m, b.val, m*sizeof(_Tp), m);

            return LU(temp.val, m*sizeof(_Tp), m, b.val, m*sizeof(_Tp), m) != 0;
        }
        else
        {
            return invert(a, b, method) != 0;
        }
    }
};

template<typename _Tp> struct Matx_FastInvOp<_Tp, 2, 2>
{
    bool operator()(const Matx<_Tp, 2, 2>& a, Matx<_Tp, 2, 2>& b, int /*method*/) const
    {
        _Tp d = (_Tp)determinant(a);
        if (d == 0)
            return false;
        d = 1/d;
        b(1,1) = a(0,0)*d;
        b(0,0) = a(1,1)*d;
        b(0,1) = -a(0,1)*d;
        b(1,0) = -a(1,0)*d;
        return true;
    }
};

template<typename _Tp> struct Matx_FastInvOp<_Tp, 3, 3>
{
    bool operator()(const Matx<_Tp, 3, 3>& a, Matx<_Tp, 3, 3>& b, int /*method*/) const
    {
        _Tp d = (_Tp)determinant(a);
        if (d == 0)
            return false;
        d = 1/d;
        b(0,0) = (a(1,1) * a(2,2) - a(1,2) * a(2,1)) * d;
        b(0,1) = (a(0,2) * a(2,1) - a(0,1) * a(2,2)) * d;
        b(0,2) = (a(0,1) * a(1,2) - a(0,2) * a(1,1)) * d;

        b(1,0) = (a(1,2) * a(2,0) - a(1,0) * a(2,2)) * d;
        b(1,1) = (a(0,0) * a(2,2) - a(0,2) * a(2,0)) * d;
        b(1,2) = (a(0,2) * a(1,0) - a(0,0) * a(1,2)) * d;

        b(2,0) = (a(1,0) * a(2,1) - a(1,1) * a(2,0)) * d;
        b(2,1) = (a(0,1) * a(2,0) - a(0,0) * a(2,1)) * d;
        b(2,2) = (a(0,0) * a(1,1) - a(0,1) * a(1,0)) * d;
        return true;
    }
};


template<typename _Tp, int m, int l, int n> struct Matx_FastSolveOp
{
    bool operator()(const Matx<_Tp, m, l>& a, const Matx<_Tp, m, n>& b,
                    Matx<_Tp, l, n>& x, int method) const
    {
        return cv::solve(a, b, x, method);
    }
};

template<typename _Tp, int m, int n> struct Matx_FastSolveOp<_Tp, m, m, n>
{
    bool operator()(const Matx<_Tp, m, m>& a, const Matx<_Tp, m, n>& b,
                    Matx<_Tp, m, n>& x, int method) const
    {
        if (method == DECOMP_LU || method == DECOMP_CHOLESKY)
        {
            Matx<_Tp, m, m> temp = a;
            x = b;
            if( method == DECOMP_CHOLESKY )
                return Cholesky(temp.val, m*sizeof(_Tp), m, x.val, n*sizeof(_Tp), n);

            return LU(temp.val, m*sizeof(_Tp), m, x.val, n*sizeof(_Tp), n) != 0;
        }
        else
        {
            return cv::solve(a, b, x, method);
        }
    }
};

template<typename _Tp> struct Matx_FastSolveOp<_Tp, 2, 2, 1>
{
    bool operator()(const Matx<_Tp, 2, 2>& a, const Matx<_Tp, 2, 1>& b,
                    Matx<_Tp, 2, 1>& x, int) const
    {
        _Tp d = (_Tp)determinant(a);
        if (d == 0)
            return false;
        d = 1/d;
        x(0) = (b(0)*a(1,1) - b(1)*a(0,1))*d;
        x(1) = (b(1)*a(0,0) - b(0)*a(1,0))*d;
        return true;
    }
};

