Diff: include/opencv2/core/cuda.hpp

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+/*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.
+// Copyright (C) 2013, OpenCV Foundation, 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_CORE_CUDA_HPP
+#define OPENCV_CORE_CUDA_HPP
+
+#ifndef __cplusplus
+#  error cuda.hpp header must be compiled as C++
+#endif
+
+#include "opencv2/core.hpp"
+#include "opencv2/core/cuda_types.hpp"
+
+/**
+  @defgroup cuda CUDA-accelerated Computer Vision
+  @{
+    @defgroup cudacore Core part
+    @{
+      @defgroup cudacore_init Initalization and Information
+      @defgroup cudacore_struct Data Structures
+    @}
+  @}
+ */
+
+namespace cv { namespace cuda {
+
+//! @addtogroup cudacore_struct
+//! @{
+
+//===================================================================================
+// GpuMat
+//===================================================================================
+
+/** @brief Base storage class for GPU memory with reference counting.
+
+Its interface matches the Mat interface with the following limitations:
+
+-   no arbitrary dimensions support (only 2D)
+-   no functions that return references to their data (because references on GPU are not valid for
+    CPU)
+-   no expression templates technique support
+
+Beware that the latter limitation may lead to overloaded matrix operators that cause memory
+allocations. The GpuMat class is convertible to cuda::PtrStepSz and cuda::PtrStep so it can be
+passed directly to the kernel.
+
+@note In contrast with Mat, in most cases GpuMat::isContinuous() == false . This means that rows are
+aligned to a size depending on the hardware. Single-row GpuMat is always a continuous matrix.
+
+@note You are not recommended to leave static or global GpuMat variables allocated, that is, to rely
+on its destructor. The destruction order of such variables and CUDA context is undefined. GPU memory
+release function returns error if the CUDA context has been destroyed before.
+
+@sa Mat
+ */
+class CV_EXPORTS GpuMat
+{
+public:
+    class CV_EXPORTS Allocator
+    {
+    public:
+        virtual ~Allocator() {}
+
+        // allocator must fill data, step and refcount fields
+        virtual bool allocate(GpuMat* mat, int rows, int cols, size_t elemSize) = 0;
+        virtual void free(GpuMat* mat) = 0;
+    };
+
+    //! default allocator
+    static Allocator* defaultAllocator();
+    static void setDefaultAllocator(Allocator* allocator);
+
+    //! default constructor
+    explicit GpuMat(Allocator* allocator = defaultAllocator());
+
+    //! constructs GpuMat of the specified size and type
+    GpuMat(int rows, int cols, int type, Allocator* allocator = defaultAllocator());
+    GpuMat(Size size, int type, Allocator* allocator = defaultAllocator());
+
+    //! constucts GpuMat and fills it with the specified value _s
+    GpuMat(int rows, int cols, int type, Scalar s, Allocator* allocator = defaultAllocator());
+    GpuMat(Size size, int type, Scalar s, Allocator* allocator = defaultAllocator());
+
+    //! copy constructor
+    GpuMat(const GpuMat& m);
+
+    //! constructor for GpuMat 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 GpuMat 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 host memory (Blocking call)
+    explicit GpuMat(InputArray arr, Allocator* allocator = defaultAllocator());
+
+    //! destructor - calls release()
+    ~GpuMat();
+
+    //! assignment operators
+    GpuMat& operator =(const GpuMat& m);
+
+    //! allocates new GpuMat data unless the GpuMat already has specified size and type
+    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);
+
+    //! pefroms upload data to GpuMat (Blocking call)
+    void upload(InputArray arr);
+
+    //! pefroms upload data to GpuMat (Non-Blocking call)
+    void upload(InputArray arr, Stream& stream);
+
+    //! pefroms download data from device to host memory (Blocking call)
+    void download(OutputArray dst) const;
+
+    //! pefroms download data from device to host memory (Non-Blocking call)
+    void download(OutputArray dst, Stream& stream) const;
+
+    //! returns deep copy of the GpuMat, i.e. the data is copied
+    GpuMat clone() const;
+
+    //! copies the GpuMat content to device memory (Blocking call)
