Hu Chunming / vpt_ascend

/*M///////////////////////////////////////////////////////////////////////////////////////
//
//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
//  By downloading, copying, installing or using the software you agree to this license.
//  If you do not agree to this license, do not download, install,
//  copy or use the software.
//
//
//                           License Agreement
//                For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
//   * Redistribution's of source code must retain the above copyright notice,
//     this list of conditions and the following disclaimer.
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//   * 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.
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// 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
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
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//M*/

#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__

#ifdef BUILD_PLUGIN
#include "opencv2/core/utility.hpp"
#else  // BUILD_PLUGIN

#include "opencv2/opencv_modules.hpp"
#include "cvconfig.h"

#include "opencv2/core/utility.hpp"
#include "opencv2/core/core_c.h"
#include "opencv2/core/cuda.hpp"
#include "opencv2/core/opengl.hpp"
#include "opencv2/core/va_intel.hpp"

#include "opencv2/core/private.hpp"
#include "opencv2/core/private.cuda.hpp"
#ifdef HAVE_OPENCL
#include "opencv2/core/ocl.hpp"
#endif

#include <assert.h>
#include <ctype.h>
#include <float.h>
#include <limits.h>
#include <math.h>
#include <stdarg.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>

#include <algorithm>
#include <cmath>
#include <cstdlib>
#include <limits>
#include <float.h>
#include <cstring>
#include <cassert>

#define USE_SSE2  (cv::checkHardwareSupport(CV_CPU_SSE2))
#define USE_SSE4_2  (cv::checkHardwareSupport(CV_CPU_SSE4_2))
#define USE_AVX  (cv::checkHardwareSupport(CV_CPU_AVX))
#define USE_AVX2  (cv::checkHardwareSupport(CV_CPU_AVX2))

#include "opencv2/core/hal/hal.hpp"
#include "opencv2/core/hal/intrin.hpp"
#include "opencv2/core/sse_utils.hpp"
#include "opencv2/core/neon_utils.hpp"
#include "opencv2/core/vsx_utils.hpp"
#include "hal_replacement.hpp"

#define GET_OPTIMIZED(func) (func)

namespace cv
{

// -128.f ... 255.f
extern const float g_8x32fTab[];
#define CV_8TO32F(x)  cv::g_8x32fTab[(x)+128]

extern const ushort g_8x16uSqrTab[];
#define CV_SQR_8U(x)  cv::g_8x16uSqrTab[(x)+255]

extern const uchar g_Saturate8u[];
#define CV_FAST_CAST_8U(t)   (assert(-256 <= (t) && (t) <= 512), cv::g_Saturate8u[(t)+256])
#define CV_MIN_8U(a,b)       ((a) - CV_FAST_CAST_8U((a) - (b)))
#define CV_MAX_8U(a,b)       ((a) + CV_FAST_CAST_8U((b) - (a)))

template<typename T1, typename T2=T1, typename T3=T1> struct OpAdd
{
    typedef T1 type1;
    typedef T2 type2;
    typedef T3 rtype;
    T3 operator ()(const T1 a, const T2 b) const { return saturate_cast<T3>(a + b); }
};

template<typename T1, typename T2=T1, typename T3=T1> struct OpSub
{
    typedef T1 type1;
    typedef T2 type2;
    typedef T3 rtype;
    T3 operator ()(const T1 a, const T2 b) const { return saturate_cast<T3>(a - b); }
};

template<typename T1, typename T2=T1, typename T3=T1> struct OpRSub
{
    typedef T1 type1;
    typedef T2 type2;
    typedef T3 rtype;
    T3 operator ()(const T1 a, const T2 b) const { return saturate_cast<T3>(b - a); }
};

template<typename T> struct OpMin
{
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator ()(const T a, const T b) const { return std::min(a, b); }
};

template<typename T> struct OpMax
{
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator ()(const T a, const T b) const { return std::max(a, b); }
};

template<typename T> struct OpAbsDiff
{
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()(T a, T b) const { return a > b ? a - b : b - a; }
};

