/*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 GpuMaterials 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_GPU_HPP__ #define __OPENCV_GPU_HPP__ #include #include "opencv2/core/core.hpp" #include "opencv2/imgproc/imgproc.hpp" #include "opencv2/gpu/devmem2d.hpp" namespace cv { namespace gpu { //////////////////////////////// Initialization //////////////////////// //! This is the only function that do not throw exceptions if the library is compiled without Cuda. CV_EXPORTS int getCudaEnabledDeviceCount(); //! Functions below throw cv::Expception if the library is compiled without Cuda. CV_EXPORTS string getDeviceName(int device); CV_EXPORTS void setDevice(int device); CV_EXPORTS int getDevice(); CV_EXPORTS void getComputeCapability(int device, int& major, int& minor); CV_EXPORTS int getNumberOfSMs(int device); CV_EXPORTS void getGpuMemInfo(size_t& free, size_t& total); //////////////////////////////// GpuMat //////////////////////////////// class Stream; class CudaMem; //! Smart pointer for GPU memory with reference counting. Its interface is mostly similar with cv::Mat. class CV_EXPORTS GpuMat { public: //! default constructor GpuMat(); //! constructs GpuMatrix of the specified size and type // (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.) GpuMat(int _rows, int _cols, int _type); GpuMat(Size _size, int _type); //! constucts GpuMatrix and fills it with the specified value _s. GpuMat(int _rows, int _cols, int _type, const Scalar& _s); GpuMat(Size _size, int _type, const Scalar& _s); //! copy constructor GpuMat(const GpuMat& m); //! constructor for GpuMatrix headers pointing to user-allocated data GpuMat(int _rows, int _cols, int _type, void* _data, size_t _step = Mat::AUTO_STEP); GpuMat(Size _size, int _type, void* _data, size_t _step = Mat::AUTO_STEP); //! creates a matrix header for a part of the bigger matrix GpuMat(const GpuMat& m, const Range& rowRange, const Range& colRange); GpuMat(const GpuMat& m, const Rect& roi); //! builds GpuMat from Mat. Perfom blocking upload to device. explicit GpuMat (const Mat& m); //! destructor - calls release() ~GpuMat(); //! assignment operators GpuMat& operator = (const GpuMat& m); //! assignment operator. Perfom blocking upload to device. GpuMat& operator = (const Mat& m); //! returns lightweight DevMem2D_ structure for passing to nvcc-compiled code. // Contains just image size, data ptr and step. template operator DevMem2D_() const; //! pefroms blocking upload data to GpuMat. . void upload(const cv::Mat& m); //! upload async void upload(const CudaMem& m, Stream& stream); //! downloads data from device to host memory. Blocking calls. operator Mat() const; void download(cv::Mat& m) const; //! download async void download(CudaMem& m, Stream& stream) const; //! returns a new GpuMatrix header for the specified row GpuMat row(int y) const; //! returns a new GpuMatrix header for the specified column GpuMat col(int x) const; //! ... for the specified row span GpuMat rowRange(int startrow, int endrow) const; GpuMat rowRange(const Range& r) const; //! ... for the specified column span GpuMat colRange(int startcol, int endcol) const; GpuMat colRange(const Range& r) const; //! returns deep copy of the GpuMatrix, i.e. the data is copied GpuMat clone() const; //! copies the GpuMatrix content to "m". // It calls m.create(this->size(), this->type()). void copyTo( GpuMat& m ) const; //! copies those GpuMatrix elements to "m" that are marked with non-zero mask elements. void copyTo( GpuMat& m, const GpuMat& mask ) const; //! converts GpuMatrix to another datatype with optional scalng. See cvConvertScale. void convertTo( GpuMat& m, int rtype, double alpha=1, double beta=0 ) const; void assignTo( GpuMat& m, int type=-1 ) const; //! sets every GpuMatrix element to s GpuMat& operator = (const Scalar& s); //! sets some of the GpuMatrix elements to s, according to the mask GpuMat& setTo(const Scalar& s, const GpuMat& mask=GpuMat()); //! creates alternative GpuMatrix header for the same data, with different // number of channels and/or different number of rows. see cvReshape. GpuMat reshape(int _cn, int _rows=0) const; //! allocates new GpuMatrix data unless the GpuMatrix already has specified size and type. // previous data is unreferenced