+    void copyTo(OutputArray dst) const;
+
+    //! copies the GpuMat content to device memory (Non-Blocking call)
+    void copyTo(OutputArray dst, Stream& stream) const;
+
+    //! copies those GpuMat elements to "m" that are marked with non-zero mask elements (Blocking call)
+    void copyTo(OutputArray dst, InputArray mask) const;
+
+    //! copies those GpuMat elements to "m" that are marked with non-zero mask elements (Non-Blocking call)
+    void copyTo(OutputArray dst, InputArray mask, Stream& stream) const;
+
+    //! sets some of the GpuMat elements to s (Blocking call)
+    GpuMat& setTo(Scalar s);
+
+    //! sets some of the GpuMat elements to s (Non-Blocking call)
+    GpuMat& setTo(Scalar s, Stream& stream);
+
+    //! sets some of the GpuMat elements to s, according to the mask (Blocking call)
+    GpuMat& setTo(Scalar s, InputArray mask);
+
+    //! sets some of the GpuMat elements to s, according to the mask (Non-Blocking call)
+    GpuMat& setTo(Scalar s, InputArray mask, Stream& stream);
+
+    //! converts GpuMat to another datatype (Blocking call)
+    void convertTo(OutputArray dst, int rtype) const;
+
+    //! converts GpuMat to another datatype (Non-Blocking call)
+    void convertTo(OutputArray dst, int rtype, Stream& stream) const;
+
+    //! converts GpuMat to another datatype with scaling (Blocking call)
+    void convertTo(OutputArray dst, int rtype, double alpha, double beta = 0.0) const;
+
+    //! converts GpuMat to another datatype with scaling (Non-Blocking call)
+    void convertTo(OutputArray dst, int rtype, double alpha, Stream& stream) const;
+
+    //! converts GpuMat to another datatype with scaling (Non-Blocking call)
+    void convertTo(OutputArray dst, int rtype, double alpha, double beta, Stream& stream) const;
+
+    void assignTo(GpuMat& m, int type=-1) 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;
+
+    template <typename _Tp> operator PtrStepSz<_Tp>() const;
+    template <typename _Tp> operator PtrStep<_Tp>() const;
+
+    //! returns a new GpuMat header for the specified row
+    GpuMat row(int y) const;
+
+    //! returns a new GpuMat 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;
+
+    //! extracts a rectangular sub-GpuMat (this is a generalized form of row, rowRange etc.)
+    GpuMat operator ()(Range rowRange, Range colRange) const;
+    GpuMat operator ()(Rect roi) const;
+
+    //! creates alternative GpuMat header for the same data, with different
+    //! number of channels and/or different number of rows
+    GpuMat reshape(int cn, int rows = 0) const;
+
+    //! locates GpuMat header within a parent GpuMat
+    void locateROI(Size& wholeSize, Point& ofs) const;
+
+    //! moves/resizes the current GpuMat ROI inside the parent GpuMat
+    GpuMat& adjustROI(int dtop, int dbottom, int dleft, int dright);
+
+    //! returns true iff the GpuMat data is continuous
+    //! (i.e. when there are no gaps between successive rows)
+    bool isContinuous() const;
+
+    //! returns element size in bytes
+    size_t elemSize() const;
+
+    //! returns the size of element channel in bytes
+    size_t elemSize1() const;
+
+    //! returns element type
+    int type() const;
+
+    //! returns element type
+    int depth() const;
+
+    //! returns number of channels
+    int channels() const;
+
+    //! returns step/elemSize1()
+    size_t step1() const;
+
+    //! returns GpuMat size : width == number of columns, height == number of rows
+    Size size() const;
+
+    //! returns true if GpuMat data is NULL
+    bool empty() 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 GpuMat points to user-allocated data, the pointer is NULL
+    int* refcount;
+
+    //! helper fields used in locateROI and adjustROI
+    uchar* datastart;
+    const uchar* dataend;
+
+    //! allocator
+    Allocator* allocator;
+};
+
+/** @brief Creates a continuous matrix.
+
+@param rows Row count.
+@param cols Column count.
+@param type Type of the matrix.
+@param arr Destination matrix. This parameter changes only if it has a proper type and area (
+\f$\texttt{rows} \times \texttt{cols}\f$ ).
+
+Matrix is called continuous if its elements are stored continuously, that is, without gaps at the
+end of each row.
