/*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_GPUMAT_HPP__ #define __OPENCV_GPUMAT_HPP__ #ifdef __cplusplus #include "opencv2/core/core.hpp" #include "opencv2/core/cuda_devptrs.hpp" namespace cv { namespace gpu { //////////////////////////////// Initialization & Info //////////////////////// //! 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 void setDevice(int device); CV_EXPORTS int getDevice(); //! Explicitly destroys and cleans up all resources associated with the current device in the current process. //! Any subsequent API call to this device will reinitialize the device. CV_EXPORTS void resetDevice(); enum FeatureSet { FEATURE_SET_COMPUTE_10 = 10, FEATURE_SET_COMPUTE_11 = 11, FEATURE_SET_COMPUTE_12 = 12, FEATURE_SET_COMPUTE_13 = 13, FEATURE_SET_COMPUTE_20 = 20, FEATURE_SET_COMPUTE_21 = 21, FEATURE_SET_COMPUTE_30 = 30, FEATURE_SET_COMPUTE_35 = 35, GLOBAL_ATOMICS = FEATURE_SET_COMPUTE_11, SHARED_ATOMICS = FEATURE_SET_COMPUTE_12, NATIVE_DOUBLE = FEATURE_SET_COMPUTE_13, WARP_SHUFFLE_FUNCTIONS = FEATURE_SET_COMPUTE_30, DYNAMIC_PARALLELISM = FEATURE_SET_COMPUTE_35 }; // Checks whether current device supports the given feature CV_EXPORTS bool deviceSupports(FeatureSet feature_set); // Gives information about what GPU archs this OpenCV GPU module was // compiled for class CV_EXPORTS TargetArchs { public: static bool builtWith(FeatureSet feature_set); static bool has(int major, int minor); static bool hasPtx(int major, int minor); static bool hasBin(int major, int minor); static bool hasEqualOrLessPtx(int major, int minor); static bool hasEqualOrGreater(int major, int minor); static bool hasEqualOrGreaterPtx(int major, int minor); static bool hasEqualOrGreaterBin(int major, int minor); private: TargetArchs(); }; // Gives information about the given GPU class CV_EXPORTS DeviceInfo { public: // Creates DeviceInfo object for the current GPU DeviceInfo() : device_id_(getDevice()) { query(); } // Creates DeviceInfo object for the given GPU DeviceInfo(int device_id) : device_id_(device_id) { query(); } std::string name() const { return name_; } // Return compute capability versions int majorVersion() const { return majorVersion_; } int minorVersion() const { return minorVersion_; } int multiProcessorCount() const { return multi_processor_count_; } size_t sharedMemPerBlock() const; void queryMemory(size_t& totalMemory, size_t& freeMemory) const; size_t freeMemory() const; size_t totalMemory() const; // Checks whether device supports the given feature bool supports(FeatureSet feature_set) const; // Checks whether the GPU module can be run on the given device bool isCompatible() const; int deviceID() const { return device_id_; } private: void query(); int device_id_; std::string name_; int multi_processor_count_; int majorVersion_; int minorVersion_; }; CV_EXPORTS void printCudaDeviceInfo(int device); CV_EXPORTS void printShortCudaDeviceInfo(int device); //////////////////////////////// GpuMat /////////////////////////////// //! 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, Scalar s); GpuMat(Size size, int type, 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, Range rowRange, Range colRange); GpuMat(const GpuMat& m, 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); //! pefroms blocking upload data to GpuMat. void upload(const Mat& m); //! downloads data from device to host memory. Blocking calls. void download(Mat& m) 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(Range r) const; //! ... for the specified column span GpuMat colRange(int startcol, int endcol) const; GpuMat colRange(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 = (Scalar s); //! sets some of the GpuMatrix elements to s, according to the mask GpuMat& setTo(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()(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; template operator PtrStepSz<_Tp>() const; template operator PtrStep<_Tp>() const; // Deprecated function __CV_GPU_DEPR_BEFORE__ template operator DevMem2D_<_Tp>() const __CV_GPU_DEPR_AFTER__; __CV_GPU_DEPR_BEFORE__ template operator PtrStep_<_Tp>() const __CV_GPU_DEPR_AFTER__; #undef __CV_GPU_DEPR_BEFORE__ #undef __CV_GPU_DEPR_AFTER__ /*! 