template<typename _Tp> struct Matx_FastSolveOp<_Tp, 3, 3, 1>
{
    bool operator()(const Matx<_Tp, 3, 3>& a, const Matx<_Tp, 3, 1>& b,
                    Matx<_Tp, 3, 1>& x, int) const
    {
        _Tp d = (_Tp)determinant(a);
        if (d == 0)
            return false;
        d = 1/d;
        x(0) = d*(b(0)*(a(1,1)*a(2,2) - a(1,2)*a(2,1)) -
                a(0,1)*(b(1)*a(2,2) - a(1,2)*b(2)) +
                a(0,2)*(b(1)*a(2,1) - a(1,1)*b(2)));

        x(1) = d*(a(0,0)*(b(1)*a(2,2) - a(1,2)*b(2)) -
                b(0)*(a(1,0)*a(2,2) - a(1,2)*a(2,0)) +
                a(0,2)*(a(1,0)*b(2) - b(1)*a(2,0)));

        x(2) = d*(a(0,0)*(a(1,1)*b(2) - b(1)*a(2,1)) -
                a(0,1)*(a(1,0)*b(2) - b(1)*a(2,0)) +
                b(0)*(a(1,0)*a(2,1) - a(1,1)*a(2,0)));
        return true;
    }
};

} // internal

template<typename _Tp, int m, int n> inline
Matx<_Tp,m,n> Matx<_Tp,m,n>::randu(_Tp a, _Tp b)
{
    Matx<_Tp,m,n> M;
    cv::randu(M, Scalar(a), Scalar(b));
    return M;
}

template<typename _Tp, int m, int n> inline
Matx<_Tp,m,n> Matx<_Tp,m,n>::randn(_Tp a, _Tp b)
{
    Matx<_Tp,m,n> M;
    cv::randn(M, Scalar(a), Scalar(b));
    return M;
}

template<typename _Tp, int m, int n> inline
Matx<_Tp, n, m> Matx<_Tp, m, n>::inv(int method, bool *p_is_ok /*= NULL*/) const
{
    Matx<_Tp, n, m> b;
    bool ok = cv::internal::Matx_FastInvOp<_Tp, m, n>()(*this, b, method);
    if (p_is_ok) *p_is_ok = ok;
    return ok ? b : Matx<_Tp, n, m>::zeros();
}

template<typename _Tp, int m, int n> template<int l> inline
Matx<_Tp, n, l> Matx<_Tp, m, n>::solve(const Matx<_Tp, m, l>& rhs, int method) const
{
    Matx<_Tp, n, l> x;
    bool ok = cv::internal::Matx_FastSolveOp<_Tp, m, n, l>()(*this, rhs, x, method);
    return ok ? x : Matx<_Tp, n, l>::zeros();
}



////////////////////////// Augmenting algebraic & logical operations //////////////////////////

#define CV_MAT_AUG_OPERATOR1(op, cvop, A, B) \
    static inline A& operator op (A& a, const B& b) { cvop; return a; }

#define CV_MAT_AUG_OPERATOR(op, cvop, A, B)   \
    CV_MAT_AUG_OPERATOR1(op, cvop, A, B)      \
    CV_MAT_AUG_OPERATOR1(op, cvop, const A, B)

#define CV_MAT_AUG_OPERATOR_T(op, cvop, A, B)                   \
    template<typename _Tp> CV_MAT_AUG_OPERATOR1(op, cvop, A, B) \
    template<typename _Tp> CV_MAT_AUG_OPERATOR1(op, cvop, const A, B)

#define CV_MAT_AUG_OPERATOR_TN(op, cvop, A)                                \
    template<typename _Tp, int m, int n> static inline A& operator op (A& a, const Matx<_Tp,m,n>& b) { cvop; return a; } \
    template<typename _Tp, int m, int n> static inline const A& operator op (const A& a, const Matx<_Tp,m,n>& b) { cvop; return a; }

