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42 
43 #ifndef __OPENCV_CUDAARITHM_HPP__
44 #define __OPENCV_CUDAARITHM_HPP__
45 
46 #ifndef __cplusplus
47 #  error cudaarithm.hpp header must be compiled as C++
48 #endif
49 
50 #include "opencv2/core/cuda.hpp"
51 
52 /**
53   @addtogroup cuda
54   @{
55     @defgroup cudaarithm Operations on Matrices
56     @{
57         @defgroup cudaarithm_core Core Operations on Matrices
58         @defgroup cudaarithm_elem Per-element Operations
59         @defgroup cudaarithm_reduce Matrix Reductions
60         @defgroup cudaarithm_arithm Arithm Operations on Matrices
61     @}
62   @}
63  */
64 
65 namespace cv { namespace cuda {
66 
67 //! @addtogroup cudaarithm
68 //! @{
69 
70 //! @addtogroup cudaarithm_elem
71 //! @{
72 
73 /** @brief Computes a matrix-matrix or matrix-scalar sum.
74 
75 @param src1 First source matrix or scalar.
76 @param src2 Second source matrix or scalar. Matrix should have the same size and type as src1 .
77 @param dst Destination matrix that has the same size and number of channels as the input array(s).
78 The depth is defined by dtype or src1 depth.
79 @param mask Optional operation mask, 8-bit single channel array, that specifies elements of the
80 destination array to be changed.
81 @param dtype Optional depth of the output array.
82 @param stream Stream for the asynchronous version.
83 
84 @sa add
85  */
86 CV_EXPORTS void add(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), int dtype = -1, Stream& stream = Stream::Null());
87 
88 /** @brief Computes a matrix-matrix or matrix-scalar difference.
89 
90 @param src1 First source matrix or scalar.
91 @param src2 Second source matrix or scalar. Matrix should have the same size and type as src1 .
92 @param dst Destination matrix that has the same size and number of channels as the input array(s).
93 The depth is defined by dtype or src1 depth.
94 @param mask Optional operation mask, 8-bit single channel array, that specifies elements of the
95 destination array to be changed.
96 @param dtype Optional depth of the output array.
97 @param stream Stream for the asynchronous version.
98 
99 @sa subtract
100  */
101 CV_EXPORTS void subtract(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), int dtype = -1, Stream& stream = Stream::Null());
102 
103 /** @brief Computes a matrix-matrix or matrix-scalar per-element product.
104 
105 @param src1 First source matrix or scalar.
106 @param src2 Second source matrix or scalar.
107 @param dst Destination matrix that has the same size and number of channels as the input array(s).
108 The depth is defined by dtype or src1 depth.
109 @param scale Optional scale factor.
110 @param dtype Optional depth of the output array.
111 @param stream Stream for the asynchronous version.
112 
113 @sa multiply
114  */
115 CV_EXPORTS void multiply(InputArray src1, InputArray src2, OutputArray dst, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
116 
117 /** @brief Computes a matrix-matrix or matrix-scalar division.
118 
119 @param src1 First source matrix or a scalar.
120 @param src2 Second source matrix or scalar.
121 @param dst Destination matrix that has the same size and number of channels as the input array(s).
122 The depth is defined by dtype or src1 depth.
123 @param scale Optional scale factor.
124 @param dtype Optional depth of the output array.
125 @param stream Stream for the asynchronous version.
126 
127 This function, in contrast to divide, uses a round-down rounding mode.
128 
129 @sa divide
130  */
131 CV_EXPORTS void divide(InputArray src1, InputArray src2, OutputArray dst, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
132 
133 /** @brief Computes per-element absolute difference of two matrices (or of a matrix and scalar).
134 
135 @param src1 First source matrix or scalar.
136 @param src2 Second source matrix or scalar.
137 @param dst Destination matrix that has the same size and type as the input array(s).
138 @param stream Stream for the asynchronous version.
139 
140 @sa absdiff
141  */
142 CV_EXPORTS void absdiff(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null());
143 
144 /** @brief Computes an absolute value of each matrix element.
145 
146 @param src Source matrix.
147 @param dst Destination matrix with the same size and type as src .
148 @param stream Stream for the asynchronous version.
149 
150 @sa abs
151  */
152 CV_EXPORTS void abs(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
153 
154 /** @brief Computes a square value of each matrix element.
155 
156 @param src Source matrix.
157 @param dst Destination matrix with the same size and type as src .
158 @param stream Stream for the asynchronous version.
159  */
160 CV_EXPORTS void sqr(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
161 
162 /** @brief Computes a square root of each matrix element.
163 
164 @param src Source matrix.
