core.hpp

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#ifndef OPENCV_CORE_HPP
#define OPENCV_CORE_HPP
 
#ifndef __cplusplus
#  error core.hpp header must be compiled as C++
#endif
 
#include "opencv2/core/cvdef.h"
#include "opencv2/core/base.hpp"
#include "opencv2/core/cvstd.hpp"
#include "opencv2/core/traits.hpp"
#include "opencv2/core/matx.hpp"
#include "opencv2/core/types.hpp"
#include "opencv2/core/mat.hpp"
#include "opencv2/core/persistence.hpp"
 
namespace cv {
 
 
class CV_EXPORTS Exception : public std::exception
{
public:
    Exception();
    Exception(int _code, const String& _err, const String& _func, const String& _file, int _line);
    virtual ~Exception() throw();
 
    virtual const char *what() const throw() CV_OVERRIDE;
    void formatMessage();
 
    String msg; 
 
    int code; 
    String err; 
    String func; 
    String file; 
    int line; 
};
 
CV_EXPORTS CV_NORETURN void error(const Exception& exc);
 
enum SortFlags { SORT_EVERY_ROW    = 0, 
                 SORT_EVERY_COLUMN = 1, 
                 SORT_ASCENDING    = 0, 
                 SORT_DESCENDING   = 16 
               };
 
 
 
enum CovarFlags {
    COVAR_SCRAMBLED = 0,
    COVAR_NORMAL    = 1,
    COVAR_USE_AVG   = 2,
    COVAR_SCALE     = 4,
    COVAR_ROWS      = 8,
    COVAR_COLS      = 16
};
 
 
enum KmeansFlags {
    KMEANS_RANDOM_CENTERS     = 0,
    KMEANS_PP_CENTERS         = 2,
    KMEANS_USE_INITIAL_LABELS = 1
};
 
 
 
enum ReduceTypes { REDUCE_SUM = 0, 
                   REDUCE_AVG = 1, 
                   REDUCE_MAX = 2, 
                   REDUCE_MIN = 3  
                 };
 
 
CV_EXPORTS void swap(Mat& a, Mat& b);
CV_EXPORTS void swap( UMat& a, UMat& b );
 
 
 
CV_EXPORTS_W int borderInterpolate(int p, int len, int borderType);
 
CV_EXPORTS_W void copyMakeBorder(InputArray src, OutputArray dst,
                                 int top, int bottom, int left, int right,
                                 int borderType, const Scalar& value = Scalar() );
 
CV_EXPORTS_W void add(InputArray src1, InputArray src2, OutputArray dst,
                      InputArray mask = noArray(), int dtype = -1);
 
CV_EXPORTS_W void subtract(InputArray src1, InputArray src2, OutputArray dst,
                           InputArray mask = noArray(), int dtype = -1);
 
 
CV_EXPORTS_W void multiply(InputArray src1, InputArray src2,
                           OutputArray dst, double scale = 1, int dtype = -1);
 
CV_EXPORTS_W void divide(InputArray src1, InputArray src2, OutputArray dst,
                         double scale = 1, int dtype = -1);
 
CV_EXPORTS_W void divide(double scale, InputArray src2,
                         OutputArray dst, int dtype = -1);
 
CV_EXPORTS_W void scaleAdd(InputArray src1, double alpha, InputArray src2, OutputArray dst);
 
CV_EXPORTS_W void addWeighted(InputArray src1, double alpha, InputArray src2,
                              double beta, double gamma, OutputArray dst, int dtype = -1);
 
CV_EXPORTS_W void convertScaleAbs(InputArray src, OutputArray dst,
                                  double alpha = 1, double beta = 0);
 
CV_EXPORTS_W void convertFp16(InputArray src, OutputArray dst);
 
CV_EXPORTS_W void LUT(InputArray src, InputArray lut, OutputArray dst);
 
CV_EXPORTS_AS(sumElems) Scalar sum(InputArray src);
 
CV_EXPORTS_W int countNonZero( InputArray src );
 
CV_EXPORTS_W void findNonZero( InputArray src, OutputArray idx );
 