+ */
+CV_EXPORTS void createContinuous(int rows, int cols, int type, OutputArray arr);
+
+/** @brief Ensures that the size of a matrix is big enough and the matrix has a proper type.
+
+@param rows Minimum desired number of rows.
+@param cols Minimum desired number of columns.
+@param type Desired matrix type.
+@param arr Destination matrix.
+
+The function does not reallocate memory if the matrix has proper attributes already.
+ */
+CV_EXPORTS void ensureSizeIsEnough(int rows, int cols, int type, OutputArray arr);
+
+//! BufferPool management (must be called before Stream creation)
+CV_EXPORTS void setBufferPoolUsage(bool on);
+CV_EXPORTS void setBufferPoolConfig(int deviceId, size_t stackSize, int stackCount);
+
+//===================================================================================
+// HostMem
+//===================================================================================
+
+/** @brief Class with reference counting wrapping special memory type allocation functions from CUDA.
+
+Its interface is also Mat-like but with additional memory type parameters.
+
+-   **PAGE_LOCKED** sets a page locked memory type used commonly for fast and asynchronous
+    uploading/downloading data from/to GPU.
+-   **SHARED** specifies a zero copy memory allocation that enables mapping the host memory to GPU
+    address space, if supported.
+-   **WRITE_COMBINED** sets the write combined buffer that is not cached by CPU. Such buffers are
+    used to supply GPU with data when GPU only reads it. The advantage is a better CPU cache
+    utilization.
+
+@note Allocation size of such memory types is usually limited. For more details, see *CUDA 2.2
+Pinned Memory APIs* document or *CUDA C Programming Guide*.
+ */
+class CV_EXPORTS HostMem
+{
+public:
+    enum AllocType { PAGE_LOCKED = 1, SHARED = 2, WRITE_COMBINED = 4 };
+
+    static MatAllocator* getAllocator(AllocType alloc_type = PAGE_LOCKED);
+
+    explicit HostMem(AllocType alloc_type = PAGE_LOCKED);
+
+    HostMem(const HostMem& m);
+
+    HostMem(int rows, int cols, int type, AllocType alloc_type = PAGE_LOCKED);
+    HostMem(Size size, int type, AllocType alloc_type = PAGE_LOCKED);
+
+    //! creates from host memory with coping data
+    explicit HostMem(InputArray arr, AllocType alloc_type = PAGE_LOCKED);
+
+    ~HostMem();
+
+    HostMem& operator =(const HostMem& m);
+
+    //! swaps with other smart pointer
+    void swap(HostMem& b);
+
+    //! returns deep copy of the matrix, i.e. the data is copied
+    HostMem clone() const;
+
+    //! allocates new matrix data unless the matrix already has specified size and type.
+    void create(int rows, int cols, int type);
+    void create(Size size, int type);
+
+    //! creates alternative HostMem header for the same data, with different
+    //! number of channels and/or different number of rows
+    HostMem reshape(int cn, int rows = 0) const;
+
+    //! decrements reference counter and released memory if needed.
+    void release();
+
+    //! returns matrix header with disabled reference counting for HostMem data.
+    Mat createMatHeader() const;
+
+    /** @brief Maps CPU memory to GPU address space and creates the cuda::GpuMat header without reference counting
+    for it.
+
+    This can be done only if memory was allocated with the SHARED flag and if it is supported by the
+    hardware. Laptops often share video and CPU memory, so address spaces can be mapped, which
+    eliminates an extra copy.
+     */
+    GpuMat createGpuMatHeader() const;
+
+    // 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;
+    const uchar* dataend;
+
+    AllocType alloc_type;
+};
+
+/** @brief Page-locks the memory of matrix and maps it for the device(s).
+
+@param m Input matrix.
+ */
+CV_EXPORTS void registerPageLocked(Mat& m);
+
+/** @brief Unmaps the memory of matrix and makes it pageable again.
+
+@param m Input matrix.
+ */
+CV_EXPORTS void unregisterPageLocked(Mat& m);
+
+//===================================================================================
+// Stream
+//===================================================================================
+
+/** @brief This class encapsulates a queue of asynchronous calls.