165 @param dst Destination matrix with the same size and type as src .
166 @param stream Stream for the asynchronous version.
167 
168 @sa sqrt
169  */
170 CV_EXPORTS void sqrt(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
171 
172 /** @brief Computes an exponent of each matrix element.
173 
174 @param src Source matrix.
175 @param dst Destination matrix with the same size and type as src .
176 @param stream Stream for the asynchronous version.
177 
178 @sa exp
179  */
180 CV_EXPORTS void exp(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
181 
182 /** @brief Computes a natural logarithm of absolute value of each matrix element.
183 
184 @param src Source matrix.
185 @param dst Destination matrix with the same size and type as src .
186 @param stream Stream for the asynchronous version.
187 
188 @sa log
189  */
190 CV_EXPORTS void log(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
191 
192 /** @brief Raises every matrix element to a power.
193 
194 @param src Source matrix.
195 @param power Exponent of power.
196 @param dst Destination matrix with the same size and type as src .
197 @param stream Stream for the asynchronous version.
198 
199 The function pow raises every element of the input matrix to power :
200 
201 \f[\texttt{dst} (I) =  \fork{\texttt{src}(I)^power}{if \texttt{power} is integer}{|\texttt{src}(I)|^power}{otherwise}\f]
202 
203 @sa pow
204  */
205 CV_EXPORTS void pow(InputArray src, double power, OutputArray dst, Stream& stream = Stream::Null());
206 
207 /** @brief Compares elements of two matrices (or of a matrix and scalar).
208 
209 @param src1 First source matrix or scalar.
210 @param src2 Second source matrix or scalar.
211 @param dst Destination matrix that has the same size and type as the input array(s).
212 @param cmpop Flag specifying the relation between the elements to be checked:
213 -   **CMP_EQ:** a(.) == b(.)
214 -   **CMP_GT:** a(.) \> b(.)
215 -   **CMP_GE:** a(.) \>= b(.)
216 -   **CMP_LT:** a(.) \< b(.)
217 -   **CMP_LE:** a(.) \<= b(.)
218 -   **CMP_NE:** a(.) != b(.)
219 @param stream Stream for the asynchronous version.
220 
221 @sa compare
222  */
223 CV_EXPORTS void compare(InputArray src1, InputArray src2, OutputArray dst, int cmpop, Stream& stream = Stream::Null());
224 
225 /** @brief Performs a per-element bitwise inversion.
226 
227 @param src Source matrix.
228 @param dst Destination matrix with the same size and type as src .
229 @param mask Optional operation mask. 8-bit single channel image.
230 @param stream Stream for the asynchronous version.
231  */
232 CV_EXPORTS void bitwise_not(InputArray src, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
233 
234 /** @brief Performs a per-element bitwise disjunction of two matrices (or of matrix and scalar).
235 
236 @param src1 First source matrix or scalar.
237 @param src2 Second source matrix or scalar.
238 @param dst Destination matrix that has the same size and type as the input array(s).
239 @param mask Optional operation mask. 8-bit single channel image.
240 @param stream Stream for the asynchronous version.
241  */
242 CV_EXPORTS void bitwise_or(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
243 
244 /** @brief Performs a per-element bitwise conjunction of two matrices (or of matrix and scalar).
245 
246 @param src1 First source matrix or scalar.
247 @param src2 Second source matrix or scalar.
248 @param dst Destination matrix that has the same size and type as the input array(s).
249 @param mask Optional operation mask. 8-bit single channel image.
250 @param stream Stream for the asynchronous version.
251  */
252 CV_EXPORTS void bitwise_and(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
253 
254 /** @brief Performs a per-element bitwise exclusive or operation of two matrices (or of matrix and scalar).
255 
256 @param src1 First source matrix or scalar.
257 @param src2 Second source matrix or scalar.
258 @param dst Destination matrix that has the same size and type as the input array(s).
259 @param mask Optional operation mask. 8-bit single channel image.
260 @param stream Stream for the asynchronous version.
261  */
262 CV_EXPORTS void bitwise_xor(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
263 
264 /** @brief Performs pixel by pixel right shift of an image by a constant value.
265 
266 @param src Source matrix. Supports 1, 3 and 4 channels images with integers elements.
267 @param val Constant values, one per channel.
268 @param dst Destination matrix with the same size and type as src .
269 @param stream Stream for the asynchronous version.
270  */
271 CV_EXPORTS void rshift(InputArray src, Scalar_<int> val, OutputArray dst, Stream& stream = Stream::Null());
272 
273 /** @brief Performs pixel by pixel right left of an image by a constant value.
