openCV library for Renesas RZ/A

Dependents:   RZ_A2M_Mbed_samples

include/opencv2/core/ocl.hpp

Committer:
RyoheiHagimoto
Date:
2021-01-29
Revision:
0:0e0631af0305

File content as of revision 0:0e0631af0305:

/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
//  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) 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.
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//   * The name of the copyright holders may not be used to endorse or promote products
//     derived from this software without specific prior written permission.
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// This software is provided by the copyright holders and contributors "as is" and
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// loss of use, data, or profits; or business interruption) however caused
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//M*/

#ifndef OPENCV_OPENCL_HPP
#define OPENCV_OPENCL_HPP

#include "opencv2/core.hpp"

namespace cv { namespace ocl {

//! @addtogroup core_opencl
//! @{

CV_EXPORTS_W bool haveOpenCL();
CV_EXPORTS_W bool useOpenCL();
CV_EXPORTS_W bool haveAmdBlas();
CV_EXPORTS_W bool haveAmdFft();
CV_EXPORTS_W void setUseOpenCL(bool flag);
CV_EXPORTS_W void finish();

CV_EXPORTS bool haveSVM();

class CV_EXPORTS Context;
class CV_EXPORTS Device;
class CV_EXPORTS Kernel;
class CV_EXPORTS Program;
class CV_EXPORTS ProgramSource;
class CV_EXPORTS Queue;
class CV_EXPORTS PlatformInfo;
class CV_EXPORTS Image2D;

class CV_EXPORTS Device
{
public:
    Device();
    explicit Device(void* d);
    Device(const Device& d);
    Device& operator = (const Device& d);
    ~Device();

    void set(void* d);

    enum
    {
        TYPE_DEFAULT     = (1 << 0),
        TYPE_CPU         = (1 << 1),
        TYPE_GPU         = (1 << 2),
        TYPE_ACCELERATOR = (1 << 3),
        TYPE_DGPU        = TYPE_GPU + (1 << 16),
        TYPE_IGPU        = TYPE_GPU + (1 << 17),
        TYPE_ALL         = 0xFFFFFFFF
    };

    String name() const;
    String extensions() const;
    String version() const;
    String vendorName() const;
    String OpenCL_C_Version() const;
    String OpenCLVersion() const;
    int deviceVersionMajor() const;
    int deviceVersionMinor() const;
    String driverVersion() const;
    void* ptr() const;

    int type() const;

    int addressBits() const;
    bool available() const;
    bool compilerAvailable() const;
    bool linkerAvailable() const;

    enum
    {
        FP_DENORM=(1 << 0),
        FP_INF_NAN=(1 << 1),
        FP_ROUND_TO_NEAREST=(1 << 2),
        FP_ROUND_TO_ZERO=(1 << 3),
        FP_ROUND_TO_INF=(1 << 4),
        FP_FMA=(1 << 5),
        FP_SOFT_FLOAT=(1 << 6),
        FP_CORRECTLY_ROUNDED_DIVIDE_SQRT=(1 << 7)
    };
    int doubleFPConfig() const;
    int singleFPConfig() const;
    int halfFPConfig() const;

    bool endianLittle() const;
    bool errorCorrectionSupport() const;

    enum
    {
        EXEC_KERNEL=(1 << 0),
        EXEC_NATIVE_KERNEL=(1 << 1)
    };
    int executionCapabilities() const;

    size_t globalMemCacheSize() const;

    enum
    {
        NO_CACHE=0,
        READ_ONLY_CACHE=1,
        READ_WRITE_CACHE=2
    };
    int globalMemCacheType() const;
    int globalMemCacheLineSize() const;
    size_t globalMemSize() const;

    size_t localMemSize() const;
    enum
    {
        NO_LOCAL_MEM=0,
        LOCAL_IS_LOCAL=1,
        LOCAL_IS_GLOBAL=2
    };
    int localMemType() const;
    bool hostUnifiedMemory() const;

    bool imageSupport() const;

    bool imageFromBufferSupport() const;
    uint imagePitchAlignment() const;
    uint imageBaseAddressAlignment() const;

    size_t image2DMaxWidth() const;
    size_t image2DMaxHeight() const;

    size_t image3DMaxWidth() const;
    size_t image3DMaxHeight() const;
    size_t image3DMaxDepth() const;

    size_t imageMaxBufferSize() const;
    size_t imageMaxArraySize() const;

