/*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. // 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_GPUARITHM_HPP__ #define __OPENCV_GPUARITHM_HPP__ #ifndef __cplusplus # error gpuarithm.hpp header must be compiled as C++ #endif #include "opencv2/core/gpu.hpp" namespace cv { namespace gpu { //! adds one matrix to another (dst = src1 + src2) CV_EXPORTS void add(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), int dtype = -1, Stream& stream = Stream::Null()); //! subtracts one matrix from another (dst = src1 - src2) CV_EXPORTS void subtract(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), int dtype = -1, Stream& stream = Stream::Null()); //! computes element-wise weighted product of the two arrays (dst = scale * src1 * src2) CV_EXPORTS void multiply(InputArray src1, InputArray src2, OutputArray dst, double scale = 1, int dtype = -1, Stream& stream = Stream::Null()); //! computes element-wise weighted quotient of the two arrays (dst = scale * (src1 / src2)) CV_EXPORTS void divide(InputArray src1, InputArray src2, OutputArray dst, double scale = 1, int dtype = -1, Stream& stream = Stream::Null()); //! computes element-wise weighted reciprocal of an array (dst = scale/src2) static inline void divide(double src1, InputArray src2, OutputArray dst, int dtype = -1, Stream& stream = Stream::Null()) { divide(src1, src2, dst, 1.0, dtype, stream); } //! computes element-wise absolute difference of two arrays (dst = abs(src1 - src2)) CV_EXPORTS void absdiff(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null()); //! computes absolute value of each matrix element CV_EXPORTS void abs(InputArray src, OutputArray dst, Stream& stream = Stream::Null()); //! computes square of each pixel in an image CV_EXPORTS void sqr(InputArray src, OutputArray dst, Stream& stream = Stream::Null()); //! computes square root of each pixel in an image CV_EXPORTS void sqrt(InputArray src, OutputArray dst, Stream& stream = Stream::Null()); //! computes exponent of each matrix element CV_EXPORTS void exp(InputArray src, OutputArray dst, Stream& stream = Stream::Null()); //! computes natural logarithm of absolute value of each matrix element CV_EXPORTS void log(InputArray src, OutputArray dst, Stream& stream = Stream::Null()); //! computes power of each matrix element: //! (dst(i,j) = pow( src(i,j) , power), if src.type() is integer //! (dst(i,j) = pow(fabs(src(i,j)), power), otherwise CV_EXPORTS void pow(InputArray src, double power, OutputArray dst, Stream& stream = Stream::Null()); //! compares elements of two arrays (dst = src1 src2) CV_EXPORTS void compare(InputArray src1, InputArray src2, OutputArray dst, int cmpop, Stream& stream = Stream::Null()); //! performs per-elements bit-wise inversion CV_EXPORTS void bitwise_not(InputArray src, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null()); //! calculates per-element bit-wise disjunction of two arrays CV_EXPORTS void bitwise_or(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null()); //! calculates per-element bit-wise conjunction of two arrays CV_EXPORTS void bitwise_and(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null()); //! calculates per-element bit-wise "exclusive or" operation CV_EXPORTS void bitwise_xor(InputArray src1, InputArray src2, OutputArray dst, InputArray mask = noArray(), Stream& stream = Stream::Null()); //! pixel by pixel right shift of an image by a constant value //! supports 1, 3 and 4 channels images with integers elements CV_EXPORTS void rshift(InputArray src, Scalar_ val, OutputArray dst, Stream& stream = Stream::Null()); //! pixel by pixel left shift of an image by a constant value //! supports 1, 3 and 4 channels images with CV_8U, CV_16U or CV_32S depth CV_EXPORTS void lshift(InputArray src, Scalar_ val, OutputArray dst, Stream& stream = Stream::Null()); //! computes per-element minimum of two arrays (dst = min(src1, src2)) CV_EXPORTS void min(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null()); //! computes per-element maximum of two arrays (dst = max(src1, src2)) CV_EXPORTS void max(InputArray src1, InputArray src2, OutputArray dst, Stream& stream = Stream::Null()); //! computes the weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma) CV_EXPORTS void addWeighted(const GpuMat& src1, double alpha, const GpuMat& src2, double beta, double gamma, GpuMat& dst, int dtype = -1, Stream& stream = Stream::Null()); //! adds scaled array to another one (dst = alpha*src1 + src2) static inline void scaleAdd(const GpuMat& src1, double alpha, const GpuMat& src2, GpuMat& dst, Stream& stream = Stream::Null()) { addWeighted(src1, alpha, src2, 1.0, 0.0, dst, -1, stream); } //! implements