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; }; //! Creates continuous GPU matrix CV_EXPORTS void createContinuous(int rows, int cols, int type, GpuMat& m); CV_EXPORTS GpuMat createContinuous(int rows, int cols, int type); CV_EXPORTS void createContinuous(Size size, int type, GpuMat& m); CV_EXPORTS GpuMat createContinuous(Size size, int type); //! Ensures that size of the given matrix is not less than (rows, cols) size //! and matrix type is match specified one too CV_EXPORTS void ensureSizeIsEnough(int rows, int cols, int type, GpuMat& m); CV_EXPORTS void ensureSizeIsEnough(Size size, int type, GpuMat& m); CV_EXPORTS GpuMat allocMatFromBuf(int rows, int cols, int type, GpuMat &mat); //////////////////////////////////////////////////////////////////////// // Error handling CV_EXPORTS void error(const char* error_string, const char* file, const int line, const char* func = ""); //////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////// inline GpuMat::GpuMat() : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) { } inline GpuMat::GpuMat(int rows_, int cols_, int type_) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) { if (rows_ > 0 && cols_ > 0) create(rows_, cols_, type_); } inline GpuMat::GpuMat(Size size_, int type_) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) { if (size_.height > 0 && size_.width > 0) create(size_.height, size_.width, type_); } inline GpuMat::GpuMat(int rows_, int cols_, int type_, Scalar s_) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) { if (rows_ > 0 && cols_ > 0) { create(rows_, cols_, type_); setTo(s_); } } inline GpuMat::GpuMat(Size size_, int type_, Scalar s_) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) { if (size_.height > 0 && size_.width > 0) { create(size_.height, size_.width, type_); setTo(s_); } } inline GpuMat::~GpuMat() { release(); } inline GpuMat GpuMat::clone() const { GpuMat m; copyTo(m); return m; } inline void GpuMat::assignTo(GpuMat& m, int _type) const { if (_type < 0) m = *this; else convertTo(m, _type); } inline size_t GpuMat::step1() const { return step / elemSize1(); } inline bool GpuMat::empty() const { return data == 0; } template inline _Tp* GpuMat::ptr(int y) { return (_Tp*)ptr(y); } template inline const _Tp* GpuMat::ptr(int y) const { return (const _Tp*)ptr(y); } inline void swap(GpuMat& a, GpuMat& b) { a.swap(b); } inline GpuMat GpuMat::row(int y) const { return GpuMat(*this, Range(y, y+1), Range::all()); } inline GpuMat GpuMat::col(int x) const { return GpuMat(*this, Range::all(), Range(x, x+1)); } inline GpuMat GpuMat::rowRange(int startrow, int endrow) const { return GpuMat(*this, Range(startrow, endrow), Range::all()); } inline GpuMat GpuMat::rowRange(Range r) const { return GpuMat(*this, r, Range::all()); } inline GpuMat GpuMat::colRange(int startcol, int endcol) const { return GpuMat(*this, Range::all(), Range(startcol, endcol)); } inline GpuMat GpuMat::colRange(Range r) const { return GpuMat(*this, Range::all(), r); } inline void GpuMat::create(Size size_, int type_) { create(size_.height, size_.width, type_); } inline GpuMat GpuMat::operator()(Range _rowRange, Range _colRange) const { return GpuMat(*this, _rowRange, _colRange); } inline GpuMat GpuMat::operator()(Rect roi) const { return GpuMat(*this, roi); } inline bool GpuMat::isContinuous() const { return (flags & Mat::CONTINUOUS_FLAG) != 0; } inline size_t GpuMat::elemSize() const { return CV_ELEM_SIZE(flags); } inline size_t GpuMat::elemSize1() const { return CV_ELEM_SIZE1(flags); } inline int GpuMat::type() const { return CV_MAT_TYPE(flags); } inline int GpuMat::depth() const { return CV_MAT_DEPTH(flags); } inline int GpuMat::channels() const { return CV_MAT_CN(flags); } inline Size GpuMat::size() const { return Size(cols, rows); } inline uchar* GpuMat::ptr(int y) { CV_DbgAssert((unsigned)y < (unsigned)rows); return data + step * y; } inline const uchar* GpuMat::ptr(int y) const { CV_DbgAssert((unsigned)y < (unsigned)rows); return data + step * y; } inline GpuMat& GpuMat::operator = (Scalar s) { setTo(s); return *this; } /** @cond IGNORED */ template inline GpuMat::operator PtrStepSz() const { return PtrStepSz(rows, cols, (T*)data, step); } template inline GpuMat::operator PtrStep() const { return PtrStep((T*)data, step); } template inline GpuMat::operator DevMem2D_() const { return DevMem2D_(rows, cols, (T*)data, step); } template inline GpuMat::operator PtrStep_() const { return PtrStep_(static_cast< DevMem2D_ >(*this)); } /** @endcond */ inline GpuMat createContinuous(int rows, int cols, int type) { GpuMat m; createContinuous(rows, cols, type, m); return m; } inline void createContinuous(Size size, int type, GpuMat& m) { createContinuous(size.height, size.width, type, m); } inline GpuMat createContinuous(Size size, int type) { GpuMat m; createContinuous(size, type, m); return m; } inline void ensureSizeIsEnough(Size size, int type, GpuMat& m) { ensureSizeIsEnough(size.height, size.width, type, m); } }} #endif // __cplusplus #endif // __OPENCV_GPUMAT_HPP__