    enum
    {
        UNKNOWN_VENDOR=0,
        VENDOR_AMD=1,
        VENDOR_INTEL=2,
        VENDOR_NVIDIA=3
    };
    int vendorID() const;
    // FIXIT
    // dev.isAMD() doesn't work for OpenCL CPU devices from AMD OpenCL platform.
    // This method should use platform name instead of vendor name.
    // After fix restore code in arithm.cpp: ocl_compare()
    inline bool isAMD() const { return vendorID() == VENDOR_AMD; }
    inline bool isIntel() const { return vendorID() == VENDOR_INTEL; }
    inline bool isNVidia() const { return vendorID() == VENDOR_NVIDIA; }

    int maxClockFrequency() const;
    int maxComputeUnits() const;
    int maxConstantArgs() const;
    size_t maxConstantBufferSize() const;

    size_t maxMemAllocSize() const;
    size_t maxParameterSize() const;

    int maxReadImageArgs() const;
    int maxWriteImageArgs() const;
    int maxSamplers() const;

    size_t maxWorkGroupSize() const;
    int maxWorkItemDims() const;
    void maxWorkItemSizes(size_t*) const;

    int memBaseAddrAlign() const;

    int nativeVectorWidthChar() const;
    int nativeVectorWidthShort() const;
    int nativeVectorWidthInt() const;
    int nativeVectorWidthLong() const;
    int nativeVectorWidthFloat() const;
    int nativeVectorWidthDouble() const;
    int nativeVectorWidthHalf() const;

    int preferredVectorWidthChar() const;
    int preferredVectorWidthShort() const;
    int preferredVectorWidthInt() const;
    int preferredVectorWidthLong() const;
    int preferredVectorWidthFloat() const;
    int preferredVectorWidthDouble() const;
    int preferredVectorWidthHalf() const;

    size_t printfBufferSize() const;
    size_t profilingTimerResolution() const;

    static const Device& getDefault();

protected:
    struct Impl;
    Impl* p;
};


class CV_EXPORTS Context
{
public:
    Context();
    explicit Context(int dtype);
    ~Context();
    Context(const Context& c);
    Context& operator = (const Context& c);

    bool create();
    bool create(int dtype);
    size_t ndevices() const;
    const Device& device(size_t idx) const;
    Program getProg(const ProgramSource& prog,
                    const String& buildopt, String& errmsg);

    static Context& getDefault(bool initialize = true);
    void* ptr() const;

    friend void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device);

    bool useSVM() const;
    void setUseSVM(bool enabled);

    struct Impl;
    Impl* p;
};

class CV_EXPORTS Platform
{
public:
    Platform();
    ~Platform();
    Platform(const Platform& p);
    Platform& operator = (const Platform& p);

    void* ptr() const;
    static Platform& getDefault();

    friend void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device);
protected:
    struct Impl;
    Impl* p;
};

/*
//! @brief Attaches OpenCL context to OpenCV
//
//! @note Note:
//    OpenCV will check if available OpenCL platform has platformName name,
//    then assign context to OpenCV and call clRetainContext function.
//    The deviceID device will be used as target device and new command queue
//    will be created.
//
// Params:
//! @param platformName - name of OpenCL platform to attach,
//!                       this string is used to check if platform is available
//!                       to OpenCV at runtime
//! @param platfromID   - ID of platform attached context was created for
//! @param context      - OpenCL context to be attached to OpenCV
//! @param deviceID     - ID of device, must be created from attached context
*/
CV_EXPORTS void attachContext(const String& platformName, void* platformID, void* context, void* deviceID);

/*
//! @brief Convert OpenCL buffer to UMat
//
//! @note Note:
//   OpenCL buffer (cl_mem_buffer) should contain 2D image data, compatible with OpenCV.
//   Memory content is not copied from clBuffer to UMat. Instead, buffer handle assigned
//   to UMat and clRetainMemObject is called.
//
// Params:
//! @param  cl_mem_buffer - source clBuffer handle
//! @param  step          - num of bytes in single row
//! @param  rows          - number of rows
//! @param  cols          - number of cols
//! @param  type          - OpenCV type of image
//! @param  dst           - destination UMat
*/
CV_EXPORTS void convertFromBuffer(void* cl_mem_buffer, size_t step, int rows, int cols, int type, UMat& dst);