274 
275 @param src Source matrix. Supports 1, 3 and 4 channels images with CV_8U , CV_16U or CV_32S
276 depth.
277 @param val Constant values, one per channel.
278 @param dst Destination matrix with the same size and type as src .
279 @param stream Stream for the asynchronous version.
280  */
281 CV_EXPORTS void lshift(InputArray src, Scalar_<int> val, OutputArray dst, Stream& stream = Stream::Null());
282 
283 /** @brief Computes the per-element minimum of two matrices (or a matrix and a scalar).
284 
285 @param src1 First source matrix or scalar.
286 @param src2 Second source matrix or scalar.
287 @param dst Destination matrix that has the same size and type as the input array(s).
288 @param stream Stream for the asynchronous version.
289 
290 @sa min
291  */
292 CV_EXPORTS void min(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null());
293 
294 /** @brief Computes the per-element maximum of two matrices (or a matrix and a scalar).
295 
296 @param src1 First source matrix or scalar.
297 @param src2 Second source matrix or scalar.
298 @param dst Destination matrix that has the same size and type as the input array(s).
299 @param stream Stream for the asynchronous version.
300 
301 @sa max
302  */
303 CV_EXPORTS void max(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null());
304 
305 /** @brief Computes the weighted sum of two arrays.
306 
307 @param src1 First source array.
308 @param alpha Weight for the first array elements.
309 @param src2 Second source array of the same size and channel number as src1 .
310 @param beta Weight for the second array elements.
311 @param dst Destination array that has the same size and number of channels as the input arrays.
312 @param gamma Scalar added to each sum.
313 @param dtype Optional depth of the destination array. When both input arrays have the same depth,
314 dtype can be set to -1, which will be equivalent to src1.depth().
315 @param stream Stream for the asynchronous version.
316 
317 The function addWeighted calculates the weighted sum of two arrays as follows:
318 
319 \f[\texttt{dst} (I)= \texttt{saturate} ( \texttt{src1} (I)* \texttt{alpha} +  \texttt{src2} (I)* \texttt{beta} +  \texttt{gamma} )\f]
320 
321 where I is a multi-dimensional index of array elements. In case of multi-channel arrays, each
322 channel is processed independently.
323 
324 @sa addWeighted
325  */
326 CV_EXPORTS void addWeighted(InputArray src1, double alpha, InputArray src2, double beta, double gamma, OutputArray dst,
327                             int dtype = -1, Stream& stream = Stream::Null());
328 
329 //! adds scaled array to another one (dst = alpha*src1 + src2)
scaleAdd(InputArray src1,double alpha,InputArray src2,OutputArray dst,Stream & stream=Stream::Null ())330 static inline void scaleAdd(InputArray src1, double alpha, InputArray src2, OutputArray dst, Stream& stream = Stream::Null())
331 {
332     addWeighted(src1, alpha, src2, 1.0, 0.0, dst, -1, stream);
333 }
334 
335 /** @brief Applies a fixed-level threshold to each array element.
336 
337 @param src Source array (single-channel).
338 @param dst Destination array with the same size and type as src .
339 @param thresh Threshold value.
340 @param maxval Maximum value to use with THRESH_BINARY and THRESH_BINARY_INV threshold types.
341 @param type Threshold type. For details, see threshold . The THRESH_OTSU and THRESH_TRIANGLE
342 threshold types are not supported.
343 @param stream Stream for the asynchronous version.
344 
345 @sa threshold
346  */
347 CV_EXPORTS double threshold(InputArray src, OutputArray dst, double thresh, double maxval, int type, Stream& stream = Stream::Null());
348 
349 /** @brief Computes magnitudes of complex matrix elements.
350 
351 @param xy Source complex matrix in the interleaved format ( CV_32FC2 ).
352 @param magnitude Destination matrix of float magnitudes ( CV_32FC1 ).
353 @param stream Stream for the asynchronous version.
354 
355 @sa magnitude
356  */
357 CV_EXPORTS void magnitude(InputArray xy, OutputArray magnitude, Stream& stream = Stream::Null());
358 
359 /** @brief Computes squared magnitudes of complex matrix elements.
360 
361 @param xy Source complex matrix in the interleaved format ( CV_32FC2 ).
362 @param magnitude Destination matrix of float magnitude squares ( CV_32FC1 ).
363 @param stream Stream for the asynchronous version.
364  */
365 CV_EXPORTS void magnitudeSqr(InputArray xy, OutputArray magnitude, Stream& stream = Stream::Null());
366 
367 /** @overload
368  computes magnitude of each (x(i), y(i)) vector
369  supports only floating-point source
370 @param x Source matrix containing real components ( CV_32FC1 ).