if needed. void create(int _rows, int _cols, int _type); void create(Size _size, int _type); //! decreases reference counter; // deallocate the data when reference counter reaches 0. void release(); //! swaps with other smart pointer void swap(GpuMat& mat); //! locates GpuMatrix header within a parent GpuMatrix. See below void locateROI( Size& wholeSize, Point& ofs ) const; //! moves/resizes the current GpuMatrix ROI inside the parent GpuMatrix. GpuMat& adjustROI( int dtop, int dbottom, int dleft, int dright ); //! extracts a rectangular sub-GpuMatrix // (this is a generalized form of row, rowRange etc.) GpuMat operator()( Range rowRange, Range colRange ) const; GpuMat operator()( const Rect& roi ) const; //! returns true iff the GpuMatrix data is continuous // (i.e. when there are no gaps between successive rows). // similar to CV_IS_GpuMat_CONT(cvGpuMat->type) bool isContinuous() const; //! returns element size in bytes, // similar to CV_ELEM_SIZE(cvMat->type) size_t elemSize() const; //! returns the size of element channel in bytes. size_t elemSize1() const; //! returns element type, similar to CV_MAT_TYPE(cvMat->type) int type() const; //! returns element type, similar to CV_MAT_DEPTH(cvMat->type) int depth() const; //! returns element type, similar to CV_MAT_CN(cvMat->type) int channels() const; //! returns step/elemSize1() size_t step1() const; //! returns GpuMatrix size: // width == number of columns, height == number of rows Size size() const; //! returns true if GpuMatrix data is NULL bool empty() const; //! returns pointer to y-th row uchar* ptr(int y=0); const uchar* ptr(int y=0) const; //! template version of the above method template _Tp* ptr(int y=0); template const _Tp* ptr(int y=0) const; //! matrix transposition GpuMat t() const; /*! includes several bit-fields: - the magic signature - continuity flag - depth - number of channels */ int flags; //! the number of rows and columns int rows, cols; //! a distance between successive rows in bytes; includes the gap if any size_t step; //! pointer to the data uchar* data; //! pointer to the reference counter; // when GpuMatrix points to user-allocated data, the pointer is NULL int* refcount; //! helper fields used in locateROI and adjustROI uchar* datastart; uchar* dataend; }; //////////////////////////////// CudaMem //////////////////////////////// // CudaMem is limited cv::Mat with page locked memory allocation. // Page locked memory is only needed for async and faster coping to GPU. // It is convertable to cv::Mat header without reference counting // so you can use it with other opencv functions. class CV_EXPORTS CudaMem { public: enum { ALLOC_PAGE_LOCKED = 1, ALLOC_ZEROCOPY = 2, ALLOC_WRITE_COMBINED = 4 }; CudaMem(); CudaMem(const CudaMem& m); CudaMem(int _rows, int _cols, int _type, int _alloc_type = ALLOC_PAGE_LOCKED); CudaMem(Size _size, int _type, int _alloc_type = ALLOC_PAGE_LOCKED); //! creates from cv::Mat with coping data explicit CudaMem(const Mat& m, int _alloc_type = ALLOC_PAGE_LOCKED); ~CudaMem(); CudaMem& operator = (const CudaMem& m); //! returns deep copy of the matrix, i.e. the data is copied CudaMem clone() const; //! allocates new matrix data unless the matrix already has specified size and type. void create(int _rows, int _cols, int _type, int _alloc_type = ALLOC_PAGE_LOCKED); void create(Size _size, int _type, int _alloc_type = ALLOC_PAGE_LOCKED); //! decrements reference counter and released memory if needed. void release(); //! returns matrix header with disabled reference counting for CudaMem data. Mat createMatHeader() const; operator Mat() const; //! maps host memory into device address space and returns GpuMat header for it. Throws exception if not supported by hardware. GpuMat createGpuMatHeader() const; operator GpuMat() const; //returns if host memory can be mapperd to gpu address space; static bool can_device_map_to_host(); // Please see cv::Mat for descriptions bool isContinuous() const; size_t elemSize() const; size_t elemSize1() const; int type() const; int depth() const; int channels() const; size_t step1() const; Size size() const; bool empty() const; // Please see cv::Mat for descriptions int flags; int rows, cols; size_t step; uchar* data; int* refcount; uchar* datastart; uchar* dataend; int