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8461cb3f4b
* converted it to Algorithm * old API still can be used for source compatibility (marked as deprecated)
420 lines
19 KiB
C++
420 lines
19 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_GPUARITHM_HPP__
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#define __OPENCV_GPUARITHM_HPP__
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#ifndef __cplusplus
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# error gpuarithm.hpp header must be compiled as C++
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#endif
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#include "opencv2/core/gpu.hpp"
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#if defined __GNUC__
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#define __OPENCV_GPUARITHM_DEPR_BEFORE__
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#define __OPENCV_GPUARITHM_DEPR_AFTER__ __attribute__ ((deprecated))
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#elif (defined WIN32 || defined _WIN32)
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#define __OPENCV_GPUARITHM_DEPR_BEFORE__ __declspec(deprecated)
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#define __OPENCV_GPUARITHM_DEPR_AFTER__
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#else
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#define __OPENCV_GPUARITHM_DEPR_BEFORE__
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#define __OPENCV_GPUARITHM_DEPR_AFTER__
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#endif
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namespace cv { namespace gpu {
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//! adds one matrix to another (dst = src1 + src2)
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CV_EXPORTS void add(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), int dtype = -1, Stream& stream = Stream::Null());
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//! subtracts one matrix from another (dst = src1 - src2)
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CV_EXPORTS void subtract(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), int dtype = -1, Stream& stream = Stream::Null());
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//! computes element-wise weighted product of the two arrays (dst = scale * src1 * src2)
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CV_EXPORTS void multiply(InputArray src1, InputArray src2, OutputArray dst, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
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//! computes element-wise weighted quotient of the two arrays (dst = scale * (src1 / src2))
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CV_EXPORTS void divide(InputArray src1, InputArray src2, OutputArray dst, double scale = 1, int dtype = -1, Stream& stream = Stream::Null());
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//! computes element-wise weighted reciprocal of an array (dst = scale/src2)
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static inline void divide(double src1, InputArray src2, OutputArray dst, int dtype = -1, Stream& stream = Stream::Null())
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{
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divide(src1, src2, dst, 1.0, dtype, stream);
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}
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//! computes element-wise absolute difference of two arrays (dst = abs(src1 - src2))
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CV_EXPORTS void absdiff(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null());
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//! computes absolute value of each matrix element
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CV_EXPORTS void abs(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
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//! computes square of each pixel in an image
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CV_EXPORTS void sqr(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
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//! computes square root of each pixel in an image
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CV_EXPORTS void sqrt(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
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//! computes exponent of each matrix element
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CV_EXPORTS void exp(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
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//! computes natural logarithm of absolute value of each matrix element
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CV_EXPORTS void log(InputArray src, OutputArray dst, Stream& stream = Stream::Null());
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//! computes power of each matrix element:
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//! (dst(i,j) = pow( src(i,j) , power), if src.type() is integer
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//! (dst(i,j) = pow(fabs(src(i,j)), power), otherwise
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CV_EXPORTS void pow(InputArray src, double power, OutputArray dst, Stream& stream = Stream::Null());
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//! compares elements of two arrays (dst = src1 <cmpop> src2)
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CV_EXPORTS void compare(InputArray src1, InputArray src2, OutputArray dst, int cmpop, Stream& stream = Stream::Null());
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//! performs per-elements bit-wise inversion
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CV_EXPORTS void bitwise_not(InputArray src, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
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//! calculates per-element bit-wise disjunction of two arrays
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CV_EXPORTS void bitwise_or(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
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//! calculates per-element bit-wise conjunction of two arrays
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CV_EXPORTS void bitwise_and(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
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//! calculates per-element bit-wise "exclusive or" operation
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CV_EXPORTS void bitwise_xor(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null());
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//! pixel by pixel right shift of an image by a constant value
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//! supports 1, 3 and 4 channels images with integers elements
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CV_EXPORTS void rshift(InputArray src, Scalar_<int> val, OutputArray dst, Stream& stream = Stream::Null());
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//! pixel by pixel left shift of an image by a constant value
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//! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth
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CV_EXPORTS void lshift(InputArray src, Scalar_<int> val, OutputArray dst, Stream& stream = Stream::Null());
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//! computes per-element minimum of two arrays (dst = min(src1, src2))
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CV_EXPORTS void min(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null());
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//! computes per-element maximum of two arrays (dst = max(src1, src2))
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CV_EXPORTS void max(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null());
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//! computes the weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma)
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CV_EXPORTS void addWeighted(InputArray src1, double alpha, InputArray src2, double beta, double gamma, OutputArray dst,