371 @param y Source matrix containing imaginary components ( CV_32FC1 ).
372 @param magnitude Destination matrix of float magnitudes ( CV_32FC1 ).
373 @param stream Stream for the asynchronous version.
374  */
375 CV_EXPORTS void magnitude(InputArray x, InputArray y, OutputArray magnitude, Stream& stream = Stream::Null());
376 
377 /** @overload
378  computes squared magnitude of each (x(i), y(i)) vector
379  supports only floating-point source
380 @param x Source matrix containing real components ( CV_32FC1 ).
381 @param y Source matrix containing imaginary components ( CV_32FC1 ).
382 @param magnitude Destination matrix of float magnitude squares ( CV_32FC1 ).
383 @param stream Stream for the asynchronous version.
384 */
385 CV_EXPORTS void magnitudeSqr(InputArray x, InputArray y, OutputArray magnitude, Stream& stream = Stream::Null());
386 
387 /** @brief Computes polar angles of complex matrix elements.
388 
389 @param x Source matrix containing real components ( CV_32FC1 ).
390 @param y Source matrix containing imaginary components ( CV_32FC1 ).
391 @param angle Destination matrix of angles ( CV_32FC1 ).
392 @param angleInDegrees Flag for angles that must be evaluated in degrees.
393 @param stream Stream for the asynchronous version.
394 
395 @sa phase
396  */
397 CV_EXPORTS void phase(InputArray x, InputArray y, OutputArray angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
398 
399 /** @brief Converts Cartesian coordinates into polar.
400 
401 @param x Source matrix containing real components ( CV_32FC1 ).
402 @param y Source matrix containing imaginary components ( CV_32FC1 ).
403 @param magnitude Destination matrix of float magnitudes ( CV_32FC1 ).
404 @param angle Destination matrix of angles ( CV_32FC1 ).
405 @param angleInDegrees Flag for angles that must be evaluated in degrees.
406 @param stream Stream for the asynchronous version.
407 
408 @sa cartToPolar
409  */
410 CV_EXPORTS void cartToPolar(InputArray x, InputArray y, OutputArray magnitude, OutputArray angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
411 
412 /** @brief Converts polar coordinates into Cartesian.
413 
414 @param magnitude Source matrix containing magnitudes ( CV_32FC1 ).
415 @param angle Source matrix containing angles ( CV_32FC1 ).
416 @param x Destination matrix of real components ( CV_32FC1 ).
417 @param y Destination matrix of imaginary components ( CV_32FC1 ).
418 @param angleInDegrees Flag that indicates angles in degrees.
419 @param stream Stream for the asynchronous version.
420  */
421 CV_EXPORTS void polarToCart(InputArray magnitude, InputArray angle, OutputArray x, OutputArray y, bool angleInDegrees = false, Stream& stream = Stream::Null());
422 
423 //! @} cudaarithm_elem
424 
425 //! @addtogroup cudaarithm_core
426 //! @{
427 
428 /** @brief Makes a multi-channel matrix out of several single-channel matrices.
429 
430 @param src Array/vector of source matrices.
431 @param n Number of source matrices.
432 @param dst Destination matrix.
433 @param stream Stream for the asynchronous version.
434 
435 @sa merge
436  */
437 CV_EXPORTS void merge(const GpuMat* src, size_t n, OutputArray dst, Stream& stream = Stream::Null());
438 /** @overload */
439 CV_EXPORTS void merge(const std::vector<GpuMat>& src, OutputArray dst, Stream& stream = Stream::Null());
440 
441 /** @brief Copies each plane of a multi-channel matrix into an array.
442 
443 @param src Source matrix.
444 @param dst Destination array/vector of single-channel matrices.
445 @param stream Stream for the asynchronous version.
446 
447 @sa split
448  */
449 CV_EXPORTS void split(InputArray src, GpuMat* dst, Stream& stream = Stream::Null());
450 /** @overload */
451 CV_EXPORTS void split(InputArray src, std::vector<GpuMat>& dst, Stream& stream = Stream::Null());
452 
453 /** @brief Transposes a matrix.
454 
455 @param src1 Source matrix. 1-, 4-, 8-byte element sizes are supported for now.
456 @param dst Destination matrix.
457 @param stream Stream for the asynchronous version.
458 
459 @sa transpose
460  */
461 CV_EXPORTS void transpose(InputArray src1, OutputArray dst, Stream& stream = Stream::Null());
462 
463 /** @brief Flips a 2D matrix around vertical, horizontal, or both axes.
464 
465 @param src Source matrix. Supports 1, 3 and 4 channels images with CV_8U, CV_16U, CV_32S or
466 CV_32F depth.
467 @param dst Destination matrix.