alloc_type; }; //////////////////////////////// CudaStream //////////////////////////////// // Encapculates Cuda Stream. Provides interface for async coping. // Passed to each function that supports async kernel execution. // Reference counting is enabled class CV_EXPORTS Stream { public: Stream(); ~Stream(); Stream(const Stream&); Stream& operator=(const Stream&); bool queryIfComplete(); void waitForCompletion(); //! downloads asynchronously. // Warning! cv::Mat must point to page locked memory (i.e. to CudaMem data or to its subMat) void enqueueDownload(const GpuMat& src, CudaMem& dst); void enqueueDownload(const GpuMat& src, Mat& dst); //! uploads asynchronously. // Warning! cv::Mat must point to page locked memory (i.e. to CudaMem data or to its ROI) void enqueueUpload(const CudaMem& src, GpuMat& dst); void enqueueUpload(const Mat& src, GpuMat& dst); void enqueueCopy(const GpuMat& src, GpuMat& dst); void enqueueMemSet(const GpuMat& src, Scalar val); void enqueueMemSet(const GpuMat& src, Scalar val, const GpuMat& mask); // converts matrix type, ex from float to uchar depending on type void enqueueConvert(const GpuMat& src, GpuMat& dst, int type, double a = 1, double b = 0); private: void create(); void release(); struct Impl; Impl *impl; friend struct StreamAccessor; }; ////////////////////////////// Arithmetics /////////////////////////////////// //! adds one matrix to another (c = a + b) //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types CV_EXPORTS void add(const GpuMat& a, const GpuMat& b, GpuMat& c); //! adds scalar to a matrix (c = a + s) //! supports CV_32FC1 and CV_32FC2 type CV_EXPORTS void add(const GpuMat& a, const Scalar& sc, GpuMat& c); //! subtracts one matrix from another (c = a - b) //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types CV_EXPORTS void subtract(const GpuMat& a, const GpuMat& b, GpuMat& c); //! subtracts scalar from a matrix (c = a - s) //! supports CV_32FC1 and CV_32FC2 type CV_EXPORTS void subtract(const GpuMat& a, const Scalar& sc, GpuMat& c); //! computes element-wise product of the two arrays (c = a * b) //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types CV_EXPORTS void multiply(const GpuMat& a, const GpuMat& b, GpuMat& c); //! multiplies matrix to a scalar (c = a * s) //! supports CV_32FC1 and CV_32FC2 type CV_EXPORTS void multiply(const GpuMat& a, const Scalar& sc, GpuMat& c); //! computes element-wise quotient of the two arrays (c = a / b) //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types CV_EXPORTS void divide(const GpuMat& a, const GpuMat& b, GpuMat& c); //! computes element-wise quotient of matrix and scalar (c = a / s) //! supports CV_32FC1 and CV_32FC2 type CV_EXPORTS void divide(const GpuMat& a, const Scalar& sc, GpuMat& c); //! transposes the matrix //! supports only CV_8UC1 type CV_EXPORTS void transpose(const GpuMat& src1, GpuMat& dst); //! computes element-wise absolute difference of two arrays (c = abs(a - b)) //! supports CV_8UC1, CV_8UC4, CV_32SC1, CV_32FC1 types CV_EXPORTS void absdiff(const GpuMat& a, const GpuMat& b, GpuMat& c); //! computes element-wise absolute difference of array and scalar (c = abs(a - s)) //! supports only CV_32FC1 type CV_EXPORTS void absdiff(const GpuMat& a, const Scalar& s, GpuMat& c); //! compares elements of two arrays (c = a b) //! supports CV_8UC4, CV_32FC1 types CV_EXPORTS void compare(const GpuMat& a, const GpuMat& b, GpuMat& c, int cmpop); //! 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); //! computes norm of array //! supports NORM_INF, NORM_L1, NORM_L2 //! supports only CV_8UC1 type CV_EXPORTS double norm(const GpuMat& src1, int normType=NORM_L2); //! 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); //! reverses the order of the rows, columns or both in a matrix //! supports CV_8UC1, CV_8UC4 types CV_EXPORTS void flip(const GpuMat& a, GpuMat& b, int flipCode); //! computes sum of array elements //! supports CV_8UC1, CV_8UC4 types //! disabled until fix crash CV_EXPORTS Scalar sum(const GpuMat& m); //! finds global minimum and maximum array elements and returns their values //! supports CV_8UC1 and CV_8UC4 type //! disabled until fix npp bug CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal = 0); //! 