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int dtype = -1, Stream& stream = Stream::Null());
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//! adds scaled array to another one (dst = alpha*src1 + src2)
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static inline void scaleAdd(InputArray src1, double alpha, InputArray src2, OutputArray dst, Stream& stream = Stream::Null())
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{
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addWeighted(src1, alpha, src2, 1.0, 0.0, dst, -1, stream);
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}
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//! applies fixed threshold to the image
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CV_EXPORTS double threshold(InputArray src, OutputArray dst, double thresh, double maxval, int type, Stream& stream = Stream::Null());
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//! computes magnitude of complex (x(i).re, x(i).im) vector
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//! supports only CV_32FC2 type
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CV_EXPORTS void magnitude(InputArray xy, OutputArray magnitude, Stream& stream = Stream::Null());
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//! computes squared magnitude of complex (x(i).re, x(i).im) vector
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//! supports only CV_32FC2 type
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CV_EXPORTS void magnitudeSqr(InputArray xy, OutputArray magnitude, Stream& stream = Stream::Null());
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//! computes magnitude of each (x(i), y(i)) vector
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//! supports only floating-point source
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CV_EXPORTS void magnitude(InputArray x, InputArray y, OutputArray magnitude, Stream& stream = Stream::Null());
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//! computes squared magnitude of each (x(i), y(i)) vector
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//! supports only floating-point source
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CV_EXPORTS void magnitudeSqr(InputArray x, InputArray y, OutputArray magnitude, Stream& stream = Stream::Null());
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//! computes angle of each (x(i), y(i)) vector
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//! supports only floating-point source
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CV_EXPORTS void phase(InputArray x, InputArray y, OutputArray angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
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//! converts Cartesian coordinates to polar
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//! supports only floating-point source
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CV_EXPORTS void cartToPolar(InputArray x, InputArray y, OutputArray magnitude, OutputArray angle, bool angleInDegrees = false, Stream& stream = Stream::Null());
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//! converts polar coordinates to Cartesian
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//! supports only floating-point source
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CV_EXPORTS void polarToCart(InputArray magnitude, InputArray angle, OutputArray x, OutputArray y, bool angleInDegrees = false, Stream& stream = Stream::Null());
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//! makes multi-channel array out of several single-channel arrays
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CV_EXPORTS void merge(const GpuMat* src, size_t n, OutputArray dst, Stream& stream = Stream::Null());
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CV_EXPORTS void merge(const std::vector<GpuMat>& src, OutputArray dst, Stream& stream = Stream::Null());
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//! copies each plane of a multi-channel array to a dedicated array
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CV_EXPORTS void split(InputArray src, GpuMat* dst, Stream& stream = Stream::Null());
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CV_EXPORTS void split(InputArray src, std::vector<GpuMat>& dst, Stream& stream = Stream::Null());
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//! transposes the matrix
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//! supports matrix with element size = 1, 4 and 8 bytes (CV_8UC1, CV_8UC4, CV_16UC2, CV_32FC1, etc)
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CV_EXPORTS void transpose(InputArray src1, OutputArray dst, Stream& stream = Stream::Null());
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//! reverses the order of the rows, columns or both in a matrix
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//! supports 1, 3 and 4 channels images with CV_8U, CV_16U, CV_32S or CV_32F depth
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CV_EXPORTS void flip(InputArray src, OutputArray dst, int flipCode, Stream& stream = Stream::Null());
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//! transforms 8-bit unsigned integers using lookup table: dst(i)=lut(src(i))
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//! destination array will have the depth type as lut and the same channels number as source
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//! supports CV_8UC1, CV_8UC3 types
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class CV_EXPORTS LookUpTable : public Algorithm
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{
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public:
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virtual void transform(InputArray src, OutputArray dst, Stream& stream = Stream::Null()) = 0;
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};
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CV_EXPORTS Ptr<LookUpTable> createLookUpTable(InputArray lut);
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__OPENCV_GPUARITHM_DEPR_BEFORE__ void LUT(InputArray src, InputArray lut, OutputArray dst, Stream& stream = Stream::Null()) __OPENCV_GPUARITHM_DEPR_AFTER__;
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inline void LUT(InputArray src, InputArray lut, OutputArray dst, Stream& stream)
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{
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createLookUpTable(lut)->transform(src, dst, stream);
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}
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//! copies 2D array to a larger destination array and pads borders with user-specifiable constant
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CV_EXPORTS void copyMakeBorder(InputArray src, OutputArray dst, int top, int bottom, int left, int right, int borderType,
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Scalar value = Scalar(), Stream& stream = Stream::Null());
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//! computes norm of array
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//! supports NORM_INF, NORM_L1, NORM_L2
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//! supports all matrices except 64F
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CV_EXPORTS double norm(InputArray src1, int normType, InputArray mask, GpuMat& buf);
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static inline double norm(InputArray src, int normType)
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{
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GpuMat buf;
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return norm(src, normType, GpuMat(), buf);
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}
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static inline double norm(InputArray src, int normType, GpuMat& buf)
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{
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return norm(src, normType, GpuMat(), buf);
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}
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//! computes norm of the difference between two arrays