468 @param flipCode Flip mode for the source:
469 -   0 Flips around x-axis.
470 -   \> 0 Flips around y-axis.
471 -   \< 0 Flips around both axes.
472 @param stream Stream for the asynchronous version.
473 
474 @sa flip
475  */
476 CV_EXPORTS void flip(InputArray src, OutputArray dst, int flipCode, Stream& stream = Stream::Null());
477 
478 /** @brief Base class for transform using lookup table.
479  */
480 class CV_EXPORTS LookUpTable : public Algorithm
481 {
482 public:
483     /** @brief Transforms the source matrix into the destination matrix using the given look-up table:
484     dst(I) = lut(src(I)) .
485 
486     @param src Source matrix. CV_8UC1 and CV_8UC3 matrices are supported for now.
487     @param dst Destination matrix.
488     @param stream Stream for the asynchronous version.
489      */
490     virtual void transform(InputArray src, OutputArray dst, Stream& stream = Stream::Null()) = 0;
491 };
492 
493 /** @brief Creates implementation for cuda::LookUpTable .
494 
495 @param lut Look-up table of 256 elements. It is a continuous CV_8U matrix.
496  */
497 CV_EXPORTS Ptr<LookUpTable> createLookUpTable(InputArray lut);
498 
499 /** @brief Forms a border around an image.
500 
501 @param src Source image. CV_8UC1 , CV_8UC4 , CV_32SC1 , and CV_32FC1 types are supported.
502 @param dst Destination image with the same type as src. The size is
503 Size(src.cols+left+right, src.rows+top+bottom) .
504 @param top
505 @param bottom
506 @param left
507 @param right Number of pixels in each direction from the source image rectangle to extrapolate.
508 For example: top=1, bottom=1, left=1, right=1 mean that 1 pixel-wide border needs to be built.
509 @param borderType Border type. See borderInterpolate for details. BORDER_REFLECT101 ,
510 BORDER_REPLICATE , BORDER_CONSTANT , BORDER_REFLECT and BORDER_WRAP are supported for now.
511 @param value Border value.
512 @param stream Stream for the asynchronous version.
513  */
514 CV_EXPORTS void copyMakeBorder(InputArray src, OutputArray dst, int top, int bottom, int left, int right, int borderType,
515                                Scalar value = Scalar(), Stream& stream = Stream::Null());
516 
517 //! @} cudaarithm_core
518 
519 //! @addtogroup cudaarithm_reduce
520 //! @{
521 
522 /** @brief Returns the norm of a matrix (or difference of two matrices).
523 
524 @param src1 Source matrix. Any matrices except 64F are supported.
525 @param normType Norm type. NORM_L1 , NORM_L2 , and NORM_INF are supported for now.
526 @param mask optional operation mask; it must have the same size as src1 and CV_8UC1 type.
527 
528 @sa norm
529  */
530 CV_EXPORTS double norm(InputArray src1, int normType, InputArray mask = noArray());
531 /** @overload */
532 CV_EXPORTS void calcNorm(InputArray src, OutputArray dst, int normType, InputArray mask = noArray(), Stream& stream = Stream::Null());
533 
534 /** @brief Returns the difference of two matrices.
535 
536 @param src1 Source matrix. Any matrices except 64F are supported.
537 @param src2 Second source matrix (if any) with the same size and type as src1.
538 @param normType Norm type. NORM_L1 , NORM_L2 , and NORM_INF are supported for now.
539 
540 @sa norm
541  */
542 CV_EXPORTS double norm(InputArray src1, InputArray src2, int normType=NORM_L2);
543 /** @overload */
544 CV_EXPORTS void calcNormDiff(InputArray src1, InputArray src2, OutputArray dst, int normType=NORM_L2, Stream& stream = Stream::Null());
545 
546 /** @brief Returns the sum of matrix elements.
547 
548 @param src Source image of any depth except for CV_64F .
549 @param mask optional operation mask; it must have the same size as src1 and CV_8UC1 type.
550 
551 @sa sum
552  */
553 CV_EXPORTS Scalar sum(InputArray src, InputArray mask = noArray());
554 /** @overload */
555 CV_EXPORTS void calcSum(InputArray src, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
556 
557 /** @brief Returns the sum of absolute values for matrix elements.
558 
559 @param src Source image of any depth except for CV_64F .
560 @param mask optional operation mask; it must have the same size as src1 and CV_8UC1 type.
561  */
562 CV_EXPORTS Scalar absSum(InputArray src, InputArray mask = noArray());
563 /** @overload */
564 CV_EXPORTS void calcAbsSum(InputArray src, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
565 
566 /** @brief Returns the squared sum of matrix elements.