generalized matrix product algorithm GEMM from BLAS CV_EXPORTS void gemm(const GpuMat& src1, const GpuMat& src2, double alpha, const GpuMat& src3, double beta, GpuMat& dst, int flags = 0, Stream& stream = Stream::Null()); //! transposes the matrix //! supports matrix with element size = 1, 4 and 8 bytes (CV_8UC1, CV_8UC4, CV_16UC2, CV_32FC1, etc) CV_EXPORTS void transpose(const GpuMat& src1, GpuMat& dst, Stream& stream = Stream::Null()); //! reverses the order of the rows, columns or both in a matrix //! supports 1, 3 and 4 channels images with CV_8U, CV_16U, CV_32S or CV_32F depth CV_EXPORTS void flip(const GpuMat& a, GpuMat& b, int flipCode, Stream& stream = Stream::Null()); //! transforms 8-bit unsigned integers using lookup table: dst(i)=lut(src(i)) //! destination array will have the depth type as lut and the same channels number as source //! supports CV_8UC1, CV_8UC3 types CV_EXPORTS void LUT(const GpuMat& src, const Mat& lut, GpuMat& dst, Stream& stream = Stream::Null()); //! makes multi-channel array out of several single-channel arrays CV_EXPORTS void merge(const GpuMat* src, size_t n, GpuMat& dst, Stream& stream = Stream::Null()); //! makes multi-channel array out of several single-channel arrays CV_EXPORTS void merge(const std::vector& src, GpuMat& dst, Stream& stream = Stream::Null()); //! copies each plane of a multi-channel array to a dedicated array CV_EXPORTS void split(const GpuMat& src, GpuMat* dst, Stream& stream = Stream::Null()); //! copies each plane of a multi-channel array to a dedicated array CV_EXPORTS void split(const GpuMat& src, std::vector& dst, Stream& stream = Stream::Null()); //! computes magnitude of complex (x(i).re, x(i).im) vector //! supports only CV_32FC2 type CV_EXPORTS void magnitude(const GpuMat& xy, GpuMat& magnitude, Stream& stream = Stream::Null()); //! computes squared magnitude of complex (x(i).re, x(i).im) vector //! supports only CV_32FC2 type CV_EXPORTS void magnitudeSqr(const GpuMat& xy, GpuMat& magnitude, Stream& stream = Stream::Null()); //! computes magnitude of each (x(i), y(i)) vector //! supports only floating-point source CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, Stream& stream = Stream::Null()); //! computes squared magnitude of each (x(i), y(i)) vector //! supports only floating-point source CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, Stream& stream = Stream::Null()); //! computes angle (angle(i)) of each (x(i), y(i)) vector //! supports only floating-point source CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees = false, Stream& stream = Stream::Null()); //! converts Cartesian coordinates to polar //! supports only floating-point source CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees = false, Stream& stream = Stream::Null()); //! converts polar coordinates to Cartesian //! supports only floating-point source CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees = false, Stream& stream = Stream::Null()); //! 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 CV_EXPORTS void normalize(const GpuMat& src, GpuMat& dst, double alpha = 1, double beta = 0, int norm_type = NORM_L2, int dtype = -1, const GpuMat& mask = GpuMat()); CV_EXPORTS void normalize(const GpuMat& src, GpuMat& dst, double a, double b, int norm_type, int dtype, const GpuMat& mask, GpuMat& norm_buf, GpuMat& cvt_buf); //! computes norm of array //! supports NORM_INF, NORM_L1, NORM_L2 //! supports all matrices except 64F CV_EXPORTS double norm(const GpuMat& src1, int normType=NORM_L2); CV_EXPORTS double norm(const GpuMat& src1, int normType, GpuMat& buf); CV_EXPORTS double norm(const GpuMat& src1, int normType, const GpuMat& mask, GpuMat& buf); //! computes norm of the difference between two arrays //! supports NORM_INF, NORM_L1, NORM_L2 //! supports only CV_8UC1 type CV_EXPORTS double norm(const GpuMat& src1, const GpuMat& src2, int normType=NORM_L2); //! computes sum of array elements //! supports only single channel images CV_EXPORTS Scalar sum(const GpuMat& src); CV_EXPORTS Scalar sum(const GpuMat& src, GpuMat& buf); CV_EXPORTS Scalar sum(const GpuMat& src, const GpuMat& mask, GpuMat& buf); //! computes sum of array elements absolute values //! supports only single channel images CV_EXPORTS Scalar absSum(const GpuMat& src); CV_EXPORTS Scalar absSum(const GpuMat& src, GpuMat& buf); CV_EXPORTS Scalar absSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf); //! computes squared sum of array elements //! supports only single channel images CV_EXPORTS Scalar sqrSum(const GpuMat& src); CV_EXPORTS Scalar sqrSum(const GpuMat& src, GpuMat& buf); CV_EXPORTS Scalar sqrSum(const GpuMat& src, const