CV_EXPORTS_W Scalar mean(InputArray src, InputArray mask = noArray());
 
CV_EXPORTS_W void meanStdDev(InputArray src, OutputArray mean, OutputArray stddev,
                             InputArray mask=noArray());
 
CV_EXPORTS_W double norm(InputArray src1, int normType = NORM_L2, InputArray mask = noArray());
 
CV_EXPORTS_W double norm(InputArray src1, InputArray src2,
                         int normType = NORM_L2, InputArray mask = noArray());
CV_EXPORTS double norm( const SparseMat& src, int normType );
 
CV_EXPORTS_W double PSNR(InputArray src1, InputArray src2, double R=255.);
 
CV_EXPORTS_W void batchDistance(InputArray src1, InputArray src2,
                                OutputArray dist, int dtype, OutputArray nidx,
                                int normType = NORM_L2, int K = 0,
                                InputArray mask = noArray(), int update = 0,
                                bool crosscheck = false);
 
CV_EXPORTS_W void normalize( InputArray src, InputOutputArray dst, double alpha = 1, double beta = 0,
                             int norm_type = NORM_L2, int dtype = -1, InputArray mask = noArray());
 
CV_EXPORTS void normalize( const SparseMat& src, SparseMat& dst, double alpha, int normType );
 
CV_EXPORTS_W void minMaxLoc(InputArray src, CV_OUT double* minVal,
                            CV_OUT double* maxVal = 0, CV_OUT Point* minLoc = 0,
                            CV_OUT Point* maxLoc = 0, InputArray mask = noArray());
 
 
CV_EXPORTS void minMaxIdx(InputArray src, double* minVal, double* maxVal = 0,
                          int* minIdx = 0, int* maxIdx = 0, InputArray mask = noArray());
 
CV_EXPORTS void minMaxLoc(const SparseMat& a, double* minVal,
                          double* maxVal, int* minIdx = 0, int* maxIdx = 0);
 
CV_EXPORTS_W void reduce(InputArray src, OutputArray dst, int dim, int rtype, int dtype = -1);
 
CV_EXPORTS void merge(const Mat* mv, size_t count, OutputArray dst);
 
CV_EXPORTS_W void merge(InputArrayOfArrays mv, OutputArray dst);
 
CV_EXPORTS void split(const Mat& src, Mat* mvbegin);
 
CV_EXPORTS_W void split(InputArray m, OutputArrayOfArrays mv);
 
CV_EXPORTS void mixChannels(const Mat* src, size_t nsrcs, Mat* dst, size_t ndsts,
                            const int* fromTo, size_t npairs);
 
CV_EXPORTS void mixChannels(InputArrayOfArrays src, InputOutputArrayOfArrays dst,
                            const int* fromTo, size_t npairs);
 
CV_EXPORTS_W void mixChannels(InputArrayOfArrays src, InputOutputArrayOfArrays dst,
                              const std::vector<int>& fromTo);
 
CV_EXPORTS_W void extractChannel(InputArray src, OutputArray dst, int coi);
 
CV_EXPORTS_W void insertChannel(InputArray src, InputOutputArray dst, int coi);
 
CV_EXPORTS_W void flip(InputArray src, OutputArray dst, int flipCode);
 
enum RotateFlags {
    ROTATE_90_CLOCKWISE = 0, 
    ROTATE_180 = 1, 
    ROTATE_90_COUNTERCLOCKWISE = 2, 
};
CV_EXPORTS_W void rotate(InputArray src, OutputArray dst, int rotateCode);
 
CV_EXPORTS_W void repeat(InputArray src, int ny, int nx, OutputArray dst);
 
CV_EXPORTS Mat repeat(const Mat& src, int ny, int nx);
 
CV_EXPORTS void hconcat(const Mat* src, size_t nsrc, OutputArray dst);
CV_EXPORTS void hconcat(InputArray src1, InputArray src2, OutputArray dst);
CV_EXPORTS_W void hconcat(InputArrayOfArrays src, OutputArray dst);
 