567 
568 @param src Source image of any depth except for CV_64F .
569 @param mask optional operation mask; it must have the same size as src1 and CV_8UC1 type.
570  */
571 CV_EXPORTS Scalar sqrSum(InputArray src, InputArray mask = noArray());
572 /** @overload */
573 CV_EXPORTS void calcSqrSum(InputArray src, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
574 
575 /** @brief Finds global minimum and maximum matrix elements and returns their values.
576 
577 @param src Single-channel source image.
578 @param minVal Pointer to the returned minimum value. Use NULL if not required.
579 @param maxVal Pointer to the returned maximum value. Use NULL if not required.
580 @param mask Optional mask to select a sub-matrix.
581 
582 The function does not work with CV_64F images on GPUs with the compute capability \< 1.3.
583 
584 @sa minMaxLoc
585  */
586 CV_EXPORTS void minMax(InputArray src, double* minVal, double* maxVal, InputArray mask = noArray());
587 /** @overload */
588 CV_EXPORTS void findMinMax(InputArray src, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
589 
590 /** @brief Finds global minimum and maximum matrix elements and returns their values with locations.
591 
592 @param src Single-channel source image.
593 @param minVal Pointer to the returned minimum value. Use NULL if not required.
594 @param maxVal Pointer to the returned maximum value. Use NULL if not required.
595 @param minLoc Pointer to the returned minimum location. Use NULL if not required.
596 @param maxLoc Pointer to the returned maximum location. Use NULL if not required.
597 @param mask Optional mask to select a sub-matrix.
598 
599 The function does not work with CV_64F images on GPU with the compute capability \< 1.3.
600 
601 @sa minMaxLoc
602  */
603 CV_EXPORTS void minMaxLoc(InputArray src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
604                           InputArray mask = noArray());
605 /** @overload */
606 CV_EXPORTS void findMinMaxLoc(InputArray src, OutputArray minMaxVals, OutputArray loc,
607                               InputArray mask = noArray(), Stream& stream = Stream::Null());
608 
609 /** @brief Counts non-zero matrix elements.
610 
611 @param src Single-channel source image.
612 
613 The function does not work with CV_64F images on GPUs with the compute capability \< 1.3.
614 
615 @sa countNonZero
616  */
617 CV_EXPORTS int countNonZero(InputArray src);
618 /** @overload */
619 CV_EXPORTS void countNonZero(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
620 
621 /** @brief Reduces a matrix to a vector.
622 
623 @param mtx Source 2D matrix.
624 @param vec Destination vector. Its size and type is defined by dim and dtype parameters.
625 @param dim Dimension index along which the matrix is reduced. 0 means that the matrix is reduced
626 to a single row. 1 means that the matrix is reduced to a single column.
627 @param reduceOp Reduction operation that could be one of the following:
628 -   **CV_REDUCE_SUM** The output is the sum of all rows/columns of the matrix.
629 -   **CV_REDUCE_AVG** The output is the mean vector of all rows/columns of the matrix.
630 -   **CV_REDUCE_MAX** The output is the maximum (column/row-wise) of all rows/columns of the
631 matrix.
632 -   **CV_REDUCE_MIN** The output is the minimum (column/row-wise) of all rows/columns of the
633 matrix.
634 @param dtype When it is negative, the destination vector will have the same type as the source
635 matrix. Otherwise, its type will be CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), mtx.channels()) .
636 @param stream Stream for the asynchronous version.
637 
638 The function reduce reduces the matrix to a vector by treating the matrix rows/columns as a set of
639 1D vectors and performing the specified operation on the vectors until a single row/column is
640 obtained. For example, the function can be used to compute horizontal and vertical projections of a
641 raster image. In case of CV_REDUCE_SUM and CV_REDUCE_AVG , the output may have a larger element
642 bit-depth to preserve accuracy. And multi-channel arrays are also supported in these two reduction
643 modes.
644 
645 @sa reduce
646  */
647 CV_EXPORTS void reduce(InputArray mtx, OutputArray vec, int dim, int reduceOp, int dtype = -1, Stream& stream = Stream::Null());
648 
649 /** @brief Computes a mean value and a standard deviation of matrix elements.
650 
651 @param mtx Source matrix. CV_8UC1 matrices are supported for now.
652 @param mean Mean value.
653 @param stddev Standard deviation value.
654 
655 @sa meanStdDev
656  */
657 CV_EXPORTS void meanStdDev(InputArray mtx, Scalar& mean, Scalar& stddev);
658 /** @overload */
659 CV_EXPORTS void meanStdDev(InputArray mtx, OutputArray dst, Stream& stream = Stream::Null());
660 
661 /** @brief Computes a standard deviation of integral images.
