--- /dev/null
- //optional function, if you want save opencl binary kernel to the file, set its path
- CV_EXPORTS void setBinpath(const char *path);
-
+/*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) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
+// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
+// Copyright (C) 2010-2012, Multicoreware, 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 oclMaterials 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_OCL_HPP__
+#define __OPENCV_OCL_HPP__
+
+#include <memory>
+#include <vector>
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgproc.hpp"
+#include "opencv2/objdetect.hpp"
+
+namespace cv
+{
+ namespace ocl
+ {
+ enum
+ {
+ CVCL_DEVICE_TYPE_DEFAULT = (1 << 0),
+ CVCL_DEVICE_TYPE_CPU = (1 << 1),
+ CVCL_DEVICE_TYPE_GPU = (1 << 2),
+ CVCL_DEVICE_TYPE_ACCELERATOR = (1 << 3),
+ //CVCL_DEVICE_TYPE_CUSTOM = (1 << 4)
+ CVCL_DEVICE_TYPE_ALL = 0xFFFFFFFF
+ };
+
+ enum DevMemRW
+ {
+ DEVICE_MEM_R_W = 0,
+ DEVICE_MEM_R_ONLY,
+ DEVICE_MEM_W_ONLY
+ };
+
+ enum DevMemType
+ {
+ DEVICE_MEM_DEFAULT = 0,
+ DEVICE_MEM_AHP, //alloc host pointer
+ DEVICE_MEM_UHP, //use host pointer
+ DEVICE_MEM_CHP, //copy host pointer
+ DEVICE_MEM_PM //persistent memory
+ };
+
+ //Get the global device memory and read/write type
+ //return 1 if unified memory system supported, otherwise return 0
+ CV_EXPORTS int getDevMemType(DevMemRW& rw_type, DevMemType& mem_type);
+
+ //Set the global device memory and read/write type,
+ //the newly generated oclMat will all use this type
+ //return -1 if the target type is unsupported, otherwise return 0
+ CV_EXPORTS int setDevMemType(DevMemRW rw_type = DEVICE_MEM_R_W, DevMemType mem_type = DEVICE_MEM_DEFAULT);
+
+ //this class contains ocl runtime information
+ class CV_EXPORTS Info
+ {
+ public:
+ struct Impl;
+ Impl *impl;
+
+ Info();
+ Info(const Info &m);
+ ~Info();
+ void release();
+ Info &operator = (const Info &m);
+ std::vector<String> DeviceName;
+ String PlatformName;
+ };
+ //////////////////////////////// Initialization & Info ////////////////////////
+ //this function may be obsoleted
+ //CV_EXPORTS cl_device_id getDevice();
+ //the function must be called before any other cv::ocl::functions, it initialize ocl runtime
+ //each Info relates to an OpenCL platform
+ //there is one or more devices in each platform, each one has a separate name
+ CV_EXPORTS int getDevice(std::vector<Info> &oclinfo, int devicetype = CVCL_DEVICE_TYPE_GPU);
+
+ //set device you want to use, optional function after getDevice be called
+ //the devnum is the index of the selected device in DeviceName vector of INfo
+ CV_EXPORTS void setDevice(Info &oclinfo, int devnum = 0);
+
-
+ //The two functions below enable other opencl program to use ocl module's cl_context and cl_command_queue
+ //returns cl_context *
+ CV_EXPORTS void* getoclContext();
+ //returns cl_command_queue *
+ CV_EXPORTS void* getoclCommandQueue();
+
+ //explicit call clFinish. The global command queue will be used.
+ CV_EXPORTS void finish();
+
+ //this function enable ocl module to use customized cl_context and cl_command_queue
+ //getDevice also need to be called before this function
+ CV_EXPORTS void setDeviceEx(Info &oclinfo, void *ctx, void *qu, int devnum = 0);
+
++ //returns true when global OpenCL context is initialized
++ CV_EXPORTS bool initialized();
++
+ //////////////////////////////// OpenCL context ////////////////////////
+ //This is a global singleton class used to represent a OpenCL context.
+ class CV_EXPORTS Context
+ {
+ protected:
+ Context();
+ friend class std::auto_ptr<Context>;
++ friend bool initialized();
+ private:
+ static std::auto_ptr<Context> clCxt;
+ static int val;
+ public:
+ ~Context();
+ void release();
+ Info::Impl* impl;
+
+ static Context *getContext();
+ static void setContext(Info &oclinfo);
+
+ enum {CL_DOUBLE, CL_UNIFIED_MEM, CL_VER_1_2};
+ bool supportsFeature(int ftype);
+ size_t computeUnits();
+ size_t maxWorkGroupSize();
+ void* oclContext();
+ void* oclCommandQueue();
+ };
+
+ //! Calls a kernel, by string. Pass globalThreads = NULL, and cleanUp = true, to finally clean-up without executing.
+ CV_EXPORTS double openCLExecuteKernelInterop(Context *clCxt ,
+ const char **source, String kernelName,
+ size_t globalThreads[3], size_t localThreads[3],
+ std::vector< std::pair<size_t, const void *> > &args,
+ int channels, int depth, const char *build_options,
+ bool finish = true, bool measureKernelTime = false,
+ bool cleanUp = true);
+
+ //! Calls a kernel, by file. Pass globalThreads = NULL, and cleanUp = true, to finally clean-up without executing.
+ CV_EXPORTS double openCLExecuteKernelInterop(Context *clCxt ,
+ const char **fileName, const int numFiles, String kernelName,
+ size_t globalThreads[3], size_t localThreads[3],
+ std::vector< std::pair<size_t, const void *> > &args,
+ int channels, int depth, const char *build_options,
+ bool finish = true, bool measureKernelTime = false,
+ bool cleanUp = true);
+
++ //! Enable or disable OpenCL program binary caching onto local disk
++ // After a program (*.cl files in opencl/ folder) is built at runtime, we allow the
++ // compiled OpenCL program to be cached to the path automatically as "path/*.clb"
++ // binary file, which will be reused when the OpenCV executable is started again.
++ //
++ // Caching mode is controlled by the following enums
++ // Notes
++ // 1. the feature is by default enabled when OpenCV is built in release mode.
++ // 2. the CACHE_DEBUG / CACHE_RELEASE flags only effectively work with MSVC compiler;
++ // for GNU compilers, the function always treats the build as release mode (enabled by default).
++ enum
++ {
++ CACHE_NONE = 0, // do not cache OpenCL binary
++ CACHE_DEBUG = 0x1 << 0, // cache OpenCL binary when built in debug mode (only work with MSVC)
++ CACHE_RELEASE = 0x1 << 1, // default behavior, only cache when built in release mode (only work with MSVC)
++ CACHE_ALL = CACHE_DEBUG | CACHE_RELEASE, // always cache opencl binary
++ CACHE_UPDATE = 0x1 << 2 // if the binary cache file with the same name is already on the disk, it will be updated.
++ };
++ CV_EXPORTS void setBinaryDiskCache(int mode = CACHE_RELEASE, cv::String path = "./");
++
++ //! set where binary cache to be saved to
++ CV_EXPORTS void setBinpath(const char *path);
++
+ class CV_EXPORTS oclMatExpr;
+ //////////////////////////////// oclMat ////////////////////////////////
+ class CV_EXPORTS oclMat
+ {
+ public:
+ //! default constructor
+ oclMat();
+ //! constructs oclMatrix of the specified size and type (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.)
+ oclMat(int rows, int cols, int type);
+ oclMat(Size size, int type);
+ //! constucts oclMatrix and fills it with the specified value _s.
+ oclMat(int rows, int cols, int type, const Scalar &s);
+ oclMat(Size size, int type, const Scalar &s);
+ //! copy constructor
+ oclMat(const oclMat &m);
+
+ //! constructor for oclMatrix headers pointing to user-allocated data
+ oclMat(int rows, int cols, int type, void *data, size_t step = Mat::AUTO_STEP);
+ oclMat(Size size, int type, void *data, size_t step = Mat::AUTO_STEP);
+
+ //! creates a matrix header for a part of the bigger matrix
+ oclMat(const oclMat &m, const Range &rowRange, const Range &colRange);
+ oclMat(const oclMat &m, const Rect &roi);
+
+ //! builds oclMat from Mat. Perfom blocking upload to device.
+ explicit oclMat (const Mat &m);
+
+ //! destructor - calls release()
+ ~oclMat();
+
+ //! assignment operators
+ oclMat &operator = (const oclMat &m);
+ //! assignment operator. Perfom blocking upload to device.
+ oclMat &operator = (const Mat &m);
+ oclMat &operator = (const oclMatExpr& expr);
+
+ //! pefroms blocking upload data to oclMat.
+ void upload(const cv::Mat &m);
+
+
+ //! downloads data from device to host memory. Blocking calls.