// specializations to prevent "-0" results
template<> struct OpAbsDiff<float>
{
    typedef float type1;
    typedef float type2;
    typedef float rtype;
    float operator()(float a, float b) const { return std::abs(a - b); }
};
template<> struct OpAbsDiff<double>
{
    typedef double type1;
    typedef double type2;
    typedef double rtype;
    double operator()(double a, double b) const { return std::abs(a - b); }
};

template<typename T> struct OpAnd
{
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T b ) const { return a & b; }
};

template<typename T> struct OpOr
{
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T b ) const { return a | b; }
};

template<typename T> struct OpXor
{
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T b ) const { return a ^ b; }
};

template<typename T> struct OpNot
{
    typedef T type1;
    typedef T type2;
    typedef T rtype;
    T operator()( T a, T ) const { return ~a; }
};

template<> inline uchar OpAdd<uchar>::operator ()(uchar a, uchar b) const
{ return CV_FAST_CAST_8U(a + b); }

template<> inline uchar OpSub<uchar>::operator ()(uchar a, uchar b) const
{ return CV_FAST_CAST_8U(a - b); }

template<> inline short OpAbsDiff<short>::operator ()(short a, short b) const
{ return saturate_cast<short>(std::abs(a - b)); }

template<> inline schar OpAbsDiff<schar>::operator ()(schar a, schar b) const
{ return saturate_cast<schar>(std::abs(a - b)); }

template<> inline uchar OpMin<uchar>::operator ()(uchar a, uchar b) const { return CV_MIN_8U(a, b); }

template<> inline uchar OpMax<uchar>::operator ()(uchar a, uchar b) const { return CV_MAX_8U(a, b); }

typedef void (*UnaryFunc)(const uchar* src1, size_t step1,
                       uchar* dst, size_t step, Size sz,
                       void*);

typedef void (*BinaryFunc)(const uchar* src1, size_t step1,
                       const uchar* src2, size_t step2,
                       uchar* dst, size_t step, Size sz,
                       void*);

typedef void (*BinaryFuncC)(const uchar* src1, size_t step1,
                       const uchar* src2, size_t step2,
                       uchar* dst, size_t step, int width, int height,
                       void*);

BinaryFunc getConvertFunc(int sdepth, int ddepth);
BinaryFunc getConvertScaleFunc(int sdepth, int ddepth);
BinaryFunc getCopyMaskFunc(size_t esz);

/* default memory block for sparse array elements */
#define  CV_SPARSE_MAT_BLOCK     (1<<12)

/* initial hash table size */
#define  CV_SPARSE_HASH_SIZE0    (1<<10)

/* maximal average node_count/hash_size ratio beyond which hash table is resized */
#define  CV_SPARSE_HASH_RATIO    3

// There is some mess in code with vectors representation.
// Both vector-column / vector-rows are used with dims=2 (as Mat2D always).
// Reshape matrices if necessary (in case of vectors) and returns size with scaled width.
Size getContinuousSize2D(Mat& m1, int widthScale=1);
Size getContinuousSize2D(Mat& m1, Mat& m2, int widthScale=1);
Size getContinuousSize2D(Mat& m1, Mat& m2, Mat& m3, int widthScale=1);

void setSize( Mat& m, int _dims, const int* _sz, const size_t* _steps, bool autoSteps=false );
void finalizeHdr(Mat& m);
int updateContinuityFlag(int flags, int dims, const int* size, const size_t* step);

struct NoVec
{
    size_t operator()(const void*, const void*, void*, size_t) const { return 0; }
};

#define CV_SPLIT_MERGE_MAX_BLOCK_SIZE(cn) ((INT_MAX/4)/(cn)) // HAL implementation accepts 'int' len, so INT_MAX doesn't work here

enum { BLOCK_SIZE = 1024 };