662 
663 @param src Source image. Only the CV_32SC1 type is supported.
664 @param sqr Squared source image. Only the CV_32FC1 type is supported.
665 @param dst Destination image with the same type and size as src .
666 @param rect Rectangular window.
667 @param stream Stream for the asynchronous version.
668  */
669 CV_EXPORTS void rectStdDev(InputArray src, InputArray sqr, OutputArray dst, Rect rect, Stream& stream = Stream::Null());
670 
671 /** @brief Normalizes the norm or value range of an array.
672 
673 @param src Input array.
674 @param dst Output array of the same size as src .
675 @param alpha Norm value to normalize to or the lower range boundary in case of the range
676 normalization.
677 @param beta Upper range boundary in case of the range normalization; it is not used for the norm
678 normalization.
679 @param norm_type Normalization type ( NORM_MINMAX , NORM_L2 , NORM_L1 or NORM_INF ).
680 @param dtype When negative, the output array has the same type as src; otherwise, it has the same
681 number of channels as src and the depth =CV_MAT_DEPTH(dtype).
682 @param mask Optional operation mask.
683 @param stream Stream for the asynchronous version.
684 
685 @sa normalize
686  */
687 CV_EXPORTS void normalize(InputArray src, OutputArray dst, double alpha, double beta,
688                           int norm_type, int dtype, InputArray mask = noArray(),
689                           Stream& stream = Stream::Null());
690 
691 /** @brief Computes an integral image.
692 
693 @param src Source image. Only CV_8UC1 images are supported for now.
694 @param sum Integral image containing 32-bit unsigned integer values packed into CV_32SC1 .
695 @param stream Stream for the asynchronous version.
696 
697 @sa integral
698  */
699 CV_EXPORTS void integral(InputArray src, OutputArray sum, Stream& stream = Stream::Null());
700 
701 /** @brief Computes a squared integral image.
702 
703 @param src Source image. Only CV_8UC1 images are supported for now.
704 @param sqsum Squared integral image containing 64-bit unsigned integer values packed into
705 CV_64FC1 .
706 @param stream Stream for the asynchronous version.
707  */
708 CV_EXPORTS void sqrIntegral(InputArray src, OutputArray sqsum, Stream& stream = Stream::Null());
709 
710 //! @} cudaarithm_reduce
711 
712 //! @addtogroup cudaarithm_arithm
713 //! @{
714 
715 /** @brief Performs generalized matrix multiplication.
716 
717 @param src1 First multiplied input matrix that should have CV_32FC1 , CV_64FC1 , CV_32FC2 , or
718 CV_64FC2 type.
719 @param src2 Second multiplied input matrix of the same type as src1 .
720 @param alpha Weight of the matrix product.
721 @param src3 Third optional delta matrix added to the matrix product. It should have the same type
722 as src1 and src2 .
723 @param beta Weight of src3 .
724 @param dst Destination matrix. It has the proper size and the same type as input matrices.
725 @param flags Operation flags:
726 -   **GEMM_1_T** transpose src1
727 -   **GEMM_2_T** transpose src2
728 -   **GEMM_3_T** transpose src3
729 @param stream Stream for the asynchronous version.
730 
731 The function performs generalized matrix multiplication similar to the gemm functions in BLAS level
732 3. For example, gemm(src1, src2, alpha, src3, beta, dst, GEMM_1_T + GEMM_3_T) corresponds to
733 
734 \f[\texttt{dst} =  \texttt{alpha} \cdot \texttt{src1} ^T  \cdot \texttt{src2} +  \texttt{beta} \cdot \texttt{src3} ^T\f]
735 
736 @note Transposition operation doesn't support CV_64FC2 input type.
737 
738 @sa gemm
739  */
740 CV_EXPORTS void gemm(InputArray src1, InputArray src2, double alpha,
741                      InputArray src3, double beta, OutputArray dst, int flags = 0, Stream& stream = Stream::Null());
742 
743 /** @brief Performs a per-element multiplication of two Fourier spectrums.
744 
745 @param src1 First spectrum.
746 @param src2 Second spectrum with the same size and type as a .
747 @param dst Destination spectrum.
748 @param flags Mock parameter used for CPU/CUDA interfaces similarity.
749 @param conjB Optional flag to specify if the second spectrum needs to be conjugated before the
750 multiplication.
751 @param stream Stream for the asynchronous version.