+
+@note Currently, you may face problems if an operation is enqueued twice with different data. Some
+functions use the constant GPU memory, and next call may update the memory before the previous one
+has been finished. But calling different operations asynchronously is safe because each operation
+has its own constant buffer. Memory copy/upload/download/set operations to the buffers you hold are
+also safe.
+
+@note The Stream class is not thread-safe. Please use different Stream objects for different CPU threads.
+
+@code
+void thread1()
+{
+    cv::cuda::Stream stream1;
+    cv::cuda::func1(..., stream1);
+}
+
+void thread2()
+{
+    cv::cuda::Stream stream2;
+    cv::cuda::func2(..., stream2);
+}
+@endcode
+
+@note By default all CUDA routines are launched in Stream::Null() object, if the stream is not specified by user.
+In multi-threading environment the stream objects must be passed explicitly (see previous note).
+ */
+class CV_EXPORTS Stream
+{
+    typedef void (Stream::*bool_type)() const;
+    void this_type_does_not_support_comparisons() const {}
+
+public:
+    typedef void (*StreamCallback)(int status, void* userData);
+
+    //! creates a new asynchronous stream
+    Stream();
+
+    /** @brief Returns true if the current stream queue is finished. Otherwise, it returns false.
+    */
+    bool queryIfComplete() const;
+
+    /** @brief Blocks the current CPU thread until all operations in the stream are complete.
+    */
+    void waitForCompletion();
+
+    /** @brief Makes a compute stream wait on an event.
+    */
+    void waitEvent(const Event& event);
+
+    /** @brief Adds a callback to be called on the host after all currently enqueued items in the stream have
+    completed.
+
+    @note Callbacks must not make any CUDA API calls. Callbacks must not perform any synchronization
+    that may depend on outstanding device work or other callbacks that are not mandated to run earlier.
+    Callbacks without a mandated order (in independent streams) execute in undefined order and may be
+    serialized.
+     */
+    void enqueueHostCallback(StreamCallback callback, void* userData);
+
+    //! return Stream object for default CUDA stream
+    static Stream& Null();
+
+    //! returns true if stream object is not default (!= 0)
+    operator bool_type() const;
+
+    class Impl;
+
+private:
+    Ptr<Impl> impl_;
+    Stream(const Ptr<Impl>& impl);
+
+    friend struct StreamAccessor;
+    friend class BufferPool;
+    friend class DefaultDeviceInitializer;
+};
+
+class CV_EXPORTS Event
+{
+public:
+    enum CreateFlags
+    {
+        DEFAULT        = 0x00,  /**< Default event flag */
+        BLOCKING_SYNC  = 0x01,  /**< Event uses blocking synchronization */
+        DISABLE_TIMING = 0x02,  /**< Event will not record timing data */
+        INTERPROCESS   = 0x04   /**< Event is suitable for interprocess use. DisableTiming must be set */
+    };
+
+    explicit Event(CreateFlags flags = DEFAULT);
+
+    //! records an event
+    void record(Stream& stream = Stream::Null());
+
+    //! queries an event's status
+    bool queryIfComplete() const;
+
+    //! waits for an event to complete
+    void waitForCompletion();
+
+    //! computes the elapsed time between events
+    static float elapsedTime(const Event& start, const Event& end);
+
+    class Impl;
+
+private:
+    Ptr<Impl> impl_;
+    Event(const Ptr<Impl>& impl);
+
+    friend struct EventAccessor;
+};
+
+//! @} cudacore_struct
+
+//===================================================================================
+// Initialization & Info
+//===================================================================================
+
+//! @addtogroup cudacore_init
+//! @{
+
+/** @brief Returns the number of installed CUDA-enabled devices.
+
+Use this function before any other CUDA functions calls. If OpenCV is compiled without CUDA support,
+this function returns 0.
+ */
+CV_EXPORTS int getCudaEnabledDeviceCount();
+
+/** @brief Sets a device and initializes it for the current thread.
+
+@param device System index of a CUDA device starting with 0.
+
+If the call of this function is omitted, a default device is initialized at the fist CUDA usage.
+ */
+CV_EXPORTS void setDevice(int device);
+
+/** @brief Returns the current device index set by cuda::setDevice or initialized by default.