+ operator Mat() const;
+ void download(cv::Mat &m) const;
+
+
+ //! returns a new oclMatrix header for the specified row
+ oclMat row(int y) const;
+ //! returns a new oclMatrix header for the specified column
+ oclMat col(int x) const;
+ //! ... for the specified row span
+ oclMat rowRange(int startrow, int endrow) const;
+ oclMat rowRange(const Range &r) const;
+ //! ... for the specified column span
+ oclMat colRange(int startcol, int endcol) const;
+ oclMat colRange(const Range &r) const;
+
+ //! returns deep copy of the oclMatrix, i.e. the data is copied
+ oclMat clone() const;
+ //! copies the oclMatrix content to "m".
+ // It calls m.create(this->size(), this->type()).
+ // It supports any data type
+ void copyTo( oclMat &m ) const;
+ //! copies those oclMatrix elements to "m" that are marked with non-zero mask elements.
+ //It supports 8UC1 8UC4 32SC1 32SC4 32FC1 32FC4
+ void copyTo( oclMat &m, const oclMat &mask ) const;
+ //! converts oclMatrix to another datatype with optional scalng. See cvConvertScale.
+ //It supports 8UC1 8UC4 32SC1 32SC4 32FC1 32FC4
+ void convertTo( oclMat &m, int rtype, double alpha = 1, double beta = 0 ) const;
+
+ void assignTo( oclMat &m, int type = -1 ) const;
+
+ //! sets every oclMatrix element to s
+ //It supports 8UC1 8UC4 32SC1 32SC4 32FC1 32FC4
+ oclMat& operator = (const Scalar &s);
+ //! sets some of the oclMatrix elements to s, according to the mask
+ //It supports 8UC1 8UC4 32SC1 32SC4 32FC1 32FC4
+ oclMat& setTo(const Scalar &s, const oclMat &mask = oclMat());
+ //! creates alternative oclMatrix header for the same data, with different
+ // number of channels and/or different number of rows. see cvReshape.
+ oclMat reshape(int cn, int rows = 0) const;
+
+ //! allocates new oclMatrix data unless the oclMatrix 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);
+
+ //! allocates new oclMatrix with specified device memory type.
+ void createEx(int rows, int cols, int type,
+ DevMemRW rw_type, DevMemType mem_type, void* hptr = 0);
+ void createEx(Size size, int type, DevMemRW rw_type,
+ DevMemType mem_type, void* hptr = 0);
+
+ //! decreases reference counter;
+ // deallocate the data when reference counter reaches 0.
+ void release();
+
+ //! swaps with other smart pointer
+ void swap(oclMat &mat);
+
+ //! locates oclMatrix header within a parent oclMatrix. See below
+ void locateROI( Size &wholeSize, Point &ofs ) const;
+ //! moves/resizes the current oclMatrix ROI inside the parent oclMatrix.
+ oclMat& adjustROI( int dtop, int dbottom, int dleft, int dright );
+ //! extracts a rectangular sub-oclMatrix
+ // (this is a generalized form of row, rowRange etc.)
+ oclMat operator()( Range rowRange, Range colRange ) const;
+ oclMat operator()( const Rect &roi ) const;
+
+ oclMat& operator+=( const oclMat& m );
+ oclMat& operator-=( const oclMat& m );
+ oclMat& operator*=( const oclMat& m );
+ oclMat& operator/=( const oclMat& m );
+
+ //! returns true if the oclMatrix data is continuous
+ // (i.e. when there are no gaps between successive rows).
+ // similar to CV_IS_oclMat_CONT(cvoclMat->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, i.e. 8UC3 returns 8UC4 because in ocl
+ //! 3 channels element actually use 4 channel space
+ int ocltype() 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 element type, return 4 for 3 channels element,
+ //!becuase 3 channels element actually use 4 channel space
+ int oclchannels() const;
+ //! returns step/elemSize1()
+ size_t step1() const;
+ //! returns oclMatrix size:
+ // width == number of columns, height == number of rows
+ Size size() const;
+ //! returns true if oclMatrix 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<typename _Tp> _Tp *ptr(int y = 0);
+ template<typename _Tp> const _Tp *ptr(int y = 0) const;
+
+ //! matrix transposition
+ oclMat 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(OCL memory object)
+ uchar *data;
+
+ //! pointer to the reference counter;
+ // when oclMatrix points to user-allocated data, the pointer is NULL
+ int *refcount;
+
+ //! helper fields used in locateROI and adjustROI
+ //datastart and dataend are not used in current version
+ uchar *datastart;
+ uchar *dataend;
+
+ //! OpenCL context associated with the oclMat object.
+ Context *clCxt;
+ //add offset for handle ROI, calculated in byte
+ int offset;
+ //add wholerows and wholecols for the whole matrix, datastart and dataend are no longer used
+ int wholerows;
+ int wholecols;
+ };
+
+
+ ///////////////////// mat split and merge /////////////////////////////////
+ //! Compose a multi-channel array from several single-channel arrays
+ // Support all types
+ CV_EXPORTS void merge(const oclMat *src, size_t n, oclMat &dst);
+ CV_EXPORTS void merge(const std::vector<oclMat> &src, oclMat &dst);
+
+ //! Divides multi-channel array into several single-channel arrays
+ // Support all types
+ CV_EXPORTS void split(const oclMat &src, oclMat *dst);
+ CV_EXPORTS void split(const oclMat &src, std::vector<oclMat> &dst);
+
+ ////////////////////////////// Arithmetics ///////////////////////////////////
+ //#if defined DOUBLE_SUPPORT
+ //typedef double F;
+ //#else
+ //typedef float F;
+ //#endif
+ // CV_EXPORTS void addWeighted(const oclMat& a,F alpha, const oclMat& b,F beta,F gama, oclMat& c);
+ CV_EXPORTS void addWeighted(const oclMat &a, double alpha, const oclMat &b, double beta, double gama, oclMat &c);
+ //! adds one matrix to another (c = a + b)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void add(const oclMat &a, const oclMat &b, oclMat &c);
+ //! adds one matrix to another (c = a + b)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void add(const oclMat &a, const oclMat &b, oclMat &c, const oclMat &mask);
+ //! adds scalar to a matrix (c = a + s)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void add(const oclMat &a, const Scalar &sc, oclMat &c, const oclMat &mask = oclMat());
+ //! subtracts one matrix from another (c = a - b)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void subtract(const oclMat &a, const oclMat &b, oclMat &c);
+ //! subtracts one matrix from another (c = a - b)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void subtract(const oclMat &a, const oclMat &b, oclMat &c, const oclMat &mask);
+ //! subtracts scalar from a matrix (c = a - s)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void subtract(const oclMat &a, const Scalar &sc, oclMat &c, const oclMat &mask = oclMat());
+ //! subtracts scalar from a matrix (c = a - s)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void subtract(const Scalar &sc, const oclMat &a, oclMat &c, const oclMat &mask = oclMat());
+ //! computes element-wise product of the two arrays (c = a * b)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void multiply(const oclMat &a, const oclMat &b, oclMat &c, double scale = 1);
+ //! multiplies matrix to a number (dst = scalar * src)
+ // supports CV_32FC1 only
+ CV_EXPORTS void multiply(double scalar, const oclMat &src, oclMat &dst);
+ //! computes element-wise quotient of the two arrays (c = a / b)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void divide(const oclMat &a, const oclMat &b, oclMat &c, double scale = 1);
+ //! computes element-wise quotient of the two arrays (c = a / b)
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void divide(double scale, const oclMat &b, oclMat &c);
+
+ //! compares elements of two arrays (c = a <cmpop> b)
+ // supports except CV_8SC1,CV_8SC2,CV8SC3,CV_8SC4 types
+ CV_EXPORTS void compare(const oclMat &a, const oclMat &b, oclMat &c, int cmpop);
+
+ //! transposes the matrix
+ // supports CV_8UC1, 8UC4, 8SC4, 16UC2, 16SC2, 32SC1 and 32FC1.(the same as cuda)
+ CV_EXPORTS void transpose(const oclMat &src, oclMat &dst);
+
+ //! computes element-wise absolute difference of two arrays (c = abs(a - b))