CV_MAT_AUG_OPERATOR  (+=, cv::add(a,b,a), Mat, Mat)
CV_MAT_AUG_OPERATOR  (+=, cv::add(a,b,a), Mat, Scalar)
CV_MAT_AUG_OPERATOR_T(+=, cv::add(a,b,a), Mat_<_Tp>, Mat)
CV_MAT_AUG_OPERATOR_T(+=, cv::add(a,b,a), Mat_<_Tp>, Scalar)
CV_MAT_AUG_OPERATOR_T(+=, cv::add(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
CV_MAT_AUG_OPERATOR_TN(+=, cv::add(a,Mat(b),a), Mat)
CV_MAT_AUG_OPERATOR_TN(+=, cv::add(a,Mat(b),a), Mat_<_Tp>)

CV_MAT_AUG_OPERATOR  (-=, cv::subtract(a,b,a), Mat, Mat)
CV_MAT_AUG_OPERATOR  (-=, cv::subtract(a,b,a), Mat, Scalar)
CV_MAT_AUG_OPERATOR_T(-=, cv::subtract(a,b,a), Mat_<_Tp>, Mat)
CV_MAT_AUG_OPERATOR_T(-=, cv::subtract(a,b,a), Mat_<_Tp>, Scalar)
CV_MAT_AUG_OPERATOR_T(-=, cv::subtract(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
CV_MAT_AUG_OPERATOR_TN(-=, cv::subtract(a,Mat(b),a), Mat)
CV_MAT_AUG_OPERATOR_TN(-=, cv::subtract(a,Mat(b),a), Mat_<_Tp>)

CV_MAT_AUG_OPERATOR  (*=, cv::gemm(a, b, 1, Mat(), 0, a, 0), Mat, Mat)
CV_MAT_AUG_OPERATOR_T(*=, cv::gemm(a, b, 1, Mat(), 0, a, 0), Mat_<_Tp>, Mat)
CV_MAT_AUG_OPERATOR_T(*=, cv::gemm(a, b, 1, Mat(), 0, a, 0), Mat_<_Tp>, Mat_<_Tp>)
CV_MAT_AUG_OPERATOR  (*=, a.convertTo(a, -1, b), Mat, double)
CV_MAT_AUG_OPERATOR_T(*=, a.convertTo(a, -1, b), Mat_<_Tp>, double)
CV_MAT_AUG_OPERATOR_TN(*=, cv::gemm(a, Mat(b), 1, Mat(), 0, a, 0), Mat)
CV_MAT_AUG_OPERATOR_TN(*=, cv::gemm(a, Mat(b), 1, Mat(), 0, a, 0), Mat_<_Tp>)

CV_MAT_AUG_OPERATOR  (/=, cv::divide(a,b,a), Mat, Mat)
CV_MAT_AUG_OPERATOR_T(/=, cv::divide(a,b,a), Mat_<_Tp>, Mat)
CV_MAT_AUG_OPERATOR_T(/=, cv::divide(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
CV_MAT_AUG_OPERATOR  (/=, a.convertTo((Mat&)a, -1, 1./b), Mat, double)
CV_MAT_AUG_OPERATOR_T(/=, a.convertTo((Mat&)a, -1, 1./b), Mat_<_Tp>, double)
CV_MAT_AUG_OPERATOR_TN(/=, cv::divide(a, Mat(b), a), Mat)
CV_MAT_AUG_OPERATOR_TN(/=, cv::divide(a, Mat(b), a), Mat_<_Tp>)

CV_MAT_AUG_OPERATOR  (&=, cv::bitwise_and(a,b,a), Mat, Mat)
CV_MAT_AUG_OPERATOR  (&=, cv::bitwise_and(a,b,a), Mat, Scalar)
CV_MAT_AUG_OPERATOR_T(&=, cv::bitwise_and(a,b,a), Mat_<_Tp>, Mat)
CV_MAT_AUG_OPERATOR_T(&=, cv::bitwise_and(a,b,a), Mat_<_Tp>, Scalar)
CV_MAT_AUG_OPERATOR_T(&=, cv::bitwise_and(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
CV_MAT_AUG_OPERATOR_TN(&=, cv::bitwise_and(a, Mat(b), a), Mat)
CV_MAT_AUG_OPERATOR_TN(&=, cv::bitwise_and(a, Mat(b), a), Mat_<_Tp>)