/*
//! @brief Convert OpenCL image2d_t to UMat
//
//! @note Note:
//   OpenCL image2d_t (cl_mem_image), should be compatible with OpenCV
//   UMat formats.
//   Memory content is copied from image to UMat with
//   clEnqueueCopyImageToBuffer function.
//
// Params:
//! @param  cl_mem_image - source image2d_t handle
//! @param  dst          - destination UMat
*/
CV_EXPORTS void convertFromImage(void* cl_mem_image, UMat& dst);

// TODO Move to internal header
void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device);

class CV_EXPORTS Queue
{
public:
    Queue();
    explicit Queue(const Context& c, const Device& d=Device());
    ~Queue();
    Queue(const Queue& q);
    Queue& operator = (const Queue& q);

    bool create(const Context& c=Context(), const Device& d=Device());
    void finish();
    void* ptr() const;
    static Queue& getDefault();

protected:
    struct Impl;
    Impl* p;
};


class CV_EXPORTS KernelArg
{
public:
    enum { LOCAL=1, READ_ONLY=2, WRITE_ONLY=4, READ_WRITE=6, CONSTANT=8, PTR_ONLY = 16, NO_SIZE=256 };
    KernelArg(int _flags, UMat* _m, int wscale=1, int iwscale=1, const void* _obj=0, size_t _sz=0);
    KernelArg();

    static KernelArg Local() { return KernelArg(LOCAL, 0); }
    static KernelArg PtrWriteOnly(const UMat& m)
    { return KernelArg(PTR_ONLY+WRITE_ONLY, (UMat*)&m); }
    static KernelArg PtrReadOnly(const UMat& m)
    { return KernelArg(PTR_ONLY+READ_ONLY, (UMat*)&m); }
    static KernelArg PtrReadWrite(const UMat& m)
    { return KernelArg(PTR_ONLY+READ_WRITE, (UMat*)&m); }
    static KernelArg ReadWrite(const UMat& m, int wscale=1, int iwscale=1)
    { return KernelArg(READ_WRITE, (UMat*)&m, wscale, iwscale); }
    static KernelArg ReadWriteNoSize(const UMat& m, int wscale=1, int iwscale=1)
    { return KernelArg(READ_WRITE+NO_SIZE, (UMat*)&m, wscale, iwscale); }
    static KernelArg ReadOnly(const UMat& m, int wscale=1, int iwscale=1)
    { return KernelArg(READ_ONLY, (UMat*)&m, wscale, iwscale); }
    static KernelArg WriteOnly(const UMat& m, int wscale=1, int iwscale=1)
    { return KernelArg(WRITE_ONLY, (UMat*)&m, wscale, iwscale); }
    static KernelArg ReadOnlyNoSize(const UMat& m, int wscale=1, int iwscale=1)
    { return KernelArg(READ_ONLY+NO_SIZE, (UMat*)&m, wscale, iwscale); }
    static KernelArg WriteOnlyNoSize(const UMat& m, int wscale=1, int iwscale=1)
    { return KernelArg(WRITE_ONLY+NO_SIZE, (UMat*)&m, wscale, iwscale); }
    static KernelArg Constant(const Mat& m);
    template<typename _Tp> static KernelArg Constant(const _Tp* arr, size_t n)
    { return KernelArg(CONSTANT, 0, 1, 1, (void*)arr, n); }

    int flags;
    UMat* m;
    const void* obj;
    size_t sz;
    int wscale, iwscale;
};


class CV_EXPORTS Kernel
{
public:
    Kernel();
    Kernel(const char* kname, const Program& prog);
    Kernel(const char* kname, const ProgramSource& prog,
           const String& buildopts = String(), String* errmsg=0);
    ~Kernel();
    Kernel(const Kernel& k);
    Kernel& operator = (const Kernel& k);

    bool empty() const;
    bool create(const char* kname, const Program& prog);
    bool create(const char* kname, const ProgramSource& prog,
                const String& buildopts, String* errmsg=0);

    int set(int i, const void* value, size_t sz);
    int set(int i, const Image2D& image2D);
    int set(int i, const UMat& m);
    int set(int i, const KernelArg& arg);
    template<typename _Tp> int set(int i, const _Tp& value)
    { return set(i, &value, sizeof(value)); }

    template<typename _Tp0>
    Kernel& args(const _Tp0& a0)
    {
        set(0, a0); return *this;
    }