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void absdiff(const oclMat &a, const oclMat &b, oclMat &c);
+ //! computes element-wise absolute difference of array and scalar (c = abs(a - s))
+ // supports all types except CV_8SC1,CV_8SC2,CV8SC3 and CV_8SC4
+ CV_EXPORTS void absdiff(const oclMat &a, const Scalar &s, oclMat &c);
+
+ //! computes mean value and standard deviation of all or selected array elements
+ // supports except CV_32F,CV_64F
+ CV_EXPORTS void meanStdDev(const oclMat &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 oclMat &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 oclMat &src1, const oclMat &src2, int normType = NORM_L2);
+
+ //! reverses the order of the rows, columns or both in a matrix
+ // supports all types
+ CV_EXPORTS void flip(const oclMat &a, oclMat &b, int flipCode);
+
+ //! computes sum of array elements
+ // disabled until fix crash
+ // support all types
+ CV_EXPORTS Scalar sum(const oclMat &m);
+ CV_EXPORTS Scalar absSum(const oclMat &m);
+ CV_EXPORTS Scalar sqrSum(const oclMat &m);
+
+ //! finds global minimum and maximum array elements and returns their values
+ // support all C1 types
+
+ CV_EXPORTS void minMax(const oclMat &src, double *minVal, double *maxVal = 0, const oclMat &mask = oclMat());
+ CV_EXPORTS void minMax_buf(const oclMat &src, double *minVal, double *maxVal, const oclMat &mask, oclMat& buf);
+
+ //! finds global minimum and maximum array elements and returns their values with locations
+ // support all C1 types
+
+ CV_EXPORTS void minMaxLoc(const oclMat &src, double *minVal, double *maxVal = 0, Point *minLoc = 0, Point *maxLoc = 0,
+ const oclMat &mask = oclMat());
+
+ //! counts non-zero array elements
+ // support all types
+ CV_EXPORTS int countNonZero(const oclMat &src);
+
+ //! 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
+ //It supports 8UC1 8UC4 only
+ CV_EXPORTS void LUT(const oclMat &src, const oclMat &lut, oclMat &dst);
+
+ //! only 8UC1 and 256 bins is supported now
+ CV_EXPORTS void calcHist(const oclMat &mat_src, oclMat &mat_hist);
+ //! only 8UC1 and 256 bins is supported now
+ CV_EXPORTS void equalizeHist(const oclMat &mat_src, oclMat &mat_dst);
++
++ //! only 8UC1 is supported now
++ class CV_EXPORTS CLAHE
++ {
++ public:
++ virtual void apply(const oclMat &src, oclMat &dst) = 0;
++
++ virtual void setClipLimit(double clipLimit) = 0;
++ virtual double getClipLimit() const = 0;
++
++ virtual void setTilesGridSize(Size tileGridSize) = 0;
++ virtual Size getTilesGridSize() const = 0;
++
++ virtual void collectGarbage() = 0;
++
++ virtual ~CLAHE() {}
++ };
++ CV_EXPORTS Ptr<cv::ocl::CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));
++
+ //! bilateralFilter
+ // supports 8UC1 8UC4
+ CV_EXPORTS void bilateralFilter(const oclMat& src, oclMat& dst, int d, double sigmaColor, double sigmaSpave, int borderType=BORDER_DEFAULT);
+ //! computes exponent of each matrix element (b = e**a)
+ // supports only CV_32FC1 type
+ CV_EXPORTS void exp(const oclMat &a, oclMat &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 oclMat &a, oclMat &b);
+
+ //! computes magnitude of each (x(i), y(i)) vector
+ // supports only CV_32F CV_64F type
+ CV_EXPORTS void magnitude(const oclMat &x, const oclMat &y, oclMat &magnitude);
+ CV_EXPORTS void magnitudeSqr(const oclMat &x, const oclMat &y, oclMat &magnitude);
+
+ CV_EXPORTS void magnitudeSqr(const oclMat &x, oclMat &magnitude);
+
+ //! computes angle (angle(i)) of each (x(i), y(i)) vector
+ // supports only CV_32F CV_64F type
+ CV_EXPORTS void phase(const oclMat &x, const oclMat &y, oclMat &angle, bool angleInDegrees = false);
+
+ //! the function raises every element of tne input array to p
+ //! support only CV_32F CV_64F type
+ CV_EXPORTS void pow(const oclMat &x, double p, oclMat &y);
+
+ //! converts Cartesian coordinates to polar
+ // supports only CV_32F CV_64F type
+ CV_EXPORTS void cartToPolar(const oclMat &x, const oclMat &y, oclMat &magnitude, oclMat &angle, bool angleInDegrees = false);
+
+ //! converts polar coordinates to Cartesian
+ // supports only CV_32F CV_64F type
+ CV_EXPORTS void polarToCart(const oclMat &magnitude, const oclMat &angle, oclMat &x, oclMat &y, bool angleInDegrees = false);
+
+ //! perfroms per-elements bit-wise inversion
+ // supports all types
+ CV_EXPORTS void bitwise_not(const oclMat &src, oclMat &dst);
+ //! calculates per-element bit-wise disjunction of two arrays
+ // supports all types
+ CV_EXPORTS void bitwise_or(const oclMat &src1, const oclMat &src2, oclMat &dst, const oclMat &mask = oclMat());
+ CV_EXPORTS void bitwise_or(const oclMat &src1, const Scalar &s, oclMat &dst, const oclMat &mask = oclMat());
+ //! calculates per-element bit-wise conjunction of two arrays
+ // supports all types
+ CV_EXPORTS void bitwise_and(const oclMat &src1, const oclMat &src2, oclMat &dst, const oclMat &mask = oclMat());
+ CV_EXPORTS void bitwise_and(const oclMat &src1, const Scalar &s, oclMat &dst, const oclMat &mask = oclMat());
+ //! calculates per-element bit-wise "exclusive or" operation
+ // supports all types
+ CV_EXPORTS void bitwise_xor(const oclMat &src1, const oclMat &src2, oclMat &dst, const oclMat &mask = oclMat());
+ CV_EXPORTS void bitwise_xor(const oclMat &src1, const Scalar &s, oclMat &dst, const oclMat &mask = oclMat());
+
+ //! Logical operators
+ CV_EXPORTS oclMat operator ~ (const oclMat &);
+ CV_EXPORTS oclMat operator | (const oclMat &, const oclMat &);
+ CV_EXPORTS oclMat operator & (const oclMat &, const oclMat &);
+ CV_EXPORTS oclMat operator ^ (const oclMat &, const oclMat &);
+
+
+ //! Mathematics operators
+ CV_EXPORTS oclMatExpr operator + (const oclMat &src1, const oclMat &src2);
+ CV_EXPORTS oclMatExpr operator - (const oclMat &src1, const oclMat &src2);
+ CV_EXPORTS oclMatExpr operator * (const oclMat &src1, const oclMat &src2);
+ CV_EXPORTS oclMatExpr operator / (const oclMat &src1, const oclMat &src2);
+
+ struct CV_EXPORTS ConvolveBuf
+ {
+ Size result_size;
+ Size block_size;
+ Size user_block_size;
+ Size dft_size;
+
+ oclMat image_spect, templ_spect, result_spect;
+ oclMat 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 of two images, may use discrete Fourier transform
+ //! support only CV_32FC1 type
+ CV_EXPORTS void convolve(const oclMat &image, const oclMat &temp1, oclMat &result, bool ccorr = false);
+ CV_EXPORTS void convolve(const oclMat &image, const oclMat &temp1, oclMat &result, bool ccorr, ConvolveBuf& buf);
+
+ //! Performs a per-element multiplication of two Fourier spectrums.
+ //! Only full (not packed) CV_32FC2 complex spectrums in the interleaved format are supported for now.
+ //! support only CV_32FC2 type
+ CV_EXPORTS void mulSpectrums(const oclMat &a, const oclMat &b, oclMat &c, int flags, float scale, bool conjB = false);
+
+ CV_EXPORTS void cvtColor(const oclMat &src, oclMat &dst, int code , int dcn = 0);
+
+ //////////////////////////////// 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_, int bordertype_) : ksize(ksize_), anchor(anchor_), bordertype(bordertype_) {}
+ virtual ~BaseRowFilter_GPU() {}
+ virtual void operator()(const oclMat &src, oclMat &dst) = 0;
+ int ksize, anchor, bordertype;
+ };
+
+ /*!
+ 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_, int bordertype_) : ksize(ksize_), anchor(anchor_), bordertype(bordertype_) {}
+ virtual ~BaseColumnFilter_GPU() {}
+ virtual void operator()(const oclMat &src, oclMat &dst) = 0;
+ int ksize, anchor, bordertype;
+ };
+
+ /*!
+ 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_, const int &borderType_)
+ : ksize(ksize_), anchor(anchor_), borderType(borderType_) {}
+ virtual ~BaseFilter_GPU() {}
+ virtual void operator()(const oclMat &src, oclMat &dst) = 0;
+ Size ksize;
+ Point anchor;
+ int borderType;
+ };
+
+ /*!