CV_MAT_AUG_OPERATOR  (|=, cv::bitwise_or(a,b,a), Mat, Mat)
CV_MAT_AUG_OPERATOR  (|=, cv::bitwise_or(a,b,a), Mat, Scalar)
CV_MAT_AUG_OPERATOR_T(|=, cv::bitwise_or(a,b,a), Mat_<_Tp>, Mat)
CV_MAT_AUG_OPERATOR_T(|=, cv::bitwise_or(a,b,a), Mat_<_Tp>, Scalar)
CV_MAT_AUG_OPERATOR_T(|=, cv::bitwise_or(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
CV_MAT_AUG_OPERATOR_TN(|=, cv::bitwise_or(a, Mat(b), a), Mat)
CV_MAT_AUG_OPERATOR_TN(|=, cv::bitwise_or(a, Mat(b), a), Mat_<_Tp>)

CV_MAT_AUG_OPERATOR  (^=, cv::bitwise_xor(a,b,a), Mat, Mat)
CV_MAT_AUG_OPERATOR  (^=, cv::bitwise_xor(a,b,a), Mat, Scalar)
CV_MAT_AUG_OPERATOR_T(^=, cv::bitwise_xor(a,b,a), Mat_<_Tp>, Mat)
CV_MAT_AUG_OPERATOR_T(^=, cv::bitwise_xor(a,b,a), Mat_<_Tp>, Scalar)
CV_MAT_AUG_OPERATOR_T(^=, cv::bitwise_xor(a,b,a), Mat_<_Tp>, Mat_<_Tp>)
CV_MAT_AUG_OPERATOR_TN(^=, cv::bitwise_xor(a, Mat(b), a), Mat)
CV_MAT_AUG_OPERATOR_TN(^=, cv::bitwise_xor(a, Mat(b), a), Mat_<_Tp>)

#undef CV_MAT_AUG_OPERATOR_TN
#undef CV_MAT_AUG_OPERATOR_T
#undef CV_MAT_AUG_OPERATOR
#undef CV_MAT_AUG_OPERATOR1



///////////////////////////////////////////// SVD /////////////////////////////////////////////

inline SVD::SVD() {}
inline SVD::SVD( InputArray m, int flags ) { operator ()(m, flags); }
inline void SVD::solveZ( InputArray m, OutputArray _dst )
{
    Mat mtx = m.getMat();
    SVD svd(mtx, (mtx.rows >= mtx.cols ? 0 : SVD::FULL_UV));
    _dst.create(svd.vt.cols, 1, svd.vt.type());
    Mat dst = _dst.getMat();
    svd.vt.row(svd.vt.rows-1).reshape(1,svd.vt.cols).copyTo(dst);
}

template<typename _Tp, int m, int n, int nm> inline void
    SVD::compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w, Matx<_Tp, m, nm>& u, Matx<_Tp, n, nm>& vt )
{
    CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector.");
    Mat _a(a, false), _u(u, false), _w(w, false), _vt(vt, false);
    SVD::compute(_a, _w, _u, _vt);
    CV_Assert(_w.data == (uchar*)&w.val[0] && _u.data == (uchar*)&u.val[0] && _vt.data == (uchar*)&vt.val[0]);
}

template<typename _Tp, int m, int n, int nm> inline void
SVD::compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w )
{
    CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector.");
    Mat _a(a, false), _w(w, false);
    SVD::compute(_a, _w);
    CV_Assert(_w.data == (uchar*)&w.val[0]);
}

template<typename _Tp, int m, int n, int nm, int nb> inline void
SVD::backSubst( const Matx<_Tp, nm, 1>& w, const Matx<_Tp, m, nm>& u,
                const Matx<_Tp, n, nm>& vt, const Matx<_Tp, m, nb>& rhs,
                Matx<_Tp, n, nb>& dst )
{
    CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector.");
    Mat _u(u, false), _w(w, false), _vt(vt, false), _rhs(rhs, false), _dst(dst, false);
    SVD::backSubst(_w, _u, _vt, _rhs, _dst);
    CV_Assert(_dst.data == (uchar*)&dst.val[0]);
}