#if defined HAVE_IPP && (IPP_VERSION_X100 >= 700)
#define ARITHM_USE_IPP 1
#else
#define ARITHM_USE_IPP 0
#endif

inline bool checkScalar(const Mat& sc, int atype, _InputArray::KindFlag sckind, _InputArray::KindFlag akind)
{
    if( sc.dims > 2 || !sc.isContinuous() )
        return false;
    Size sz = sc.size();
    if(sz.width != 1 && sz.height != 1)
        return false;
    int cn = CV_MAT_CN(atype);
    if( akind == _InputArray::MATX && sckind != _InputArray::MATX )
        return false;
    return sz == Size(1, 1) || sz == Size(1, cn) || sz == Size(cn, 1) ||
           (sz == Size(1, 4) && sc.type() == CV_64F && cn <= 4);
}

inline bool checkScalar(InputArray sc, int atype, _InputArray::KindFlag sckind, _InputArray::KindFlag akind)
{
    if( sc.dims() > 2 || !sc.isContinuous() )
        return false;
    Size sz = sc.size();
    if(sz.width != 1 && sz.height != 1)
        return false;
    int cn = CV_MAT_CN(atype);
    if( akind == _InputArray::MATX && sckind != _InputArray::MATX )
        return false;
    return sz == Size(1, 1) || sz == Size(1, cn) || sz == Size(cn, 1) ||
           (sz == Size(1, 4) && sc.type() == CV_64F && cn <= 4);
}

void convertAndUnrollScalar( const Mat& sc, int buftype, uchar* scbuf, size_t blocksize );

#ifdef CV_COLLECT_IMPL_DATA
struct ImplCollector
{
    ImplCollector()
    {
        useCollection   = false;
        implFlags       = 0;
    }
    bool useCollection; // enable/disable impl data collection

    int implFlags;
    std::vector<int>    implCode;
    std::vector<String> implFun;

    cv::Mutex mutex;
};
#endif

struct CoreTLSData
{
    CoreTLSData() :
//#ifdef HAVE_OPENCL
        oclExecutionContextInitialized(false), useOpenCL(-1),
//#endif
        useIPP(-1),
        useIPP_NE(-1)
#ifdef HAVE_OPENVX
        ,useOpenVX(-1)
#endif
    {}

    RNG rng;
//#ifdef HAVE_OPENCL
    ocl::OpenCLExecutionContext oclExecutionContext;
    bool oclExecutionContextInitialized;
    int useOpenCL; // 1 - use, 0 - do not use, -1 - auto/not initialized
//#endif
    int useIPP;    // 1 - use, 0 - do not use, -1 - auto/not initialized
    int useIPP_NE; // 1 - use, 0 - do not use, -1 - auto/not initialized
#ifdef HAVE_OPENVX
    int useOpenVX; // 1 - use, 0 - do not use, -1 - auto/not initialized
#endif
};

CoreTLSData& getCoreTlsData();

#if defined(BUILD_SHARED_LIBS)
#if defined _WIN32 || defined WINCE
#define CL_RUNTIME_EXPORT __declspec(dllexport)
#elif defined __GNUC__ && __GNUC__ >= 4
#define CL_RUNTIME_EXPORT __attribute__ ((visibility ("default")))
#else
#define CL_RUNTIME_EXPORT
#endif
#else
#define CL_RUNTIME_EXPORT
#endif

extern CV_EXPORTS
bool __termination;  // skip some cleanups, because process is terminating
                     // (for example, if ExitProcess() was already called)

cv::Mutex& getInitializationMutex();

#define CV_SINGLETON_LAZY_INIT_(TYPE, INITIALIZER, RET_VALUE) \
    static TYPE* const instance = INITIALIZER; \
    return RET_VALUE;

#define CV_SINGLETON_LAZY_INIT(TYPE, INITIALIZER) CV_SINGLETON_LAZY_INIT_(TYPE, INITIALIZER, instance)
#define CV_SINGLETON_LAZY_INIT_REF(TYPE, INITIALIZER) CV_SINGLETON_LAZY_INIT_(TYPE, INITIALIZER, *instance)

CV_EXPORTS void releaseTlsStorageThread();

int cv_snprintf(char* buf, int len, const char* fmt, ...);
int cv_vsnprintf(char* buf, int len, const char* fmt, va_list args);
}

#endif  // BUILD_PLUGIN
#endif  // __OPENCV_PRECOMP_H__