GpuMat& mask, GpuMat& buf); //! finds global minimum and maximum array elements and returns their values CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal=0, const GpuMat& mask=GpuMat()); CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf); //! finds global minimum and maximum array elements and returns their values with locations CV_EXPORTS void minMaxLoc(const GpuMat& src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0, const GpuMat& mask=GpuMat()); CV_EXPORTS void minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf); //! counts non-zero array elements CV_EXPORTS int countNonZero(const GpuMat& src); CV_EXPORTS int countNonZero(const GpuMat& src, GpuMat& buf); //! reduces a matrix to a vector CV_EXPORTS void reduce(const GpuMat& mtx, GpuMat& vec, int dim, int reduceOp, int dtype = -1, Stream& stream = Stream::Null()); //! computes mean value and standard deviation of all or selected array elements //! supports only CV_8UC1 type CV_EXPORTS void meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev); //! buffered version CV_EXPORTS void meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev, GpuMat& buf); //! computes the standard deviation of integral images //! supports only CV_32SC1 source type and CV_32FC1 sqr type //! output will have CV_32FC1 type CV_EXPORTS void rectStdDev(const GpuMat& src, const GpuMat& sqr, GpuMat& dst, const Rect& rect, Stream& stream = Stream::Null()); //! copies 2D array to a larger destination array and pads borders with user-specifiable constant CV_EXPORTS void copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom, int left, int right, int borderType, const Scalar& value = Scalar(), Stream& stream = Stream::Null()); //! applies fixed threshold to the image CV_EXPORTS double threshold(const GpuMat& src, GpuMat& dst, double thresh, double maxval, int type, Stream& stream = Stream::Null()); //! computes the integral image //! sum will have CV_32S type, but will contain unsigned int values //! supports only CV_8UC1 source type CV_EXPORTS void integral(const GpuMat& src, GpuMat& sum, Stream& stream = Stream::Null()); //! buffered version CV_EXPORTS void integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer, Stream& stream = Stream::Null()); //! computes squared integral image //! result matrix will have 64F type, but will contain 64U values //! supports source images of 8UC1 type only CV_EXPORTS void sqrIntegral(const GpuMat& src, GpuMat& sqsum, Stream& stream = Stream::Null()); //! performs per-element multiplication of two full (not packed) Fourier spectrums //! supports 32FC2 matrixes only (interleaved format) CV_EXPORTS void mulSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, bool conjB=false, Stream& stream = Stream::Null()); //! performs per-element multiplication of two full (not packed) Fourier spectrums //! supports 32FC2 matrixes only (interleaved format) CV_EXPORTS void mulAndScaleSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, float scale, bool conjB=false, Stream& stream = Stream::Null()); //! Performs a forward or inverse discrete Fourier transform (1D or 2D) of floating point matrix. //! Param dft_size is the size of DFT transform. //! //! If the source matrix is not continous, then additional copy will be done, //! so to avoid copying ensure the source matrix is continous one. If you want to use //! preallocated output ensure it is continuous too, otherwise it will be reallocated. //! //! Being implemented via CUFFT real-to-complex transform result contains only non-redundant values //! in CUFFT's format. Result as full complex matrix for such kind of transform cannot be retrieved. //! //! For complex-to-real transform it is assumed that the source matrix is packed in CUFFT's format. CV_EXPORTS void dft(const GpuMat& src, GpuMat& dst, Size dft_size, int flags=0, Stream& stream = Stream::Null()); struct CV_EXPORTS ConvolveBuf { Size result_size; Size block_size; Size user_block_size; Size dft_size; int spect_len; GpuMat image_spect, templ_spect, result_spect; GpuMat image_block, templ_block, result_data; void create(Size image_size, Size templ_size); static Size estimateBlockSize(Size result_size, Size templ_size); }; //! computes convolution (or cross-correlation) of two images using discrete Fourier transform //! supports source images of 32FC1 type only //! result matrix will have 32FC1 type CV_EXPORTS void convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, bool ccorr = false); CV_EXPORTS void convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, bool ccorr, ConvolveBuf& buf, Stream& stream = Stream::Null()); }} // namespace cv { namespace gpu { #endif /* __OPENCV_GPUARITHM_HPP__ */