+ */
+CV_EXPORTS int getDevice();
+
+/** @brief 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();
+
+/** @brief Enumeration providing CUDA computing features.
+ */
+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_32 = 32,
+    FEATURE_SET_COMPUTE_35 = 35,
+    FEATURE_SET_COMPUTE_50 = 50,
+
+    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);
+
+/** @brief Class providing a set of static methods to check what NVIDIA\* card architecture the CUDA module was
+built for.
+
+According to the CUDA C Programming Guide Version 3.2: "PTX code produced for some specific compute
+capability can always be compiled to binary code of greater or equal compute capability".
+ */
+class CV_EXPORTS TargetArchs
+{
+public:
+    /** @brief The following method checks whether the module was built with the support of the given feature:
+
+    @param feature_set Features to be checked. See :ocvcuda::FeatureSet.
+     */
+    static bool builtWith(FeatureSet feature_set);
+
+    /** @brief There is a set of methods to check whether the module contains intermediate (PTX) or binary CUDA
+    code for the given architecture(s):
+
+    @param major Major compute capability version.
+    @param minor Minor compute capability version.
+     */
+    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);
+};
+
+/** @brief Class providing functionality for querying the specified GPU properties.
+ */
+class CV_EXPORTS DeviceInfo
+{
+public:
+    //! creates DeviceInfo object for the current GPU
+    DeviceInfo();
+
+    /** @brief The constructors.
+
+    @param device_id System index of the CUDA device starting with 0.
+
+    Constructs the DeviceInfo object for the specified device. If device_id parameter is missed, it
+    constructs an object for the current device.
+     */
+    DeviceInfo(int device_id);
+
+    /** @brief Returns system index of the CUDA device starting with 0.
+    */
+    int deviceID() const;
+
+    //! ASCII string identifying device
+    const char* name() const;
+
+    //! global memory available on device in bytes
+    size_t totalGlobalMem() const;
+
+    //! shared memory available per block in bytes
+    size_t sharedMemPerBlock() const;
+
+    //! 32-bit registers available per block
+    int regsPerBlock() const;
+
+    //! warp size in threads
+    int warpSize() const;
+
+    //! maximum pitch in bytes allowed by memory copies
+    size_t memPitch() const;
+
+    //! maximum number of threads per block
+    int maxThreadsPerBlock() const;
+
+    //! maximum size of each dimension of a block
+    Vec3i maxThreadsDim() const;
+
+    //! maximum size of each dimension of a grid
+    Vec3i maxGridSize() const;
+
+    //! clock frequency in kilohertz
+    int clockRate() const;
+
+    //! constant memory available on device in bytes
+    size_t totalConstMem() const;
+
+    //! major compute capability
+    int majorVersion() const;
+
+    //! minor compute capability
+    int minorVersion() const;
+
+    //! alignment requirement for textures
+    size_t textureAlignment() const;
+
+    //! pitch alignment requirement for texture references bound to pitched memory
+    size_t texturePitchAlignment() const;
+
+    //! number of multiprocessors on device
+    int multiProcessorCount() const;
+
+    //! specified whether there is a run time limit on kernels
+    bool kernelExecTimeoutEnabled() const;
+
+    //! device is integrated as opposed to discrete
+    bool integrated() const;
+
+    //! device can map host memory with cudaHostAlloc/cudaHostGetDevicePointer
+    bool canMapHostMemory() const;
+
+    enum ComputeMode
+    {
+        ComputeModeDefault,         /**< default compute mode (Multiple threads can use cudaSetDevice with this device) */
+        ComputeModeExclusive,       /**< compute-exclusive-thread mode (Only one thread in one process will be able to use cudaSetDevice with this device) */
+        ComputeModeProhibited,      /**< compute-prohibited mode (No threads can use cudaSetDevice with this device) */
+        ComputeModeExclusiveProcess /**< compute-exclusive-process mode (Many threads in one process will be able to use cudaSetDevice with this device) */