CV_EXPORTS void vconcat(const Mat* src, size_t nsrc, OutputArray dst);
CV_EXPORTS void vconcat(InputArray src1, InputArray src2, OutputArray dst);
CV_EXPORTS_W void vconcat(InputArrayOfArrays src, OutputArray dst);
 
CV_EXPORTS_W void bitwise_and(InputArray src1, InputArray src2,
                              OutputArray dst, InputArray mask = noArray());
 
CV_EXPORTS_W void bitwise_or(InputArray src1, InputArray src2,
                             OutputArray dst, InputArray mask = noArray());
 
CV_EXPORTS_W void bitwise_xor(InputArray src1, InputArray src2,
                              OutputArray dst, InputArray mask = noArray());
 
CV_EXPORTS_W void bitwise_not(InputArray src, OutputArray dst,
                              InputArray mask = noArray());
 
CV_EXPORTS_W void absdiff(InputArray src1, InputArray src2, OutputArray dst);
 
void CV_EXPORTS_W copyTo(InputArray src, OutputArray dst, InputArray mask);
CV_EXPORTS_W void inRange(InputArray src, InputArray lowerb,
                          InputArray upperb, OutputArray dst);
 
CV_EXPORTS_W void compare(InputArray src1, InputArray src2, OutputArray dst, int cmpop);
 
CV_EXPORTS_W void min(InputArray src1, InputArray src2, OutputArray dst);
CV_EXPORTS void min(const Mat& src1, const Mat& src2, Mat& dst);
CV_EXPORTS void min(const UMat& src1, const UMat& src2, UMat& dst);
 
CV_EXPORTS_W void max(InputArray src1, InputArray src2, OutputArray dst);
CV_EXPORTS void max(const Mat& src1, const Mat& src2, Mat& dst);
CV_EXPORTS void max(const UMat& src1, const UMat& src2, UMat& dst);
 
CV_EXPORTS_W void sqrt(InputArray src, OutputArray dst);
 
CV_EXPORTS_W void pow(InputArray src, double power, OutputArray dst);
 
CV_EXPORTS_W void exp(InputArray src, OutputArray dst);
 
CV_EXPORTS_W void log(InputArray src, OutputArray dst);
 
CV_EXPORTS_W void polarToCart(InputArray magnitude, InputArray angle,
                              OutputArray x, OutputArray y, bool angleInDegrees = false);
 
CV_EXPORTS_W void cartToPolar(InputArray x, InputArray y,
                              OutputArray magnitude, OutputArray angle,
                              bool angleInDegrees = false);
 
CV_EXPORTS_W void phase(InputArray x, InputArray y, OutputArray angle,
                        bool angleInDegrees = false);
 
CV_EXPORTS_W void magnitude(InputArray x, InputArray y, OutputArray magnitude);
 
CV_EXPORTS_W bool checkRange(InputArray a, bool quiet = true, CV_OUT Point* pos = 0,
                            double minVal = -DBL_MAX, double maxVal = DBL_MAX);
 
CV_EXPORTS_W void patchNaNs(InputOutputArray a, double val = 0);
 
CV_EXPORTS_W void gemm(InputArray src1, InputArray src2, double alpha,
                       InputArray src3, double beta, OutputArray dst, int flags = 0);
 
CV_EXPORTS_W void mulTransposed( InputArray src, OutputArray dst, bool aTa,
                                 InputArray delta = noArray(),
                                 double scale = 1, int dtype = -1 );
 
CV_EXPORTS_W void transpose(InputArray src, OutputArray dst);
 
CV_EXPORTS_W void transform(InputArray src, OutputArray dst, InputArray m );
 
CV_EXPORTS_W void perspectiveTransform(InputArray src, OutputArray dst, InputArray m );
 
CV_EXPORTS_W void completeSymm(InputOutputArray m, bool lowerToUpper = false);
 
CV_EXPORTS_W void setIdentity(InputOutputArray mtx, const Scalar& s = Scalar(1));
 
CV_EXPORTS_W double determinant(InputArray mtx);
 
CV_EXPORTS_W Scalar trace(InputArray mtx);
 
CV_EXPORTS_W double invert(InputArray src, OutputArray dst, int flags = DECOMP_LU);
 