+ 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 oclMat &src, oclMat &dst, Rect roi = Rect(0, 0, -1, -1)) = 0;
+ };
+
+ //! returns the non-separable filter engine with the specified filter
+ CV_EXPORTS Ptr<FilterEngine_GPU> createFilter2D_GPU(const Ptr<BaseFilter_GPU> filter2D);
+
+ //! returns the primitive row filter with the specified kernel
+ CV_EXPORTS Ptr<BaseRowFilter_GPU> getLinearRowFilter_GPU(int srcType, int bufType, const Mat &rowKernel,
+ int anchor = -1, int bordertype = BORDER_DEFAULT);
+
+ //! returns the primitive column filter with the specified kernel
+ CV_EXPORTS Ptr<BaseColumnFilter_GPU> getLinearColumnFilter_GPU(int bufType, int dstType, const Mat &columnKernel,
+ int anchor = -1, int bordertype = BORDER_DEFAULT, double delta = 0.0);
+
+ //! returns the separable linear filter engine
+ CV_EXPORTS Ptr<FilterEngine_GPU> createSeparableLinearFilter_GPU(int srcType, int dstType, const Mat &rowKernel,
+ const Mat &columnKernel, const Point &anchor = Point(-1, -1), double delta = 0.0, int bordertype = BORDER_DEFAULT);
+
+ //! returns the separable filter engine with the specified filters
+ CV_EXPORTS Ptr<FilterEngine_GPU> createSeparableFilter_GPU(const Ptr<BaseRowFilter_GPU> &rowFilter,
+ const Ptr<BaseColumnFilter_GPU> &columnFilter);
+
+ //! returns the Gaussian filter engine
+ CV_EXPORTS Ptr<FilterEngine_GPU> createGaussianFilter_GPU(int type, Size ksize, double sigma1, double sigma2 = 0, int bordertype = BORDER_DEFAULT);
+
+ //! returns filter engine for the generalized Sobel operator
+ CV_EXPORTS Ptr<FilterEngine_GPU> createDerivFilter_GPU( int srcType, int dstType, int dx, int dy, int ksize, int borderType = BORDER_DEFAULT );
+
+ //! applies Laplacian operator to the image
+ // supports only ksize = 1 and ksize = 3 8UC1 8UC4 32FC1 32FC4 data type
+ CV_EXPORTS void Laplacian(const oclMat &src, oclMat &dst, int ddepth, int ksize = 1, double scale = 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<BaseFilter_GPU> getBoxFilter_GPU(int srcType, int dstType,
+ const Size &ksize, Point anchor = Point(-1, -1), int borderType = BORDER_DEFAULT);
+
+ //! returns box filter engine
+ CV_EXPORTS Ptr<FilterEngine_GPU> createBoxFilter_GPU(int srcType, int dstType, const Size &ksize,
+ const Point &anchor = Point(-1, -1), int borderType = BORDER_DEFAULT);
+
+ //! returns 2D filter with the specified kernel
+ // supports CV_8UC1 and CV_8UC4 types
+ CV_EXPORTS Ptr<BaseFilter_GPU> getLinearFilter_GPU(int srcType, int dstType, const Mat &kernel, const Size &ksize,
+ Point anchor = Point(-1, -1), int borderType = BORDER_DEFAULT);
+
+ //! returns the non-separable linear filter engine
+ CV_EXPORTS Ptr<FilterEngine_GPU> createLinearFilter_GPU(int srcType, int dstType, const Mat &kernel,
+ const Point &anchor = Point(-1, -1), int borderType = BORDER_DEFAULT);
+
+ //! smooths the image using the normalized box filter
+ // supports data type: CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4
+ // supports border type: BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT,BORDER_REFLECT_101,BORDER_WRAP
+ CV_EXPORTS void boxFilter(const oclMat &src, oclMat &dst, int ddepth, Size ksize,
+ Point anchor = Point(-1, -1), int borderType = BORDER_DEFAULT);
+
+ //! returns 2D morphological filter
+ //! only MORPH_ERODE and MORPH_DILATE are supported
+ // supports CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4 types
+ // kernel must have CV_8UC1 type, one rows and cols == ksize.width * ksize.height
+ CV_EXPORTS Ptr<BaseFilter_GPU> getMorphologyFilter_GPU(int op, int type, const Mat &kernel, const Size &ksize,
+ Point anchor = Point(-1, -1));
+
+ //! returns morphological filter engine. Only MORPH_ERODE and MORPH_DILATE are supported.
+ CV_EXPORTS Ptr<FilterEngine_GPU> createMorphologyFilter_GPU(int op, int type, const Mat &kernel,
+ const Point &anchor = Point(-1, -1), int iterations = 1);
+
+ //! a synonym for normalized box filter
+ // supports data type: CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4
+ // supports border type: BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT,BORDER_REFLECT_101
+ static inline void blur(const oclMat &src, oclMat &dst, Size ksize, Point anchor = Point(-1, -1),
+ int borderType = BORDER_CONSTANT)
+ {
+ boxFilter(src, dst, -1, ksize, anchor, borderType);
+ }
+
+ //! applies non-separable 2D linear filter to the image
+ // Note, at the moment this function only works when anchor point is in the kernel center
+ // and kernel size supported is either 3x3 or 5x5; otherwise the function will fail to output valid result
+ CV_EXPORTS void filter2D(const oclMat &src, oclMat &dst, int ddepth, const Mat &kernel,
+ Point anchor = Point(-1, -1), int borderType = BORDER_DEFAULT);
+
+ //! applies separable 2D linear filter to the image
+ CV_EXPORTS void sepFilter2D(const oclMat &src, oclMat &dst, int ddepth, const Mat &kernelX, const Mat &kernelY,
+ Point anchor = Point(-1, -1), double delta = 0.0, int bordertype = BORDER_DEFAULT);
+
+ //! applies generalized Sobel operator to the image
+ // dst.type must equalize src.type
+ // supports data type: CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4
+ // supports border type: BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT,BORDER_REFLECT_101
+ CV_EXPORTS void Sobel(const oclMat &src, oclMat &dst, int ddepth, int dx, int dy, int ksize = 3, double scale = 1, double delta = 0.0, int bordertype = BORDER_DEFAULT);
+
+ //! applies the vertical or horizontal Scharr operator to the image
+ // dst.type must equalize src.type
+ // supports data type: CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4
+ // supports border type: BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT,BORDER_REFLECT_101
+ CV_EXPORTS void Scharr(const oclMat &src, oclMat &dst, int ddepth, int dx, int dy, double scale = 1, double delta = 0.0, int bordertype = BORDER_DEFAULT);
+
+ //! smooths the image using Gaussian filter.
+ // dst.type must equalize src.type
+ // supports data type: CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4
+ // supports border type: BORDER_CONSTANT, BORDER_REPLICATE, BORDER_REFLECT,BORDER_REFLECT_101
+ CV_EXPORTS void GaussianBlur(const oclMat &src, oclMat &dst, Size ksize, double sigma1, double sigma2 = 0, int bordertype = BORDER_DEFAULT);
+
+ //! erodes the image (applies the local minimum operator)
+ // supports data type: CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4
+ CV_EXPORTS void erode( const oclMat &src, oclMat &dst, const Mat &kernel, Point anchor = Point(-1, -1), int iterations = 1,
+
+ int borderType = BORDER_CONSTANT, const Scalar &borderValue = morphologyDefaultBorderValue());
+
+
+ //! dilates the image (applies the local maximum operator)
+ // supports data type: CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4
+ CV_EXPORTS void dilate( const oclMat &src, oclMat &dst, const Mat &kernel, Point anchor = Point(-1, -1), int iterations = 1,
+
+ int borderType = BORDER_CONSTANT, const Scalar &borderValue = morphologyDefaultBorderValue());
+
+
+ //! applies an advanced morphological operation to the image
+ CV_EXPORTS void morphologyEx( const oclMat &src, oclMat &dst, int op, const Mat &kernel, Point anchor = Point(-1, -1), int iterations = 1,
+
+ int borderType = BORDER_CONSTANT, const Scalar &borderValue = morphologyDefaultBorderValue());
+
+
+ ////////////////////////////// Image processing //////////////////////////////
+ //! Does mean shift filtering on GPU.
+ CV_EXPORTS void meanShiftFiltering(const oclMat &src, oclMat &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 oclMat &src, oclMat &dstr, oclMat &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 oclMat &src, Mat &dst, int sp, int sr, int minsize,
+ TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1));
+
+ //! applies fixed threshold to the image.
+ // supports CV_8UC1 and CV_32FC1 data type
+ // supports threshold type: THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, THRESH_TOZERO, THRESH_TOZERO_INV
+ CV_EXPORTS double threshold(const oclMat &src, oclMat &dst, double thresh, double maxVal, int type = THRESH_TRUNC);
+
+ //! resizes the image
+ // Supports INTER_NEAREST, INTER_LINEAR
+ // supports CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4 types
+ CV_EXPORTS void resize(const oclMat &src, oclMat &dst, Size dsize, double fx = 0, double fy = 0, int interpolation = INTER_LINEAR);
+
+ //! Applies a generic geometrical transformation to an image.
+
+ // Supports INTER_NEAREST, INTER_LINEAR.
+
+ // Map1 supports CV_16SC2, CV_32FC2 types.
+
+ // Src supports CV_8UC1, CV_8UC2, CV_8UC4.
+
+ CV_EXPORTS void remap(const oclMat &src, oclMat &dst, oclMat &map1, oclMat &map2, int interpolation, int bordertype, const Scalar &value = Scalar());
+
+ //! 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 oclMat &src, oclMat &dst, int top, int bottom, int left, int right, int boardtype, const Scalar &value = Scalar());
+
+ //! Smoothes image using median filter
+ // The source 1- or 4-channel image. When m is 3 or 5, the image depth should be CV 8U or CV 32F.