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//! supports NORM_INF, NORM_L1, NORM_L2
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//! supports only CV_8UC1 type
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CV_EXPORTS double norm(InputArray src1, InputArray src2, GpuMat& buf, int normType=NORM_L2);
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static inline double norm(InputArray src1, InputArray src2, int normType=NORM_L2)
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{
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GpuMat buf;
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return norm(src1, src2, buf, normType);
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}
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//! computes sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sum(InputArray src, InputArray mask, GpuMat& buf);
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static inline Scalar sum(InputArray src)
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{
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GpuMat buf;
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return sum(src, GpuMat(), buf);
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}
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static inline Scalar sum(InputArray src, GpuMat& buf)
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{
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return sum(src, GpuMat(), buf);
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}
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//! computes sum of array elements absolute values
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//! supports only single channel images
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CV_EXPORTS Scalar absSum(InputArray src, InputArray mask, GpuMat& buf);
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static inline Scalar absSum(InputArray src)
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{
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GpuMat buf;
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return absSum(src, GpuMat(), buf);
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}
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static inline Scalar absSum(InputArray src, GpuMat& buf)
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{
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return absSum(src, GpuMat(), buf);
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}
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//! computes squared sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sqrSum(InputArray src, InputArray mask, GpuMat& buf);
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static inline Scalar sqrSum(InputArray src)
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{
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GpuMat buf;
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return sqrSum(src, GpuMat(), buf);
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}
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static inline Scalar sqrSum(InputArray src, GpuMat& buf)
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{
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return sqrSum(src, GpuMat(), buf);
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}
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//! finds global minimum and maximum array elements and returns their values
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CV_EXPORTS void minMax(InputArray src, double* minVal, double* maxVal, InputArray mask, GpuMat& buf);
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static inline void minMax(InputArray src, double* minVal, double* maxVal=0, InputArray mask=noArray())
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{
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GpuMat buf;
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minMax(src, minVal, maxVal, mask, buf);
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}
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//! finds global minimum and maximum array elements and returns their values with locations
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CV_EXPORTS void minMaxLoc(InputArray src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
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InputArray mask, GpuMat& valbuf, GpuMat& locbuf);
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static inline void minMaxLoc(InputArray src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0,
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InputArray mask=noArray())
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{
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GpuMat valBuf, locBuf;
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minMaxLoc(src, minVal, maxVal, minLoc, maxLoc, mask, valBuf, locBuf);
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}
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//! counts non-zero array elements
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CV_EXPORTS int countNonZero(InputArray src, GpuMat& buf);
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static inline int countNonZero(const GpuMat& src)
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{
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GpuMat buf;
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return countNonZero(src, buf);
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}
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//! reduces a matrix to a vector
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CV_EXPORTS void reduce(InputArray mtx, OutputArray vec, int dim, int reduceOp, int dtype = -1, Stream& stream = Stream::Null());
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//! computes mean value and standard deviation of all or selected array elements
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//! supports only CV_8UC1 type
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CV_EXPORTS void meanStdDev(InputArray mtx, Scalar& mean, Scalar& stddev, GpuMat& buf);
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static inline void meanStdDev(InputArray src, Scalar& mean, Scalar& stddev)
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{
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GpuMat buf;
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meanStdDev(src, mean, stddev, buf);
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}
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//! computes the standard deviation of integral images
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//! supports only CV_32SC1 source type and CV_32FC1 sqr type
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//! output will have CV_32FC1 type
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CV_EXPORTS void rectStdDev(InputArray src, InputArray sqr, OutputArray dst, Rect rect, Stream& stream = Stream::Null());
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//! scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values
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CV_EXPORTS void normalize(InputArray src, OutputArray dst, double alpha, double beta,
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int norm_type, int dtype, InputArray mask, GpuMat& norm_buf, GpuMat& cvt_buf);
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static inline void normalize(InputArray src, OutputArray dst, double alpha = 1, double beta = 0,
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int norm_type = NORM_L2, int dtype = -1, InputArray mask = noArray())
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{
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GpuMat norm_buf;
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GpuMat cvt_buf;
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normalize(src, dst, alpha, beta, norm_type, dtype, mask, norm_buf, cvt_buf);
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}
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//! computes the integral image