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); //! makes multi-channel array out of several single-channel arrays CV_EXPORTS void merge(const GpuMat* src, size_t n, GpuMat& dst); //! makes multi-channel array out of several single-channel arrays CV_EXPORTS void merge(const vector& src, GpuMat& dst); //! makes multi-channel array out of several single-channel arrays (async version) CV_EXPORTS void merge(const GpuMat* src, size_t n, GpuMat& dst, const Stream& stream); //! makes multi-channel array out of several single-channel arrays (async version) CV_EXPORTS void merge(const vector& src, GpuMat& dst, const Stream& stream); //! copies each plane of a multi-channel array to a dedicated array CV_EXPORTS void split(const GpuMat& src, GpuMat* dst); //! copies each plane of a multi-channel array to a dedicated array CV_EXPORTS void split(const GpuMat& src, vector& dst); //! copies each plane of a multi-channel array to a dedicated array (async version) CV_EXPORTS void split(const GpuMat& src, GpuMat* dst, const Stream& stream); //! copies each plane of a multi-channel array to a dedicated array (async version) CV_EXPORTS void split(const GpuMat& src, vector& dst, const Stream& stream); //! computes exponent of each matrix element (b = e**a) //! supports only CV_32FC1 type CV_EXPORTS void exp(const GpuMat& a, GpuMat& b); //! computes natural logarithm of absolute value of each matrix element: b = log(abs(a)) //! supports only CV_32FC1 type CV_EXPORTS void log(const GpuMat& a, GpuMat& b); //! computes magnitude of each (x(i), y(i)) vector //! supports only CV_32FC1 type CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude); //! computes magnitude of complex (x(i).re, x(i).im) vector //! supports only CV_32FC2 type CV_EXPORTS void magnitude(const GpuMat& x, GpuMat& magnitude); //! computes squared magnitude of each (x(i), y(i)) vector //! supports only CV_32FC1 type CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude); //! computes squared magnitude of complex (x(i).re, x(i).im) vector //! supports only CV_32FC2 type CV_EXPORTS void magnitudeSqr(const GpuMat& x, GpuMat& magnitude); ////////////////////////////// Image processing ////////////////////////////// //! DST[x,y] = SRC[xmap[x,y],ymap[x,y]] with bilinear interpolation. //! supports CV_8UC1, CV_8UC3 source types and CV_32FC1 map type CV_EXPORTS void remap(const GpuMat& src, GpuMat& dst, const GpuMat& xmap, const GpuMat& ymap); //! Does mean shift filtering on GPU. CV_EXPORTS void meanShiftFiltering(const GpuMat& src, GpuMat& dst, int sp, int sr, TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1)); //! Does mean shift procedure on GPU. CV_EXPORTS void meanShiftProc(const GpuMat& src, GpuMat& dstr, GpuMat& dstsp, int sp, int sr, TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1)); //! Does mean shift segmentation with elimiation of small regions. CV_EXPORTS void meanShiftSegmentation(const GpuMat& src, Mat& dst, int sp, int sr, int minsize, TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1)); //! Does coloring of disparity image: [0..ndisp) -> [0..240, 1, 1] in HSV. //! Supported types of input disparity: CV_8U, CV_16S. //! Output disparity has CV_8UC4 type in BGRA format (alpha = 255). CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp); //! Acync version CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, const Stream& stream); //! Reprojects disparity image to 3D space. //! Supports CV_8U and CV_16S types of input disparity. //! The output is a 4-channel floating-point (CV_32FC4) matrix. //! Each element of this matrix will contain the 3D coordinates of the point (x,y,z,1), computed from the disparity map. //! Q is the 4x4 perspective transformation matrix that can be obtained with cvStereoRectify. CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q); //! Acync version CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, const Stream& stream); //! converts image from one color space to another CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn = 0); //! Acync version CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn, const Stream& stream); //! applies fixed threshold to the image. //! Now supports only THRESH_TRUNC threshold type and one channels float source. CV_EXPORTS double threshold(const GpuMat& src, GpuMat& dst, double thresh); //! resizes the image //! Supports INTER_NEAREST, INTER_LINEAR //! supports CV_8UC1, CV_8UC4 types CV_EXPORTS void resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx=0, double fy=0, int interpolation = INTER_LINEAR); //! warps the image using affine transformation //! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC CV_EXPORTS void warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR); //! warps the image using perspective transformation //! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC CV_EXPORTS void warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR); //! rotate 8bit single or four channel image //! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC //! supports CV_8UC1, CV_8UC4 types CV_EXPORTS void rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift = 0, double yShift = 0, int interpolation = INTER_LINEAR); //! copies 2D array to a larger destination array and pads borders with user-specifiable constant //! supports CV_8UC1, CV_8UC4, CV_32SC1 types CV_EXPORTS void copyMakeBorder(const GpuMat& src, GpuMat& dst, int top, int bottom, int left, int right, const Scalar& value = Scalar()); //! computes the integral image and integral for the squared image //! sum will have CV_32S type, sqsum - CV32F type //! supports only CV_32FC1 source type CV_EXPORTS void integral(GpuMat& src, GpuMat& sum, GpuMat& sqsum); //! 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); //! applies Canny edge detector and produces the edge map //! supprots only CV_8UC1 source type //! disabled until fix crash CV_EXPORTS void Canny(const GpuMat& image, GpuMat& edges, double threshold1, double threshold2, int apertureSize = 3); //////////////////////////////// Filter Engine //////////////////////////////// /*! The Base Class for 1D or Row-wise Filters This is the base class for linear or non-linear filters that process 1D data. In particular, such filters are used for the "horizontal" filtering parts in separable filters. */ class CV_EXPORTS BaseRowFilter_GPU { public: BaseRowFilter_GPU(int ksize_, int anchor_) : ksize(ksize_), anchor(anchor_) {} virtual ~BaseRowFilter_GPU() {} virtual void operator()(const GpuMat& src, GpuMat& dst) = 0; int ksize, anchor; }; /*! The Base Class for Column-wise Filters This is the base class for linear or non-linear filters that process columns of 2D arrays. Such filters are used for the "vertical" filtering parts in separable filters. */ class CV_EXPORTS BaseColumnFilter_GPU { public: BaseColumnFilter_GPU(int ksize_, int anchor_) : ksize(ksize_), anchor(anchor_) {} virtual ~BaseColumnFilter_GPU() {} virtual void operator()(const GpuMat& src, GpuMat& dst) = 0; int ksize, anchor; }; /*! The Base Class for Non-Separable 2D Filters. This is the base class for linear or non-linear 2D filters. */ class CV_EXPORTS BaseFilter_GPU { public: BaseFilter_GPU(const Size& ksize_, const Point& anchor_) : ksize(ksize_), anchor(anchor_) {} virtual ~BaseFilter_GPU() {} virtual void operator()(const GpuMat& src, GpuMat& dst) = 0; Size ksize; Point anchor; }; /*! The Base Class for Filter Engine. The class can be used to apply an arbitrary filtering operation to an image. It contains all the necessary intermediate buffers. */ class CV_EXPORTS FilterEngine_GPU { public: virtual ~FilterEngine_GPU() {} virtual void apply(const GpuMat& src, GpuMat& dst, Rect roi = Rect(0,0,-1,-1)) = 0; }; //! returns the non-separable filter engine with the specified filter CV_EXPORTS Ptr createFilter2D_GPU(const Ptr filter2D); //! returns the separable filter engine with the specified filters CV_EXPORTS Ptr createSeparableFilter_GPU(const Ptr& rowFilter, const Ptr& columnFilter, bool rowFilterFirst = true); //! returns horizontal 1D box filter //! supports only CV_8UC1 source type and CV_32FC1 sum type CV_EXPORTS Ptr getRowSumFilter_GPU(int srcType, int sumType, int ksize, int anchor = -1); //! returns vertical 1D box filter //! supports only CV_8UC1 sum type and CV_32FC1 dst type CV_EXPORTS Ptr getColumnSumFilter_GPU(int sumType, int dstType, int ksize, int anchor = -1); //! returns 2D box filter //! supports CV_8UC1 and CV_8UC4 source type, dst type must be the same as source type CV_EXPORTS Ptr getBoxFilter_GPU(int