    template<typename _Tp0, typename _Tp1>
    Kernel& args(const _Tp0& a0, const _Tp1& a1)
    {
        int i = set(0, a0); set(i, a1); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2)
    {
        int i = set(0, a0); i = set(i, a1); set(i, a2); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3, typename _Tp4>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2,
                 const _Tp3& a3, const _Tp4& a4)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2);
        i = set(i, a3); set(i, a4); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2,
             typename _Tp3, typename _Tp4, typename _Tp5>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2,
                 const _Tp3& a3, const _Tp4& a4, const _Tp5& a5)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2);
        i = set(i, a3); i = set(i, a4); set(i, a5); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
             typename _Tp4, typename _Tp5, typename _Tp6>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3);
        i = set(i, a4); i = set(i, a5); set(i, a6); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
             typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3);
        i = set(i, a4); i = set(i, a5); i = set(i, a6); set(i, a7); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3, typename _Tp4,
             typename _Tp5, typename _Tp6, typename _Tp7, typename _Tp8>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
                 const _Tp8& a8)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4);
        i = set(i, a5); i = set(i, a6); i = set(i, a7); set(i, a8); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3, typename _Tp4,
             typename _Tp5, typename _Tp6, typename _Tp7, typename _Tp8, typename _Tp9>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
                 const _Tp8& a8, const _Tp9& a9)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
        i = set(i, a6); i = set(i, a7); i = set(i, a8); set(i, a9); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
             typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
             typename _Tp8, typename _Tp9, typename _Tp10>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
                 const _Tp8& a8, const _Tp9& a9, const _Tp10& a10)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
        i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); set(i, a10); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
             typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
             typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
                 const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
        i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); set(i, a11); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
             typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
             typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11, typename _Tp12>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
                 const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11,
                 const _Tp12& a12)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
        i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11);
        set(i, a12); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
             typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
             typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11, typename _Tp12,
             typename _Tp13>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
                 const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11,
                 const _Tp12& a12, const _Tp13& a13)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
        i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11);
        i = set(i, a12); set(i, a13); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
             typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
             typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11, typename _Tp12,
             typename _Tp13, typename _Tp14>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
                 const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11,
                 const _Tp12& a12, const _Tp13& a13, const _Tp14& a14)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
        i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11);
        i = set(i, a12); i = set(i, a13); set(i, a14); return *this;
    }

    template<typename _Tp0, typename _Tp1, typename _Tp2, typename _Tp3,
             typename _Tp4, typename _Tp5, typename _Tp6, typename _Tp7,
             typename _Tp8, typename _Tp9, typename _Tp10, typename _Tp11, typename _Tp12,
             typename _Tp13, typename _Tp14, typename _Tp15>
    Kernel& args(const _Tp0& a0, const _Tp1& a1, const _Tp2& a2, const _Tp3& a3,
                 const _Tp4& a4, const _Tp5& a5, const _Tp6& a6, const _Tp7& a7,
                 const _Tp8& a8, const _Tp9& a9, const _Tp10& a10, const _Tp11& a11,
                 const _Tp12& a12, const _Tp13& a13, const _Tp14& a14, const _Tp15& a15)
    {
        int i = set(0, a0); i = set(i, a1); i = set(i, a2); i = set(i, a3); i = set(i, a4); i = set(i, a5);
        i = set(i, a6); i = set(i, a7); i = set(i, a8); i = set(i, a9); i = set(i, a10); i = set(i, a11);
        i = set(i, a12); i = set(i, a13); i = set(i, a14); set(i, a15); return *this;
    }
    /*
    Run the OpenCL kernel.
    @param dims the work problem dimensions. It is the length of globalsize and localsize. It can be either 1, 2 or 3.
    @param globalsize work items for each dimension.
    It is not the final globalsize passed to OpenCL.
    Each dimension will be adjusted to the nearest integer divisible by the corresponding value in localsize.
    If localsize is NULL, it will still be adjusted depending on dims.
    The adjusted values are greater than or equal to the original values.
    @param localsize work-group size for each dimension.
    @param sync specify whether to wait for OpenCL computation to finish before return.
    @param q command queue
    */
    bool run(int dims, size_t globalsize[],
             size_t localsize[], bool sync, const Queue& q=Queue());
    bool runTask(bool sync, const Queue& q=Queue());

    size_t workGroupSize() const;
    size_t preferedWorkGroupSizeMultiple() const;
    bool compileWorkGroupSize(size_t wsz[]) const;
    size_t localMemSize() const;

    void* ptr() const;
    struct Impl;

protected:
    Impl* p;
};

class CV_EXPORTS Program
{
public:
    Program();
    Program(const ProgramSource& src,
            const String& buildflags, String& errmsg);
    explicit Program(const String& buf);
    Program(const Program& prog);