+ CV_EXPORTS void medianFilter(const oclMat &src, oclMat &dst, int m);
+
+ //! warps the image using affine transformation
+ // Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
+ // supports CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4 types
+ CV_EXPORTS void warpAffine(const oclMat &src, oclMat &dst, const Mat &M, Size dsize, int flags = INTER_LINEAR);
+
+ //! warps the image using perspective transformation
+ // Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
+ // supports CV_8UC1, CV_8UC4, CV_32FC1 and CV_32FC4 types
+ CV_EXPORTS void warpPerspective(const oclMat &src, oclMat &dst, const Mat &M, Size dsize, int flags = INTER_LINEAR);
+
+ //! computes the integral image and integral for the squared image
+ // sum will have CV_32S type, sqsum - CV32F type
+ // supports only CV_8UC1 source type
+ CV_EXPORTS void integral(const oclMat &src, oclMat &sum, oclMat &sqsum);
+ CV_EXPORTS void integral(const oclMat &src, oclMat &sum);
+ CV_EXPORTS void cornerHarris(const oclMat &src, oclMat &dst, int blockSize, int ksize, double k, int bordertype = cv::BORDER_DEFAULT);
+ CV_EXPORTS void cornerHarris_dxdy(const oclMat &src, oclMat &dst, oclMat &Dx, oclMat &Dy,
+ int blockSize, int ksize, double k, int bordertype = cv::BORDER_DEFAULT);
+ CV_EXPORTS void cornerMinEigenVal(const oclMat &src, oclMat &dst, int blockSize, int ksize, int bordertype = cv::BORDER_DEFAULT);
+ CV_EXPORTS void cornerMinEigenVal_dxdy(const oclMat &src, oclMat &dst, oclMat &Dx, oclMat &Dy,
+ int blockSize, int ksize, int bordertype = cv::BORDER_DEFAULT);
+
+ ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ ///////////////////////////////////////////CascadeClassifier//////////////////////////////////////////////////////////////////
+ ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+
+#if 0
+ class CV_EXPORTS OclCascadeClassifier : public cv::CascadeClassifier
+ {
+ public:
+ OclCascadeClassifier() {};
+ ~OclCascadeClassifier() {};
+
+ CvSeq* oclHaarDetectObjects(oclMat &gimg, CvMemStorage *storage, double scaleFactor,
+ int minNeighbors, int flags, CvSize minSize = cvSize(0, 0), CvSize maxSize = cvSize(0, 0));
+ };
+#endif
+
+#if 0
+ class CV_EXPORTS OclCascadeClassifierBuf : public cv::CascadeClassifier
+ {
+ public:
+ OclCascadeClassifierBuf() :
+ m_flags(0), initialized(false), m_scaleFactor(0), buffers(NULL) {}
+
+ ~OclCascadeClassifierBuf() { release(); }
+
+ void detectMultiScale(oclMat &image, CV_OUT std::vector<cv::Rect>& faces,
+ double scaleFactor = 1.1, int minNeighbors = 3, int flags = 0,
+ Size minSize = Size(), Size maxSize = Size());
+ void release();
+
+ private:
+ void Init(const int rows, const int cols, double scaleFactor, int flags,
+ const int outputsz, const size_t localThreads[],
+ Size minSize, Size maxSize);
+ void CreateBaseBufs(const int datasize, const int totalclassifier, const int flags, const int outputsz);
+ void CreateFactorRelatedBufs(const int rows, const int cols, const int flags,
+ const double scaleFactor, const size_t localThreads[],
+ Size minSize, Size maxSize);
+ void GenResult(CV_OUT std::vector<cv::Rect>& faces, const std::vector<cv::Rect> &rectList, const std::vector<int> &rweights);
+
+ int m_rows;
+ int m_cols;
+ int m_flags;
+ int m_loopcount;
+ int m_nodenum;
+ bool findBiggestObject;
+ bool initialized;
+ double m_scaleFactor;
+ Size m_minSize;
+ Size m_maxSize;
+ std::vector<Size> sizev;
+ std::vector<float> scalev;
+ oclMat gimg1, gsum, gsqsum;
+ void * buffers;
+ };
+#endif
+
+ /////////////////////////////// Pyramid /////////////////////////////////////
+ CV_EXPORTS void pyrDown(const oclMat &src, oclMat &dst);
+
+ //! upsamples the source image and then smoothes it
+ CV_EXPORTS void pyrUp(const oclMat &src, oclMat &dst);
+
+ //! performs linear blending of two images
+ //! to avoid accuracy errors sum of weigths shouldn't be very close to zero
+ // supports only CV_8UC1 source type
+ CV_EXPORTS void blendLinear(const oclMat &img1, const oclMat &img2, const oclMat &weights1, const oclMat &weights2, oclMat &result);
+
+ //! computes vertical sum, supports only CV_32FC1 images
+ CV_EXPORTS void columnSum(const oclMat &src, oclMat &sum);
+
+ ///////////////////////////////////////// match_template /////////////////////////////////////////////////////////////
+ struct CV_EXPORTS MatchTemplateBuf
+ {
+ Size user_block_size;
+ oclMat imagef, templf;
+ std::vector<oclMat> images;
+ std::vector<oclMat> image_sums;
+ std::vector<oclMat> image_sqsums;
+ };
+
+ //! computes the proximity map for the raster template and the image where the template is searched for
+ // Supports TM_SQDIFF, TM_SQDIFF_NORMED, TM_CCORR, TM_CCORR_NORMED, TM_CCOEFF, TM_CCOEFF_NORMED for type 8UC1 and 8UC4
+ // Supports TM_SQDIFF, TM_CCORR for type 32FC1 and 32FC4
+ CV_EXPORTS void matchTemplate(const oclMat &image, const oclMat &templ, oclMat &result, int method);
+
+ //! computes the proximity map for the raster template and the image where the template is searched for
+ // Supports TM_SQDIFF, TM_SQDIFF_NORMED, TM_CCORR, TM_CCORR_NORMED, TM_CCOEFF, TM_CCOEFF_NORMED for type 8UC1 and 8UC4
+ // Supports TM_SQDIFF, TM_CCORR for type 32FC1 and 32FC4
+ CV_EXPORTS void matchTemplate(const oclMat &image, const oclMat &templ, oclMat &result, int method, MatchTemplateBuf &buf);
+
+
+
+ ///////////////////////////////////////////// Canny /////////////////////////////////////////////
+ struct CV_EXPORTS CannyBuf;
+
+ //! compute edges of the input image using Canny operator
+ // Support CV_8UC1 only
+ CV_EXPORTS void Canny(const oclMat &image, oclMat &edges, double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false);
+ CV_EXPORTS void Canny(const oclMat &image, CannyBuf &buf, oclMat &edges, double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false);
+ CV_EXPORTS void Canny(const oclMat &dx, const oclMat &dy, oclMat &edges, double low_thresh, double high_thresh, bool L2gradient = false);
+ CV_EXPORTS void Canny(const oclMat &dx, const oclMat &dy, CannyBuf &buf, oclMat &edges, double low_thresh, double high_thresh, bool L2gradient = false);
+
+ struct CV_EXPORTS CannyBuf
+ {
+ CannyBuf() : counter(NULL) {}
+ ~CannyBuf()
+ {
+ release();
+ }
+ explicit CannyBuf(const Size &image_size, int apperture_size = 3) : counter(NULL)
+ {
+ create(image_size, apperture_size);
+ }
+ CannyBuf(const oclMat &dx_, const oclMat &dy_);
+ void create(const Size &image_size, int apperture_size = 3);
+ void release();
+
+ oclMat dx, dy;
+ oclMat dx_buf, dy_buf;
+ oclMat magBuf, mapBuf;
+ oclMat trackBuf1, trackBuf2;
+ void *counter;
+ Ptr<FilterEngine_GPU> filterDX, filterDY;
+ };
+
+ ///////////////////////////////////////// Hough Transform /////////////////////////////////////////
+ //! HoughCircles
+ struct HoughCirclesBuf
+ {
+ oclMat edges;
+ oclMat accum;
+ oclMat srcPoints;
+ oclMat centers;
+ CannyBuf cannyBuf;
+ };
+
+ CV_EXPORTS void HoughCircles(const oclMat& src, oclMat& circles, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096);
+ CV_EXPORTS void HoughCircles(const oclMat& src, oclMat& circles, HoughCirclesBuf& buf, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096);
+ CV_EXPORTS void HoughCirclesDownload(const oclMat& d_circles, OutputArray h_circles);
+
+
+ ///////////////////////////////////////// clAmdFft related /////////////////////////////////////////
+ //! Performs a forward or inverse discrete Fourier transform (1D or 2D) of floating point matrix.
+ //! Param dft_size is the size of DFT transform.
+ //!
+ //! For complex-to-real transform it is assumed that the source matrix is packed in CLFFT's format.
+ // support src type of CV32FC1, CV32FC2
+ // support flags: DFT_INVERSE, DFT_REAL_OUTPUT, DFT_COMPLEX_OUTPUT, DFT_ROWS
+ // dft_size is the size of original input, which is used for transformation from complex to real.
