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374 lines
18 KiB
374 lines
18 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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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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// 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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// 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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// * 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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// * 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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// * 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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// 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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// loss of use, data, or profits; or business interruption) however caused |
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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_CUDAARITHM_HPP__ |
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#define __OPENCV_CUDAARITHM_HPP__ |
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#ifndef __cplusplus |
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# error cudaarithm.hpp header must be compiled as C++ |
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#endif |
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#include "opencv2/core/cuda.hpp" |
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namespace cv { namespace cuda { |
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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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//! 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 matrices 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 matrices 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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}} // namespace cv { namespace cuda { |
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#endif /* __OPENCV_CUDAARITHM_HPP__ */
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