    Program& operator = (const Program& prog);
    ~Program();

    bool create(const ProgramSource& src,
                const String& buildflags, String& errmsg);
    bool read(const String& buf, const String& buildflags);
    bool write(String& buf) const;

    const ProgramSource& source() const;
    void* ptr() const;

    String getPrefix() const;
    static String getPrefix(const String& buildflags);

protected:
    struct Impl;
    Impl* p;
};


class CV_EXPORTS ProgramSource
{
public:
    typedef uint64 hash_t;

    ProgramSource();
    explicit ProgramSource(const String& prog);
    explicit ProgramSource(const char* prog);
    ~ProgramSource();
    ProgramSource(const ProgramSource& prog);
    ProgramSource& operator = (const ProgramSource& prog);

    const String& source() const;
    hash_t hash() const;

protected:
    struct Impl;
    Impl* p;
};

class CV_EXPORTS PlatformInfo
{
public:
    PlatformInfo();
    explicit PlatformInfo(void* id);
    ~PlatformInfo();

    PlatformInfo(const PlatformInfo& i);
    PlatformInfo& operator =(const PlatformInfo& i);

    String name() const;
    String vendor() const;
    String version() const;
    int deviceNumber() const;
    void getDevice(Device& device, int d) const;

protected:
    struct Impl;
    Impl* p;
};

CV_EXPORTS const char* convertTypeStr(int sdepth, int ddepth, int cn, char* buf);
CV_EXPORTS const char* typeToStr(int t);
CV_EXPORTS const char* memopTypeToStr(int t);
CV_EXPORTS const char* vecopTypeToStr(int t);
CV_EXPORTS String kernelToStr(InputArray _kernel, int ddepth = -1, const char * name = NULL);
CV_EXPORTS void getPlatfomsInfo(std::vector<PlatformInfo>& platform_info);


enum OclVectorStrategy
{
    // all matrices have its own vector width
    OCL_VECTOR_OWN = 0,
    // all matrices have maximal vector width among all matrices
    // (useful for cases when matrices have different data types)
    OCL_VECTOR_MAX = 1,

    // default strategy
    OCL_VECTOR_DEFAULT = OCL_VECTOR_OWN
};

CV_EXPORTS int predictOptimalVectorWidth(InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
                                         InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
                                         InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray(),
                                         OclVectorStrategy strat = OCL_VECTOR_DEFAULT);

CV_EXPORTS int checkOptimalVectorWidth(const int *vectorWidths,
                                       InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
                                       InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
                                       InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray(),
                                       OclVectorStrategy strat = OCL_VECTOR_DEFAULT);

// with OCL_VECTOR_MAX strategy
CV_EXPORTS int predictOptimalVectorWidthMax(InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
                                            InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
                                            InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray());

CV_EXPORTS void buildOptionsAddMatrixDescription(String& buildOptions, const String& name, InputArray _m);

class CV_EXPORTS Image2D
{
public:
    Image2D();

    // src:     The UMat from which to get image properties and data
    // norm:    Flag to enable the use of normalized channel data types
    // alias:   Flag indicating that the image should alias the src UMat.
    //          If true, changes to the image or src will be reflected in
    //          both objects.
    explicit Image2D(const UMat &src, bool norm = false, bool alias = false);
    Image2D(const Image2D & i);
    ~Image2D();

    Image2D & operator = (const Image2D & i);

    // Indicates if creating an aliased image should succeed.  Depends on the
    // underlying platform and the dimensions of the UMat.
    static bool canCreateAlias(const UMat &u);

    // Indicates if the image format is supported.
    static bool isFormatSupported(int depth, int cn, bool norm);

    void* ptr() const;
protected:
    struct Impl;
    Impl* p;
};


CV_EXPORTS MatAllocator* getOpenCLAllocator();


#ifdef __OPENCV_BUILD
namespace internal {

CV_EXPORTS bool isOpenCLForced();
#define OCL_FORCE_CHECK(condition) (cv::ocl::internal::isOpenCLForced() || (condition))

CV_EXPORTS bool isPerformanceCheckBypassed();
#define OCL_PERFORMANCE_CHECK(condition) (cv::ocl::internal::isPerformanceCheckBypassed() || (condition))

CV_EXPORTS bool isCLBuffer(UMat& u);

} // namespace internal
#endif

//! @}

}}

#endif