+ // dft_size must be powers of 2, 3 and 5
+ // real to complex dft requires at least v1.8 clAmdFft
+ // real to complex dft output is not the same with cpu version
+ // real to complex and complex to real does not support DFT_ROWS
+ CV_EXPORTS void dft(const oclMat &src, oclMat &dst, Size dft_size = Size(0, 0), int flags = 0);
+
+ //! implements generalized matrix product algorithm GEMM from BLAS
+ // The functionality requires clAmdBlas library
+ // only support type CV_32FC1
+ // flag GEMM_3_T is not supported
+ CV_EXPORTS void gemm(const oclMat &src1, const oclMat &src2, double alpha,
+ const oclMat &src3, double beta, oclMat &dst, int flags = 0);
+
+ //////////////// HOG (Histogram-of-Oriented-Gradients) Descriptor and Object Detector //////////////
+
+ struct CV_EXPORTS HOGDescriptor
+
+ {
+
+ enum { DEFAULT_WIN_SIGMA = -1 };
+
+ enum { DEFAULT_NLEVELS = 64 };
+
+ enum { DESCR_FORMAT_ROW_BY_ROW, DESCR_FORMAT_COL_BY_COL };
+
+
+
+ HOGDescriptor(Size win_size = Size(64, 128), Size block_size = Size(16, 16),
+
+ Size block_stride = Size(8, 8), Size cell_size = Size(8, 8),
+
+ int nbins = 9, double win_sigma = DEFAULT_WIN_SIGMA,
+
+ double threshold_L2hys = 0.2, bool gamma_correction = true,
+
+ int nlevels = DEFAULT_NLEVELS);
+
+
+
+ size_t getDescriptorSize() const;
+
+ size_t getBlockHistogramSize() const;
+
+
+
+ void setSVMDetector(const std::vector<float> &detector);
+
+
+
+ static std::vector<float> getDefaultPeopleDetector();
+
+ static std::vector<float> getPeopleDetector48x96();
+
+ static std::vector<float> getPeopleDetector64x128();
+
+
+
+ void detect(const oclMat &img, std::vector<Point> &found_locations,
+
+ double hit_threshold = 0, Size win_stride = Size(),
+
+ Size padding = Size());
+
+
+
+ void detectMultiScale(const oclMat &img, std::vector<Rect> &found_locations,
+
+ double hit_threshold = 0, Size win_stride = Size(),
+
+ Size padding = Size(), double scale0 = 1.05,
+
+ int group_threshold = 2);
+
+
+
+ void getDescriptors(const oclMat &img, Size win_stride,
+
+ oclMat &descriptors,
+
+ int descr_format = DESCR_FORMAT_COL_BY_COL);
+
+
+
+ Size win_size;
+
+ Size block_size;
+
+ Size block_stride;
+
+ Size cell_size;
+
+ int nbins;
+
+ double win_sigma;
+
+ double threshold_L2hys;
+
+ bool gamma_correction;
+
+ int nlevels;
+
+
+
+ protected:
+
+ // initialize buffers; only need to do once in case of multiscale detection
+
+ void init_buffer(const oclMat &img, Size win_stride);
+
+
+
+ void computeBlockHistograms(const oclMat &img);
+
+ void computeGradient(const oclMat &img, oclMat &grad, oclMat &qangle);
+
+
+
+ double getWinSigma() const;
+
+ bool checkDetectorSize() const;
+
+
+
+ static int numPartsWithin(int size, int part_size, int stride);
+
+ static Size numPartsWithin(Size size, Size part_size, Size stride);
+
+
+
+ // Coefficients of the separating plane
+
+ float free_coef;
+
+ oclMat detector;
+
+
+
+ // Results of the last classification step
+
+ oclMat labels;
+
+ Mat labels_host;
+
+
+
+ // Results of the last histogram evaluation step
+
+ oclMat block_hists;
+
+
+
+ // Gradients conputation results
+
+ oclMat grad, qangle;
+
+
+
+ // scaled image
+
+ oclMat image_scale;
+
+
+
+ // effect size of input image (might be different from original size after scaling)
+
+ Size effect_size;
+
+ };
+
+
+ ////////////////////////feature2d_ocl/////////////////
+ /****************************************************************************************\
+ * Distance *
+ \****************************************************************************************/
+ template<typename T>
+ struct CV_EXPORTS Accumulator
+ {
+ typedef T Type;
+ };
+ template<> struct Accumulator<unsigned char>
+ {
+ typedef float Type;
+ };
+ template<> struct Accumulator<unsigned short>
+ {
+ typedef float Type;
+ };
+ template<> struct Accumulator<char>
+ {
+ typedef float Type;
+ };
+ template<> struct Accumulator<short>
+ {
+ typedef float Type;
+ };
+
+ /*
+ * Manhattan distance (city block distance) functor
+ */
+ template<class T>
+ struct CV_EXPORTS L1
+ {
+ enum { normType = NORM_L1 };
+ typedef T ValueType;
+ typedef typename Accumulator<T>::Type ResultType;
+
+ ResultType operator()( const T *a, const T *b, int size ) const
+ {
+ return normL1<ValueType, ResultType>(a, b, size);
+ }
+ };
+
+ /*
+ * Euclidean distance functor
+ */
+ template<class T>
+ struct CV_EXPORTS L2
+ {
+ enum { normType = NORM_L2 };
+ typedef T ValueType;
+ typedef typename Accumulator<T>::Type ResultType;
+
+ ResultType operator()( const T *a, const T *b, int size ) const
+ {
+ return (ResultType)std::sqrt((double)normL2Sqr<ValueType, ResultType>(a, b, size));
+ }
+ };
+
+ /*
+ * Hamming distance functor - counts the bit differences between two strings - useful for the Brief descriptor
+ * bit count of A exclusive XOR'ed with B
+ */
+ struct CV_EXPORTS Hamming
+ {
+ enum { normType = NORM_HAMMING };
+ typedef unsigned char ValueType;
+ typedef int ResultType;
+
+ /** this will count the bits in a ^ b
+ */
+ ResultType operator()( const unsigned char *a, const unsigned char *b, int size ) const
+ {
+ return normHamming(a, b, size);
+ }
+ };
+
+ ////////////////////////////////// BruteForceMatcher //////////////////////////////////
+
+ class CV_EXPORTS BruteForceMatcher_OCL_base
+ {
+ public:
+ enum DistType {L1Dist = 0, L2Dist, HammingDist};
+ explicit BruteForceMatcher_OCL_base(DistType distType = L2Dist);
+
+ // Add descriptors to train descriptor collection
+ void add(const std::vector<oclMat> &descCollection);
+
+ // Get train descriptors collection
+ const std::vector<oclMat> &getTrainDescriptors() const;
+
+ // Clear train descriptors collection
+ void clear();
+
+ // Return true if there are not train descriptors in collection
+ bool empty() const;
+
+ // Return true if the matcher supports mask in match methods
+ bool isMaskSupported() const;
+
+ // Find one best match for each query descriptor
+ void matchSingle(const oclMat &query, const oclMat &train,
+ oclMat &trainIdx, oclMat &distance,
+ const oclMat &mask = oclMat());
+
+ // Download trainIdx and distance and convert it to CPU vector with DMatch
+ static void matchDownload(const oclMat &trainIdx, const oclMat &distance, std::vector<DMatch> &matches);
+ // Convert trainIdx and distance to vector with DMatch
+ static void matchConvert(const Mat &trainIdx, const Mat &distance, std::vector<DMatch> &matches);
+
+ // Find one best match for each query descriptor
+ void match(const oclMat &query, const oclMat &train, std::vector<DMatch> &matches, const oclMat &mask = oclMat());
+
+ // Make gpu collection of trains and masks in suitable format for matchCollection function
+ void makeGpuCollection(oclMat &trainCollection, oclMat &maskCollection, const std::vector<oclMat> &masks = std::vector<oclMat>());
+
+ // Find one best match from train collection for each query descriptor
+ void matchCollection(const oclMat &query, const oclMat &trainCollection,
+ oclMat &trainIdx, oclMat &imgIdx, oclMat &distance,
+ const oclMat &masks = oclMat());
+
+ // Download trainIdx, imgIdx and distance and convert it to vector with DMatch
+ static void matchDownload(const oclMat &trainIdx, const oclMat &imgIdx, const oclMat &distance, std::vector<DMatch> &matches);
+ // Convert trainIdx, imgIdx and distance to vector with DMatch
+ static void matchConvert(const Mat &trainIdx, const Mat &imgIdx, const Mat &distance, std::vector<DMatch> &matches);
+
+ // Find one best match from train collection for each query descriptor.
+ void match(const oclMat &query, std::vector<DMatch> &matches, const std::vector<oclMat> &masks = std::vector<oclMat>());
+
+ // Find k best matches for each query descriptor (in increasing order of distances)
+ void knnMatchSingle(const oclMat &query, const oclMat &train,
+ oclMat &trainIdx, oclMat &distance, oclMat &allDist, int k,
+ const oclMat &mask = oclMat());
+
+ // Download trainIdx and distance and convert it to vector with DMatch
+ // compactResult is used when mask is not empty. If compactResult is false matches
+ // vector will have the same size as queryDescriptors rows. If compactResult is true
+ // matches vector will not contain matches for fully masked out query descriptors.
+ static void knnMatchDownload(const oclMat &trainIdx, const oclMat &distance,
+ std::vector< std::vector<DMatch> > &matches, bool compactResult = false);
+ // Convert trainIdx and distance to vector with DMatch
+ static void knnMatchConvert(const Mat &trainIdx, const Mat &distance,
+ std::vector< std::vector<DMatch> > &matches, bool compactResult = false);
+
+ // Find k best matches for each query descriptor (in increasing order of distances).