752 
753 Only full (not packed) CV_32FC2 complex spectrums in the interleaved format are supported for now.
754 
755 @sa mulSpectrums
756  */
757 CV_EXPORTS void mulSpectrums(InputArray src1, InputArray src2, OutputArray dst, int flags, bool conjB=false, Stream& stream = Stream::Null());
758 
759 /** @brief Performs a per-element multiplication of two Fourier spectrums and scales the result.
760 
761 @param src1 First spectrum.
762 @param src2 Second spectrum with the same size and type as a .
763 @param dst Destination spectrum.
764 @param flags Mock parameter used for CPU/CUDA interfaces similarity, simply add a `0` value.
765 @param scale Scale constant.
766 @param conjB Optional flag to specify if the second spectrum needs to be conjugated before the
767 multiplication.
768 @param stream Stream for the asynchronous version.
769 
770 Only full (not packed) CV_32FC2 complex spectrums in the interleaved format are supported for now.
771 
772 @sa mulSpectrums
773  */
774 CV_EXPORTS void mulAndScaleSpectrums(InputArray src1, InputArray src2, OutputArray dst, int flags, float scale, bool conjB=false, Stream& stream = Stream::Null());
775 
776 /** @brief Performs a forward or inverse discrete Fourier transform (1D or 2D) of the floating point matrix.
777 
778 @param src Source matrix (real or complex).
779 @param dst Destination matrix (real or complex).
780 @param dft_size Size of a discrete Fourier transform.
781 @param flags Optional flags:
782 -   **DFT_ROWS** transforms each individual row of the source matrix.
783 -   **DFT_SCALE** scales the result: divide it by the number of elements in the transform
784 (obtained from dft_size ).
785 -   **DFT_INVERSE** inverts DFT. Use for complex-complex cases (real-complex and complex-real
786 cases are always forward and inverse, respectively).
787 -   **DFT_REAL_OUTPUT** specifies the output as real. The source matrix is the result of
788 real-complex transform, so the destination matrix must be real.
789 @param stream Stream for the asynchronous version.
790 
791 Use to handle real matrices ( CV32FC1 ) and complex matrices in the interleaved format ( CV32FC2 ).
792 
793 The source matrix should be continuous, otherwise reallocation and data copying is performed. The
794 function chooses an operation mode depending on the flags, size, and channel count of the source
795 matrix:
796 
797 -   If the source matrix is complex and the output is not specified as real, the destination
798 matrix is complex and has the dft_size size and CV_32FC2 type. The destination matrix
799 contains a full result of the DFT (forward or inverse).
800 -   If the source matrix is complex and the output is specified as real, the function assumes that
801 its input is the result of the forward transform (see the next item). The destination matrix
802 has the dft_size size and CV_32FC1 type. It contains the result of the inverse DFT.
803 -   If the source matrix is real (its type is CV_32FC1 ), forward DFT is performed. The result of
804 the DFT is packed into complex ( CV_32FC2 ) matrix. So, the width of the destination matrix
805 is dft_size.width / 2 + 1 . But if the source is a single column, the height is reduced
806 instead of the width.
807 
808 @sa dft
809  */
810 CV_EXPORTS void dft(InputArray src, OutputArray dst, Size dft_size, int flags=0, Stream& stream = Stream::Null());
811 
812 /** @brief Base class for convolution (or cross-correlation) operator. :
813  */
814 class CV_EXPORTS Convolution : public Algorithm
815 {
816 public:
817     /** @brief Computes a convolution (or cross-correlation) of two images.
818 
819     @param image Source image. Only CV_32FC1 images are supported for now.
820     @param templ Template image. The size is not greater than the image size. The type is the same as
821     image .
822     @param result Result image. If image is *W x H* and templ is *w x h*, then result must be *W-w+1 x
823     H-h+1*.
824     @param ccorr Flags to evaluate cross-correlation instead of convolution.
825     @param stream Stream for the asynchronous version.
826      */
827     virtual void convolve(InputArray image, InputArray templ, OutputArray result, bool ccorr = false, Stream& stream = Stream::Null()) = 0;
828 };
829 
830 /** @brief Creates implementation for cuda::Convolution .
831 
832 @param user_block_size Block size. If you leave default value Size(0,0) then automatic
833 estimation of block size will be used (which is optimized for speed). By varying user_block_size
834 you can reduce memory requirements at the cost of speed.
835  */
836 CV_EXPORTS Ptr<Convolution> createConvolution(Size user_block_size = Size());
837 
838 //! @} cudaarithm_arithm
839 
840 //! @} cudaarithm
841 
842 }} // namespace cv { namespace cuda {
843 
844 #endif /* __OPENCV_CUDAARITHM_HPP__ */
845