/////////////////////////////////// Multiply-with-Carry RNG ///////////////////////////////////

inline RNG::RNG()              { state = 0xffffffff; }
inline RNG::RNG(uint64 _state) { state = _state ? _state : 0xffffffff; }

inline RNG::operator uchar()    { return (uchar)next(); }
inline RNG::operator schar()    { return (schar)next(); }
inline RNG::operator ushort()   { return (ushort)next(); }
inline RNG::operator short()    { return (short)next(); }
inline RNG::operator int()      { return (int)next(); }
inline RNG::operator unsigned() { return next(); }
inline RNG::operator float()    { return next()*2.3283064365386962890625e-10f; }
inline RNG::operator double()   { unsigned t = next(); return (((uint64)t << 32) | next()) * 5.4210108624275221700372640043497e-20; }

inline unsigned RNG::operator ()(unsigned N) { return (unsigned)uniform(0,N); }
inline unsigned RNG::operator ()()           { return next(); }

inline int    RNG::uniform(int a, int b)       { return a == b ? a : (int)(next() % (b - a) + a); }
inline float  RNG::uniform(float a, float b)   { return ((float)*this)*(b - a) + a; }
inline double RNG::uniform(double a, double b) { return ((double)*this)*(b - a) + a; }

inline bool RNG::operator ==(const RNG& other) const { return state == other.state; }

inline unsigned RNG::next()
{
    state = (uint64)(unsigned)state* /*CV_RNG_COEFF*/ 4164903690U + (unsigned)(state >> 32);
    return (unsigned)state;
}

//! returns the next uniformly-distributed random number of the specified type
template<typename _Tp> static inline _Tp randu()
{
  return (_Tp)theRNG();
}

///////////////////////////////// Formatted string generation /////////////////////////////////

/** @brief Returns a text string formatted using the printf-like expression.

The function acts like sprintf but forms and returns an STL string. It can be used to form an error
message in the Exception constructor.
@param fmt printf-compatible formatting specifiers.

**Note**:
|Type|Specifier|
|-|-|
|`const char*`|`%s`|
|`char`|`%c`|
|`float` / `double`|`%f`,`%g`|
|`int`, `long`, `long long`|`%d`, `%ld`, ``%lld`|
|`unsigned`, `unsigned long`, `unsigned long long`|`%u`, `%lu`, `%llu`|
|`uint64` -> `uintmax_t`, `int64` -> `intmax_t`|`%ju`, `%jd`|
|`size_t`|`%zu`|
 */
CV_EXPORTS String format( const char* fmt, ... ) CV_FORMAT_PRINTF(1, 2);

///////////////////////////////// Formatted output of cv::Mat /////////////////////////////////

static inline
Ptr<Formatted> format(InputArray mtx, Formatter::FormatType fmt)
{
    return Formatter::get(fmt)->format(mtx.getMat());
}

static inline
int print(Ptr<Formatted> fmtd, FILE* stream = stdout)
{
    int written = 0;
    fmtd->reset();
    for(const char* str = fmtd->next(); str; str = fmtd->next())
        written += fputs(str, stream);

    return written;
}

static inline
int print(const Mat& mtx, FILE* stream = stdout)
{
    return print(Formatter::get()->format(mtx), stream);
}

static inline
int print(const UMat& mtx, FILE* stream = stdout)
{
    return print(Formatter::get()->format(mtx.getMat(ACCESS_READ)), stream);
}

template<typename _Tp> static inline
int print(const std::vector<Point_<_Tp> >& vec, FILE* stream = stdout)
{
    return print(Formatter::get()->format(Mat(vec)), stream);
}

template<typename _Tp> static inline
int print(const std::vector<Point3_<_Tp> >& vec, FILE* stream = stdout)
{
    return print(Formatter::get()->format(Mat(vec)), stream);
}

template<typename _Tp, int m, int n> static inline
int print(const Matx<_Tp, m, n>& matx, FILE* stream = stdout)
{
    return print(Formatter::get()->format(cv::Mat(matx)), stream);
}