+ // compactResult is used when mask is not empty. If compactResult is false matches
+ // vector will have the same size as queryDescriptors rows. If compactResult is true
+ // matches vector will not contain matches for fully masked out query descriptors.
+ void knnMatch(const oclMat &query, const oclMat &train,
+ std::vector< std::vector<DMatch> > &matches, int k, const oclMat &mask = oclMat(),
+ bool compactResult = false);
+
+ // Find k best matches from train collection for each query descriptor (in increasing order of distances)
+ void knnMatch2Collection(const oclMat &query, const oclMat &trainCollection,
+ oclMat &trainIdx, oclMat &imgIdx, oclMat &distance,
+ const oclMat &maskCollection = oclMat());
+
+ // Download trainIdx and distance and convert it to vector with DMatch
+ // compactResult is used when mask is not empty. If compactResult is false matches
+ // vector will have the same size as queryDescriptors rows. If compactResult is true
+ // matches vector will not contain matches for fully masked out query descriptors.
+ static void knnMatch2Download(const oclMat &trainIdx, const oclMat &imgIdx, const oclMat &distance,
+ std::vector< std::vector<DMatch> > &matches, bool compactResult = false);
+ // Convert trainIdx and distance to vector with DMatch
+ static void knnMatch2Convert(const Mat &trainIdx, const Mat &imgIdx, const Mat &distance,
+ std::vector< std::vector<DMatch> > &matches, bool compactResult = false);
+
+ // Find k best matches for each query descriptor (in increasing order of distances).
+ // compactResult is used when mask is not empty. If compactResult is false matches
+ // vector will have the same size as queryDescriptors rows. If compactResult is true
+ // matches vector will not contain matches for fully masked out query descriptors.
+ void knnMatch(const oclMat &query, std::vector< std::vector<DMatch> > &matches, int k,
+ const std::vector<oclMat> &masks = std::vector<oclMat>(), bool compactResult = false);
+
+ // Find best matches for each query descriptor which have distance less than maxDistance.
+ // nMatches.at<int>(0, queryIdx) will contain matches count for queryIdx.
+ // carefully nMatches can be greater than trainIdx.cols - it means that matcher didn't find all matches,
+ // because it didn't have enough memory.
+ // If trainIdx is empty, then trainIdx and distance will be created with size nQuery x max((nTrain / 100), 10),
+ // otherwize user can pass own allocated trainIdx and distance with size nQuery x nMaxMatches
+ // Matches doesn't sorted.
+ void radiusMatchSingle(const oclMat &query, const oclMat &train,
+ oclMat &trainIdx, oclMat &distance, oclMat &nMatches, float maxDistance,
+ const oclMat &mask = oclMat());
+
+ // Download trainIdx, nMatches and distance and convert it to vector with DMatch.
+ // matches will be sorted in increasing order of distances.
+ // compactResult is used when mask is not empty. If compactResult is false matches
+ // vector will have the same size as queryDescriptors rows. If compactResult is true
+ // matches vector will not contain matches for fully masked out query descriptors.
+ static void radiusMatchDownload(const oclMat &trainIdx, const oclMat &distance, const oclMat &nMatches,
+ std::vector< std::vector<DMatch> > &matches, bool compactResult = false);
+ // Convert trainIdx, nMatches and distance to vector with DMatch.
+ static void radiusMatchConvert(const Mat &trainIdx, const Mat &distance, const Mat &nMatches,
+ std::vector< std::vector<DMatch> > &matches, bool compactResult = false);
+
+ // Find best matches for each query descriptor which have distance less than maxDistance
+ // in increasing order of distances).
+ void radiusMatch(const oclMat &query, const oclMat &train,
+ std::vector< std::vector<DMatch> > &matches, float maxDistance,
+ const oclMat &mask = oclMat(), bool compactResult = false);
+
+ // Find best matches for each query descriptor which have distance less than maxDistance.
+ // If trainIdx is empty, then trainIdx and distance will be created with size nQuery x max((nQuery / 100), 10),
+ // otherwize user can pass own allocated trainIdx and distance with size nQuery x nMaxMatches
+ // Matches doesn't sorted.
+ void radiusMatchCollection(const oclMat &query, oclMat &trainIdx, oclMat &imgIdx, oclMat &distance, oclMat &nMatches, float maxDistance,
+ const std::vector<oclMat> &masks = std::vector<oclMat>());
+
+ // Download trainIdx, imgIdx, nMatches and distance and convert it to vector with DMatch.
+ // matches will be sorted in increasing order of distances.
+ // compactResult is used when mask is not empty. If compactResult is false matches
+ // vector will have the same size as queryDescriptors rows. If compactResult is true
+ // matches vector will not contain matches for fully masked out query descriptors.
+ static void radiusMatchDownload(const oclMat &trainIdx, const oclMat &imgIdx, const oclMat &distance, const oclMat &nMatches,
+ std::vector< std::vector<DMatch> > &matches, bool compactResult = false);
+ // Convert trainIdx, nMatches and distance to vector with DMatch.
+ static void radiusMatchConvert(const Mat &trainIdx, const Mat &imgIdx, const Mat &distance, const Mat &nMatches,
+ std::vector< std::vector<DMatch> > &matches, bool compactResult = false);
+
+ // Find best matches from train collection for each query descriptor which have distance less than
+ // maxDistance (in increasing order of distances).
+ void radiusMatch(const oclMat &query, std::vector< std::vector<DMatch> > &matches, float maxDistance,
+ const std::vector<oclMat> &masks = std::vector<oclMat>(), bool compactResult = false);
+
+ DistType distType;
+
+ private:
+ std::vector<oclMat> trainDescCollection;
+ };
+
+ template <class Distance>
+ class CV_EXPORTS BruteForceMatcher_OCL;
+
+ template <typename T>
+ class CV_EXPORTS BruteForceMatcher_OCL< L1<T> > : public BruteForceMatcher_OCL_base
+ {
+ public:
+ explicit BruteForceMatcher_OCL() : BruteForceMatcher_OCL_base(L1Dist) {}
+ explicit BruteForceMatcher_OCL(L1<T> /*d*/) : BruteForceMatcher_OCL_base(L1Dist) {}
+ };
+ template <typename T>
+ class CV_EXPORTS BruteForceMatcher_OCL< L2<T> > : public BruteForceMatcher_OCL_base
+ {
+ public:
+ explicit BruteForceMatcher_OCL() : BruteForceMatcher_OCL_base(L2Dist) {}
+ explicit BruteForceMatcher_OCL(L2<T> /*d*/) : BruteForceMatcher_OCL_base(L2Dist) {}
+ };
+ template <> class CV_EXPORTS BruteForceMatcher_OCL< Hamming > : public BruteForceMatcher_OCL_base
+ {
+ public:
+ explicit BruteForceMatcher_OCL() : BruteForceMatcher_OCL_base(HammingDist) {}
+ explicit BruteForceMatcher_OCL(Hamming /*d*/) : BruteForceMatcher_OCL_base(HammingDist) {}
+ };
+
+ class CV_EXPORTS BFMatcher_OCL : public BruteForceMatcher_OCL_base
+ {
+ public:
+ explicit BFMatcher_OCL(int norm = NORM_L2) : BruteForceMatcher_OCL_base(norm == NORM_L1 ? L1Dist : norm == NORM_L2 ? L2Dist : HammingDist) {}
+ };
+
+ class CV_EXPORTS GoodFeaturesToTrackDetector_OCL
+ {
+ public:
+ explicit GoodFeaturesToTrackDetector_OCL(int maxCorners = 1000, double qualityLevel = 0.01, double minDistance = 0.0,
+ int blockSize = 3, bool useHarrisDetector = false, double harrisK = 0.04);
+
+ //! return 1 rows matrix with CV_32FC2 type
+ void operator ()(const oclMat& image, oclMat& corners, const oclMat& mask = oclMat());
+ //! download points of type Point2f to a vector. the vector's content will be erased
+ void downloadPoints(const oclMat &points, std::vector<Point2f> &points_v);
+
+ int maxCorners;
+ double qualityLevel;
+ double minDistance;
+
+ int blockSize;
+ bool useHarrisDetector;
+ double harrisK;
+ void releaseMemory()
+ {
+ Dx_.release();
+ Dy_.release();
+ eig_.release();
+ minMaxbuf_.release();
+ tmpCorners_.release();
+ }
+ private:
+ oclMat Dx_;
+ oclMat Dy_;
+ oclMat eig_;
+ oclMat minMaxbuf_;
+ oclMat tmpCorners_;
+ };
+
+ inline GoodFeaturesToTrackDetector_OCL::GoodFeaturesToTrackDetector_OCL(int maxCorners_, double qualityLevel_, double minDistance_,
+ int blockSize_, bool useHarrisDetector_, double harrisK_)