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//! sum will have CV_32S type, but will contain unsigned int values
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//! supports only CV_8UC1 source type
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CV_EXPORTS void integral(InputArray src, OutputArray sum, GpuMat& buffer, Stream& stream = Stream::Null());
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static inline void integralBuffered(InputArray src, OutputArray sum, GpuMat& buffer, Stream& stream = Stream::Null())
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{
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integral(src, sum, buffer, stream);
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}
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static inline void integral(InputArray src, OutputArray sum, Stream& stream = Stream::Null())
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{
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GpuMat buffer;
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integral(src, sum, buffer, stream);
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}
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//! computes squared integral image
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//! result matrix will have 64F type, but will contain 64U values
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//! supports source images of 8UC1 type only
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CV_EXPORTS void sqrIntegral(InputArray src, OutputArray sqsum, GpuMat& buf, Stream& stream = Stream::Null());
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static inline void sqrIntegral(InputArray src, OutputArray sqsum, Stream& stream = Stream::Null())
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{
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GpuMat buffer;
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sqrIntegral(src, sqsum, buffer, stream);
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}
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CV_EXPORTS void gemm(InputArray src1, InputArray src2, double alpha,
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InputArray src3, double beta, OutputArray dst, int flags = 0, Stream& stream = Stream::Null());
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//! performs per-element multiplication of two full (not packed) Fourier spectrums
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//! supports 32FC2 matrixes only (interleaved format)
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CV_EXPORTS void mulSpectrums(InputArray src1, InputArray src2, OutputArray dst, int flags, bool conjB=false, Stream& stream = Stream::Null());
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//! performs per-element multiplication of two full (not packed) Fourier spectrums
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//! supports 32FC2 matrixes only (interleaved format)
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CV_EXPORTS void mulAndScaleSpectrums(InputArray src1, InputArray src2, OutputArray dst, int flags, float scale, bool conjB=false, Stream& stream = Stream::Null());
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//! Performs a forward or inverse discrete Fourier transform (1D or 2D) of floating point matrix.
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//! Param dft_size is the size of DFT transform.
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//!
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//! If the source matrix is not continous, then additional copy will be done,
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//! so to avoid copying ensure the source matrix is continous one. If you want to use
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//! preallocated output ensure it is continuous too, otherwise it will be reallocated.
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//!
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//! Being implemented via CUFFT real-to-complex transform result contains only non-redundant values
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//! in CUFFT's format. Result as full complex matrix for such kind of transform cannot be retrieved.
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//!
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//! For complex-to-real transform it is assumed that the source matrix is packed in CUFFT's format.
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CV_EXPORTS void dft(InputArray src, OutputArray dst, Size dft_size, int flags=0, Stream& stream = Stream::Null());
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//! computes convolution (or cross-correlation) of two images using discrete Fourier transform
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//! supports source images of 32FC1 type only
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//! result matrix will have 32FC1 type
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class CV_EXPORTS Convolution : public Algorithm
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{
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public:
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virtual void convolve(InputArray image, InputArray templ, OutputArray result, bool ccorr = false, Stream& stream = Stream::Null()) = 0;
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};
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CV_EXPORTS Ptr<Convolution> createConvolution(Size user_block_size = Size());
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__OPENCV_GPUARITHM_DEPR_BEFORE__ void convolve(InputArray image, InputArray templ, OutputArray result, bool ccorr = false, Stream& stream = Stream::Null()) __OPENCV_GPUARITHM_DEPR_AFTER__;
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inline void convolve(InputArray image, InputArray templ, OutputArray result, bool ccorr , Stream& stream)
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{
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createConvolution()->convolve(image, templ, result, ccorr, stream);
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}
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struct ConvolveBuf
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{
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Size result_size;
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Size block_size;
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Size user_block_size;
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Size dft_size;
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int spect_len;
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GpuMat image_spect, templ_spect, result_spect;
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GpuMat image_block, templ_block, result_data;
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void create(Size, Size){}
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static Size estimateBlockSize(Size, Size){ return Size(); }
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};
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__OPENCV_GPUARITHM_DEPR_BEFORE__ void convolve(InputArray image, InputArray templ, OutputArray result, bool ccorr, ConvolveBuf& buf, Stream& stream = Stream::Null()) __OPENCV_GPUARITHM_DEPR_AFTER__;
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inline void convolve(InputArray image, InputArray templ, OutputArray result, bool ccorr, ConvolveBuf& buf, Stream& stream)
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{
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createConvolution(buf.user_block_size)->convolve(image, templ, result, ccorr, stream);
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}
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}} // namespace cv { namespace gpu {
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#undef __OPENCV_GPUARITHM_DEPR_BEFORE__
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#undef __OPENCV_GPUARITHM_DEPR_AFTER__
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#endif /* __OPENCV_GPUARITHM_HPP__ */
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