+    };
+
+    //! compute mode
+    ComputeMode computeMode() const;
+
+    //! maximum 1D texture size
+    int maxTexture1D() const;
+
+    //! maximum 1D mipmapped texture size
+    int maxTexture1DMipmap() const;
+
+    //! maximum size for 1D textures bound to linear memory
+    int maxTexture1DLinear() const;
+
+    //! maximum 2D texture dimensions
+    Vec2i maxTexture2D() const;
+
+    //! maximum 2D mipmapped texture dimensions
+    Vec2i maxTexture2DMipmap() const;
+
+    //! maximum dimensions (width, height, pitch) for 2D textures bound to pitched memory
+    Vec3i maxTexture2DLinear() const;
+
+    //! maximum 2D texture dimensions if texture gather operations have to be performed
+    Vec2i maxTexture2DGather() const;
+
+    //! maximum 3D texture dimensions
+    Vec3i maxTexture3D() const;
+
+    //! maximum Cubemap texture dimensions
+    int maxTextureCubemap() const;
+
+    //! maximum 1D layered texture dimensions
+    Vec2i maxTexture1DLayered() const;
+
+    //! maximum 2D layered texture dimensions
+    Vec3i maxTexture2DLayered() const;
+
+    //! maximum Cubemap layered texture dimensions
+    Vec2i maxTextureCubemapLayered() const;
+
+    //! maximum 1D surface size
+    int maxSurface1D() const;
+
+    //! maximum 2D surface dimensions
+    Vec2i maxSurface2D() const;
+
+    //! maximum 3D surface dimensions
+    Vec3i maxSurface3D() const;
+
+    //! maximum 1D layered surface dimensions
+    Vec2i maxSurface1DLayered() const;
+
+    //! maximum 2D layered surface dimensions
+    Vec3i maxSurface2DLayered() const;
+
+    //! maximum Cubemap surface dimensions
+    int maxSurfaceCubemap() const;
+
+    //! maximum Cubemap layered surface dimensions
+    Vec2i maxSurfaceCubemapLayered() const;
+
+    //! alignment requirements for surfaces
+    size_t surfaceAlignment() const;
+
+    //! device can possibly execute multiple kernels concurrently
+    bool concurrentKernels() const;
+
+    //! device has ECC support enabled
+    bool ECCEnabled() const;
+
+    //! PCI bus ID of the device
+    int pciBusID() const;
+
+    //! PCI device ID of the device
+    int pciDeviceID() const;
+
+    //! PCI domain ID of the device
+    int pciDomainID() const;
+
+    //! true if device is a Tesla device using TCC driver, false otherwise
+    bool tccDriver() const;
+
+    //! number of asynchronous engines
+    int asyncEngineCount() const;
+
+    //! device shares a unified address space with the host
+    bool unifiedAddressing() const;
+
+    //! peak memory clock frequency in kilohertz
+    int memoryClockRate() const;
+
+    //! global memory bus width in bits
+    int memoryBusWidth() const;
+
+    //! size of L2 cache in bytes
+    int l2CacheSize() const;
+
+    //! maximum resident threads per multiprocessor
+    int maxThreadsPerMultiProcessor() const;
+
+    //! gets free and total device memory
+    void queryMemory(size_t& totalMemory, size_t& freeMemory) const;
+    size_t freeMemory() const;
+    size_t totalMemory() const;
+
+    /** @brief Provides information on CUDA feature support.
+
+    @param feature_set Features to be checked. See cuda::FeatureSet.
+
+    This function returns true if the device has the specified CUDA feature. Otherwise, it returns false
+     */
+    bool supports(FeatureSet feature_set) const;
+
+    /** @brief Checks the CUDA module and device compatibility.
+
+    This function returns true if the CUDA module can be run on the specified device. Otherwise, it
+    returns false .
+     */
+    bool isCompatible() const;
+
+private:
+    int device_id_;
+};
+
+CV_EXPORTS void printCudaDeviceInfo(int device);
+CV_EXPORTS void printShortCudaDeviceInfo(int device);
+
+/** @brief Converts an array to half precision floating number.
+
+@param _src input array.
+@param _dst output array.
+@param stream Stream for the asynchronous version.
+@sa convertFp16
+*/
+CV_EXPORTS void convertFp16(InputArray _src, OutputArray _dst, Stream& stream = Stream::Null());
+
+//! @} cudacore_init
+
+}} // namespace cv { namespace cuda {
+
+
+#include "opencv2/core/cuda.inl.hpp"
+
+#endif /* OPENCV_CORE_CUDA_HPP */