//! @endcond

/****************************************************************************************\
*                                  Auxiliary algorithms                                  *
\****************************************************************************************/

/** @brief Splits an element set into equivalency classes.

The generic function partition implements an \f$O(N^2)\f$ algorithm for splitting a set of \f$N\f$ elements
into one or more equivalency classes, as described in
<http://en.wikipedia.org/wiki/Disjoint-set_data_structure> . The function returns the number of
equivalency classes.
@param _vec Set of elements stored as a vector.
@param labels Output vector of labels. It contains as many elements as vec. Each label labels[i] is
a 0-based cluster index of `vec[i]`.
@param predicate Equivalence predicate (pointer to a boolean function of two arguments or an
instance of the class that has the method bool operator()(const _Tp& a, const _Tp& b) ). The
predicate returns true when the elements are certainly in the same class, and returns false if they
may or may not be in the same class.
@ingroup core_cluster
*/
template<typename _Tp, class _EqPredicate> int
partition( const std::vector<_Tp>& _vec, std::vector<int>& labels,
          _EqPredicate predicate=_EqPredicate())
{
    int i, j, N = (int)_vec.size();
    const _Tp* vec = &_vec[0];

    const int PARENT=0;
    const int RANK=1;

    std::vector<int> _nodes(N*2);
    int (*nodes)[2] = (int(*)[2])&_nodes[0];

    // The first O(N) pass: create N single-vertex trees
    for(i = 0; i < N; i++)
    {
        nodes[i][PARENT]=-1;
        nodes[i][RANK] = 0;
    }

    // The main O(N^2) pass: merge connected components
    for( i = 0; i < N; i++ )
    {
        int root = i;

        // find root
        while( nodes[root][PARENT] >= 0 )
            root = nodes[root][PARENT];

        for( j = 0; j < N; j++ )
        {
            if( i == j || !predicate(vec[i], vec[j]))
                continue;
            int root2 = j;

            while( nodes[root2][PARENT] >= 0 )
                root2 = nodes[root2][PARENT];

            if( root2 != root )
            {
                // unite both trees
                int rank = nodes[root][RANK], rank2 = nodes[root2][RANK];
                if( rank > rank2 )
                    nodes[root2][PARENT] = root;
                else
                {
                    nodes[root][PARENT] = root2;
                    nodes[root2][RANK] += rank == rank2;
                    root = root2;
                }
                CV_Assert( nodes[root][PARENT] < 0 );

                int k = j, parent;

                // compress the path from node2 to root
                while( (parent = nodes[k][PARENT]) >= 0 )
                {
                    nodes[k][PARENT] = root;
                    k = parent;
                }

                // compress the path from node to root
                k = i;
                while( (parent = nodes[k][PARENT]) >= 0 )
                {
                    nodes[k][PARENT] = root;
                    k = parent;
                }
            }
        }
    }

    // Final O(N) pass: enumerate classes
    labels.resize(N);
    int nclasses = 0;

    for( i = 0; i < N; i++ )
    {
        int root = i;
        while( nodes[root][PARENT] >= 0 )
            root = nodes[root][PARENT];
        // re-use the rank as the class label
        if( nodes[root][RANK] >= 0 )
            nodes[root][RANK] = ~nclasses++;
        labels[i] = ~nodes[root][RANK];
    }

    return nclasses;
}

} // cv

#endif