srcType, int dstType, const Size& ksize, Point anchor = Point(-1, -1)); //! returns box filter engine CV_EXPORTS Ptr createBoxFilter_GPU(int srcType, int dstType, const Size& ksize, const Point& anchor = Point(-1,-1)); //! returns 2D morphological filter //! only MORPH_ERODE and MORPH_DILATE are supported //! supports CV_8UC1 and CV_8UC4 types //! kernel must have CV_8UC1 type, one rows and cols == ksize.width * ksize.height CV_EXPORTS Ptr getMorphologyFilter_GPU(int op, int type, const GpuMat& kernel, const Size& ksize, Point anchor=Point(-1,-1)); //! returns morphological filter engine. Only MORPH_ERODE and MORPH_DILATE are supported. CV_EXPORTS Ptr createMorphologyFilter_GPU(int op, int type, const Mat& kernel, const Point& anchor = Point(-1,-1), int iterations = 1); //! returns 2D filter with the specified kernel //! supports CV_8UC1 and CV_8UC4 types //! kernel must have CV_8UC1 type, one rows and cols == ksize.width * ksize.height CV_EXPORTS Ptr getLinearFilter_GPU(int srcType, int dstType, const GpuMat& kernel, const Size& ksize, Point anchor = Point(-1, -1), int nDivisor = 1); //! returns the non-separable linear filter engine CV_EXPORTS Ptr createLinearFilter_GPU(int srcType, int dstType, const Mat& kernel, const Point& anchor = Point(-1,-1)); //! returns the primitive row filter with the specified kernel CV_EXPORTS Ptr getLinearRowFilter_GPU(int srcType, int bufType, const GpuMat& rowKernel, int anchor = -1, int nDivisor = 1); //! returns the primitive column filter with the specified kernel CV_EXPORTS Ptr getLinearColumnFilter_GPU(int bufType, int dstType, const GpuMat& columnKernel, int anchor = -1, int nDivisor = 1); //! returns the separable linear filter engine CV_EXPORTS Ptr createSeparableLinearFilter_GPU(int srcType, int dstType, const Mat& rowKernel, const Mat& columnKernel, const Point& anchor = Point(-1,-1), bool rowFilterFirst = true); //! returns filter engine for the generalized Sobel operator CV_EXPORTS Ptr createDerivFilter_GPU(int srcType, int dstType, int dx, int dy, int ksize); //! returns the Gaussian filter engine CV_EXPORTS Ptr createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2 = 0); //! returns maximum filter CV_EXPORTS Ptr getMaxFilter_GPU(int srcType, int dstType, const Size& ksize, Point anchor = Point(-1,-1)); //! returns minimum filter CV_EXPORTS Ptr getMinFilter_GPU(int srcType, int dstType, const Size& ksize, Point anchor = Point(-1,-1)); //! smooths the image using the normalized box filter //! supports CV_8UC1, CV_8UC4 types CV_EXPORTS void boxFilter(const GpuMat& src, GpuMat& dst, int ddepth, Size ksize, Point anchor = Point(-1,-1)); //! a synonym for normalized box filter static inline void blur(const GpuMat& src, GpuMat& dst, Size ksize, Point anchor = Point(-1,-1)) { boxFilter(src, dst, -1, ksize, anchor); } //! erodes the image (applies the local minimum operator) CV_EXPORTS void erode( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1); //! dilates the image (applies the local maximum operator) CV_EXPORTS void dilate( const GpuMat& src, GpuMat& dst, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1); //! applies an advanced morphological operation to the image CV_EXPORTS void morphologyEx( const GpuMat& src, GpuMat& dst, int op, const Mat& kernel, Point anchor = Point(-1, -1), int iterations = 1); //! applies non-separable 2D linear filter to the image CV_EXPORTS void filter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernel, Point anchor=Point(-1,-1)); //! applies separable 2D linear filter to the image CV_EXPORTS void sepFilter2D(const GpuMat& src, GpuMat& dst, int ddepth, const Mat& kernelX, const Mat& kernelY, Point anchor = Point(-1,-1), bool rowFilterFirst = true); //! applies generalized Sobel operator to the image CV_EXPORTS void Sobel(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, int ksize = 3, double scale = 1); //! applies the vertical or horizontal Scharr operator to the image CV_EXPORTS void Scharr(const GpuMat& src, GpuMat& dst, int ddepth, int dx, int dy, double scale = 1); //! smooths the image using Gaussian filter. CV_EXPORTS void GaussianBlur(const GpuMat& src, GpuMat& dst, Size ksize, double sigma1, double sigma2 = 0); //! applies Laplacian operator to the image //! supports