+ {
+ maxCorners = maxCorners_;
+ qualityLevel = qualityLevel_;
+ minDistance = minDistance_;
+ blockSize = blockSize_;
+ useHarrisDetector = useHarrisDetector_;
+ harrisK = harrisK_;
+ }
+
+ /////////////////////////////// PyrLKOpticalFlow /////////////////////////////////////
+
+ class CV_EXPORTS PyrLKOpticalFlow
+ {
+ public:
+ PyrLKOpticalFlow()
+ {
+ winSize = Size(21, 21);
+ maxLevel = 3;
+ iters = 30;
+ derivLambda = 0.5;
+ useInitialFlow = false;
+ minEigThreshold = 1e-4f;
+ getMinEigenVals = false;
+ isDeviceArch11_ = false;
+ }
+
+ void sparse(const oclMat &prevImg, const oclMat &nextImg, const oclMat &prevPts, oclMat &nextPts,
+ oclMat &status, oclMat *err = 0);
+
+ void dense(const oclMat &prevImg, const oclMat &nextImg, oclMat &u, oclMat &v, oclMat *err = 0);
+
+ Size winSize;
+ int maxLevel;
+ int iters;
+ double derivLambda;
+ bool useInitialFlow;
+ float minEigThreshold;
+ bool getMinEigenVals;
+
+ void releaseMemory()
+ {
+ dx_calcBuf_.release();
+ dy_calcBuf_.release();
+
+ prevPyr_.clear();
+ nextPyr_.clear();
+
+ dx_buf_.release();
+ dy_buf_.release();
+ }
+
+ private:
+ void calcSharrDeriv(const oclMat &src, oclMat &dx, oclMat &dy);
+
+ void buildImagePyramid(const oclMat &img0, std::vector<oclMat> &pyr, bool withBorder);
+
+ oclMat dx_calcBuf_;
+ oclMat dy_calcBuf_;
+
+ std::vector<oclMat> prevPyr_;
+ std::vector<oclMat> nextPyr_;
+
+ oclMat dx_buf_;
+ oclMat dy_buf_;
+
+ oclMat uPyr_[2];
+ oclMat vPyr_[2];
+
+ bool isDeviceArch11_;
+ };
+ //////////////// build warping maps ////////////////////
+ //! builds plane warping maps
+ CV_EXPORTS void buildWarpPlaneMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat &R, const Mat &T, float scale, oclMat &map_x, oclMat &map_y);
+ //! builds cylindrical warping maps
+ CV_EXPORTS void buildWarpCylindricalMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat &R, float scale, oclMat &map_x, oclMat &map_y);
+ //! builds spherical warping maps
+ CV_EXPORTS void buildWarpSphericalMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat &R, float scale, oclMat &map_x, oclMat &map_y);
+ //! builds Affine warping maps
+ CV_EXPORTS void buildWarpAffineMaps(const Mat &M, bool inverse, Size dsize, oclMat &xmap, oclMat &ymap);
+
+ //! builds Perspective warping maps
+ CV_EXPORTS void buildWarpPerspectiveMaps(const Mat &M, bool inverse, Size dsize, oclMat &xmap, oclMat &ymap);
+
+ ///////////////////////////////////// interpolate frames //////////////////////////////////////////////
+ //! Interpolate frames (images) using provided optical flow (displacement field).
+ //! frame0 - frame 0 (32-bit floating point images, single channel)
+ //! frame1 - frame 1 (the same type and size)
+ //! fu - forward horizontal displacement
+ //! fv - forward vertical displacement
+ //! bu - backward horizontal displacement
+ //! bv - backward vertical displacement
+ //! pos - new frame position
+ //! newFrame - new frame
+ //! buf - temporary buffer, will have width x 6*height size, CV_32FC1 type and contain 6 oclMat;
+ //! occlusion masks 0, occlusion masks 1,
+ //! interpolated forward flow 0, interpolated forward flow 1,
+ //! interpolated backward flow 0, interpolated backward flow 1
+ //!
+ CV_EXPORTS void interpolateFrames(const oclMat &frame0, const oclMat &frame1,
+ const oclMat &fu, const oclMat &fv,
+ const oclMat &bu, const oclMat &bv,
+ float pos, oclMat &newFrame, oclMat &buf);
+
+ //! computes moments of the rasterized shape or a vector of points
+ CV_EXPORTS Moments ocl_moments(InputArray _array, bool binaryImage);
+
+ class CV_EXPORTS StereoBM_OCL
+ {
+ public:
+ enum { BASIC_PRESET = 0, PREFILTER_XSOBEL = 1 };
+
+ enum { DEFAULT_NDISP = 64, DEFAULT_WINSZ = 19 };
+
+ //! the default constructor
+ StereoBM_OCL();
+ //! the full constructor taking the camera-specific preset, number of disparities and the SAD window size. ndisparities must be multiple of 8.
+ StereoBM_OCL(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 oclMat &left, const oclMat &right, oclMat &disparity);
+
+ //! 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 preset;
+ int ndisp;
+ int winSize;
+
+ // 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:
+ oclMat minSSD, leBuf, riBuf;
+ };
+
+ 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);
+ explicit StereoBeliefPropagation(int ndisp = DEFAULT_NDISP,
+ int iters = DEFAULT_ITERS,
+ int levels = DEFAULT_LEVELS,
+ int msg_type = CV_16S);
+ 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);
+ void operator()(const oclMat &left, const oclMat &right, oclMat &disparity);
+ void operator()(const oclMat &data, oclMat &disparity);
+ 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:
+ oclMat u, d, l, r, u2, d2, l2, r2;
+ std::vector<oclMat> datas;
+ oclMat out;
+ };
+
+ 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);
+ 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);
+ 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);
+ void operator()(const oclMat &left, const oclMat &right, oclMat &disparity);
+ 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:
+ oclMat u[2], d[2], l[2], r[2];
+ oclMat disp_selected_pyr[2];
+ oclMat data_cost;
+ oclMat data_cost_selected;
+ oclMat temp;
+ oclMat out;
+ };
+
+ // Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method
+ //
+ // see reference:
+ // [1] C. Zach, T. Pock and H. Bischof, "A Duality Based Approach for Realtime TV-L1 Optical Flow".
+ // [2] Javier Sanchez, Enric Meinhardt-Llopis and Gabriele Facciolo. "TV-L1 Optical Flow Estimation".
+ class CV_EXPORTS OpticalFlowDual_TVL1_OCL
+ {
+ public:
+ OpticalFlowDual_TVL1_OCL();
+
+ void operator ()(const oclMat& I0, const oclMat& I1, oclMat& flowx, oclMat& flowy);
+
+ void collectGarbage();
+
+ /**
+ * Time step of the numerical scheme.
+ */
+ double tau;
+
+ /**
+ * Weight parameter for the data term, attachment parameter.
+ * This is the most relevant parameter, which determines the smoothness of the output.
+ * The smaller this parameter is, the smoother the solutions we obtain.
+ * It depends on the range of motions of the images, so its value should be adapted to each image sequence.
+ */
+ double lambda;
+
+ /**
+ * Weight parameter for (u - v)^2, tightness parameter.
+ * It serves as a link between the attachment and the regularization terms.
+ * In theory, it should have a small value in order to maintain both parts in correspondence.
+ * The method is stable for a large range of values of this parameter.
+ */
+ double theta;
+
+ /**
+ * Number of scales used to create the pyramid of images.
+ */
+ int nscales;
+
+ /**
+ * Number of warpings per scale.
+ * Represents the number of times that I1(x+u0) and grad( I1(x+u0) ) are computed per scale.
+ * This is a parameter that assures the stability of the method.
+ * It also affects the running time, so it is a compromise between speed and accuracy.
+ */
+ int warps;
+
+ /**
+ * Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time.
+ * A small value will yield more accurate solutions at the expense of a slower convergence.
+ */
+ double epsilon;
+
+ /**
+ * Stopping criterion iterations number used in the numerical scheme.
+ */
+ int iterations;
+
+ bool useInitialFlow;
+
+ private:
+ void procOneScale(const oclMat& I0, const oclMat& I1, oclMat& u1, oclMat& u2);
+
+ std::vector<oclMat> I0s;
+ std::vector<oclMat> I1s;
+ std::vector<oclMat> u1s;
+ std::vector<oclMat> u2s;
+
+ oclMat I1x_buf;
+ oclMat I1y_buf;
+
+ oclMat I1w_buf;
+ oclMat I1wx_buf;
+ oclMat I1wy_buf;
+
+ oclMat grad_buf;
+ oclMat rho_c_buf;
+
+ oclMat p11_buf;
+ oclMat p12_buf;
+ oclMat p21_buf;
+ oclMat p22_buf;
+
+ oclMat diff_buf;
+ oclMat norm_buf;
+ };
+ }
+}
+#if defined _MSC_VER && _MSC_VER >= 1200
+# pragma warning( push)
+# pragma warning( disable: 4267)
+#endif
+#include "opencv2/ocl/matrix_operations.hpp"
+#if defined _MSC_VER && _MSC_VER >= 1200
+# pragma warning( pop)
+#endif
+
+#endif /* __OPENCV_OCL_HPP__ */
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