only ksize = 1 and ksize = 3 CV_EXPORTS void Laplacian(const GpuMat& src, GpuMat& dst, int ddepth, int ksize = 1, double scale = 1); //////////////////////////////// Image Labeling //////////////////////////////// //!performs labeling via graph cuts CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels, GpuMat& buf); ////////////////////////////////// Histograms ////////////////////////////////// //! Compute levels with even distribution. levels will have 1 row and nLevels cols and CV_32SC1 type. CV_EXPORTS void evenLevels(GpuMat& levels, int nLevels, int lowerLevel, int upperLevel); //! Calculates histogram with evenly distributed bins for signle channel source. //! Supports CV_8UC1, CV_16UC1 and CV_16SC1 source types. //! Output hist will have one row and histSize cols and CV_32SC1 type. CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel); //! Calculates histogram with evenly distributed bins for four-channel source. //! All channels of source are processed separately. //! Supports CV_8UC4, CV_16UC4 and CV_16SC4 source types. //! Output hist[i] will have one row and histSize[i] cols and CV_32SC1 type. CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4]); //! Calculates histogram with bins determined by levels array. //! levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise. //! Supports CV_8UC1, CV_16UC1, CV_16SC1 and CV_32FC1 source types. //! Output hist will have one row and (levels.cols-1) cols and CV_32SC1 type. CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels); //! Calculates histogram with bins determined by levels array. //! All levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise. //! All channels of source are processed separately. //! Supports CV_8UC4, CV_16UC4, CV_16SC4 and CV_32FC4 source types. //! Output hist[i] will have one row and (levels[i].cols-1) cols and CV_32SC1 type. CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4]); //////////////////////////////// StereoBM_GPU //////////////////////////////// class CV_EXPORTS StereoBM_GPU { public: enum { BASIC_PRESET = 0, PREFILTER_XSOBEL = 1 }; enum { DEFAULT_NDISP = 64, DEFAULT_WINSZ = 19 }; //! the default constructor StereoBM_GPU(); //! the full constructor taking the camera-specific preset, number of disparities and the SAD window size. ndisparities must be multiple of 8. StereoBM_GPU(int preset, int ndisparities = DEFAULT_NDISP, int winSize = DEFAULT_WINSZ); //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair //! Output disparity has CV_8U type. void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity); //! Acync version void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream & stream); //! Some heuristics that tries to estmate // if current GPU will be faster then CPU in this algorithm. // It queries current active device. static bool checkIfGpuCallReasonable(); int ndisp; int winSize; int preset; // If avergeTexThreshold == 0 => post procesing is disabled // If avergeTexThreshold != 0 then disparity is set 0 in each point (x,y) where for left image // SumOfHorizontalGradiensInWindow(x, y, winSize) < (winSize * winSize) * avergeTexThreshold // i.e. input left image is low textured. float avergeTexThreshold; private: GpuMat minSSD, leBuf, riBuf; }; ////////////////////////// StereoBeliefPropagation /////////////////////////// // "Efficient Belief Propagation for Early Vision" // P.Felzenszwalb class CV_EXPORTS StereoBeliefPropagation { public: enum { DEFAULT_NDISP = 64 }; enum { DEFAULT_ITERS = 5 }; enum { DEFAULT_LEVELS = 5 }; static void estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels); //! the default constructor explicit StereoBeliefPropagation(int ndisp = DEFAULT_NDISP, int iters = DEFAULT_ITERS, int levels = DEFAULT_LEVELS, int msg_type = CV_32F); //! the full constructor taking the number of disparities, number of BP iterations on each level, //! number of levels, truncation of data cost, data weight, //! truncation of discontinuity cost and discontinuity single jump //! DataTerm = data_weight * min(fabs(I2-I1), max_data_term) //! DiscTerm = min(disc_single_jump * fabs(f1-f2), max_disc_term) //! please see paper for more details StereoBeliefPropagation(int ndisp, int iters, int levels, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump, int msg_type = CV_32F); //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair, //! if disparity is empty output type will be CV_16S else output type will be disparity.type(). void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity); //! Acync version void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream); //! version for user specified data term void operator()(const GpuMat& data, GpuMat& disparity); void operator()(const GpuMat& data, GpuMat& disparity, Stream& stream); int ndisp; int iters; int levels; float max_data_term; float data_weight; float max_disc_term; float disc_single_jump; int msg_type; private: GpuMat u, d, l, r, u2, d2, l2, r2; std::vector datas; GpuMat out; }; /////////////////////////// StereoConstantSpaceBP /////////////////////////// // "A Constant-Space Belief Propagation Algorithm for Stereo Matching" // Qingxiong Yang, Liang Wang†, Narendra Ahuja // http://vision.ai.uiuc.edu/~qyang6/ class CV_EXPORTS StereoConstantSpaceBP { public: enum { DEFAULT_NDISP = 128 }; enum { DEFAULT_ITERS = 8 }; enum { DEFAULT_LEVELS = 4 }; enum { DEFAULT_NR_PLANE = 4 }; static void estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane); //! the default constructor explicit StereoConstantSpaceBP(int ndisp = DEFAULT_NDISP, int iters = DEFAULT_ITERS, int levels = DEFAULT_LEVELS, int nr_plane = DEFAULT_NR_PLANE, int msg_type = CV_32F); //! the full constructor taking the number of disparities, number of BP iterations on each level, //! number of levels, number of active disparity on the first level, truncation of data cost, data weight, //! truncation of discontinuity cost, discontinuity single jump and minimum disparity threshold StereoConstantSpaceBP(int ndisp, int iters, int levels, int nr_plane, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump, int min_disp_th = 0, int msg_type = CV_32F); //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair, //! if disparity is empty output type will be CV_16S else output type will be disparity.type(). void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity); //! Acync version void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream); int ndisp; int iters; int levels; int nr_plane; float max_data_term; float data_weight; float max_disc_term; float disc_single_jump; int min_disp_th; int msg_type; bool use_local_init_data_cost; private: GpuMat u[2], d[2], l[2], r[2]; GpuMat disp_selected_pyr[2]; GpuMat data_cost; GpuMat data_cost_selected; GpuMat temp; GpuMat out; }; /////////////////////////// DisparityBilateralFilter /////////////////////////// // Disparity map refinement using joint bilateral filtering given a single color image. // Qingxiong Yang, Liang Wang†, Narendra Ahuja // http://vision.ai.uiuc.edu/~qyang6/ class CV_EXPORTS DisparityBilateralFilter { public: enum { DEFAULT_NDISP = 64 }; enum { DEFAULT_RADIUS = 3 }; enum { DEFAULT_ITERS = 1 }; //! the default constructor explicit DisparityBilateralFilter(int ndisp = DEFAULT_NDISP, int radius = DEFAULT_RADIUS, int iters = DEFAULT_ITERS); //! the full constructor taking the number of disparities, filter radius, //! number of iterations, truncation of data continuity, truncation of disparity continuity //! and filter range sigma DisparityBilateralFilter(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold, float sigma_range); //! the disparity map refinement operator. Refine disparity map using joint bilateral filtering given a single color image. //! disparity must have CV_8U or CV_16S type, image must have CV_8UC1 or CV_8UC3 type. void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst); //! Acync version void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream); private: int ndisp; int radius; int iters; float edge_threshold; float max_disc_threshold; float sigma_range; GpuMat table_color; GpuMat table_space; }; } //! Speckle filtering - filters small connected components on diparity image. //! It sets pixel (x,y) to newVal if it coresponds to small CC with size < maxSpeckleSize. //! Threshold for border between CC is diffThreshold; CV_EXPORTS void filterSpeckles( Mat& img, uchar newVal, int maxSpeckleSize, uchar diffThreshold, Mat& buf); } #include "opencv2/gpu/matrix_operations.hpp" #endif /* __OPENCV_GPU_HPP__ */