CV_EXPORTS_W bool solve(InputArray src1, InputArray src2,
                        OutputArray dst, int flags = DECOMP_LU);
 
CV_EXPORTS_W void sort(InputArray src, OutputArray dst, int flags);
 
CV_EXPORTS_W void sortIdx(InputArray src, OutputArray dst, int flags);
 
CV_EXPORTS_W int solveCubic(InputArray coeffs, OutputArray roots);
 
CV_EXPORTS_W double solvePoly(InputArray coeffs, OutputArray roots, int maxIters = 300);
 
CV_EXPORTS_W bool eigen(InputArray src, OutputArray eigenvalues,
                        OutputArray eigenvectors = noArray());
 
CV_EXPORTS_W void eigenNonSymmetric(InputArray src, OutputArray eigenvalues,
                                    OutputArray eigenvectors);
 
CV_EXPORTS void calcCovarMatrix( const Mat* samples, int nsamples, Mat& covar, Mat& mean,
                                 int flags, int ctype = CV_64F);
 
CV_EXPORTS_W void calcCovarMatrix( InputArray samples, OutputArray covar,
                                   InputOutputArray mean, int flags, int ctype = CV_64F);
 
CV_EXPORTS_W void PCACompute(InputArray data, InputOutputArray mean,
                             OutputArray eigenvectors, int maxComponents = 0);
 
CV_EXPORTS_AS(PCACompute2) void PCACompute(InputArray data, InputOutputArray mean,
                                           OutputArray eigenvectors, OutputArray eigenvalues,
                                           int maxComponents = 0);
 
CV_EXPORTS_W void PCACompute(InputArray data, InputOutputArray mean,
                             OutputArray eigenvectors, double retainedVariance);
 
CV_EXPORTS_AS(PCACompute2) void PCACompute(InputArray data, InputOutputArray mean,
                                           OutputArray eigenvectors, OutputArray eigenvalues,
                                           double retainedVariance);
 
CV_EXPORTS_W void PCAProject(InputArray data, InputArray mean,
                             InputArray eigenvectors, OutputArray result);
 
CV_EXPORTS_W void PCABackProject(InputArray data, InputArray mean,
                                 InputArray eigenvectors, OutputArray result);
 
CV_EXPORTS_W void SVDecomp( InputArray src, OutputArray w, OutputArray u, OutputArray vt, int flags = 0 );
 
CV_EXPORTS_W void SVBackSubst( InputArray w, InputArray u, InputArray vt,
                               InputArray rhs, OutputArray dst );
 
CV_EXPORTS_W double Mahalanobis(InputArray v1, InputArray v2, InputArray icovar);
 
CV_EXPORTS_W void dft(InputArray src, OutputArray dst, int flags = 0, int nonzeroRows = 0);
 
CV_EXPORTS_W void idft(InputArray src, OutputArray dst, int flags = 0, int nonzeroRows = 0);
 
CV_EXPORTS_W void dct(InputArray src, OutputArray dst, int flags = 0);
 
CV_EXPORTS_W void idct(InputArray src, OutputArray dst, int flags = 0);
 
CV_EXPORTS_W void mulSpectrums(InputArray a, InputArray b, OutputArray c,
                               int flags, bool conjB = false);
 
CV_EXPORTS_W int getOptimalDFTSize(int vecsize);
 
CV_EXPORTS RNG& theRNG();
 
CV_EXPORTS_W void setRNGSeed(int seed);
 
CV_EXPORTS_W void randu(InputOutputArray dst, InputArray low, InputArray high);
 
CV_EXPORTS_W void randn(InputOutputArray dst, InputArray mean, InputArray stddev);
 
CV_EXPORTS_W void randShuffle(InputOutputArray dst, double iterFactor = 1., RNG* rng = 0);
 
class CV_EXPORTS PCA
{
public:
    enum Flags { DATA_AS_ROW = 0, 
                 DATA_AS_COL = 1, 
                 USE_AVG     = 2  
               };
 
    PCA();
 
    PCA(InputArray data, InputArray mean, int flags, int maxComponents = 0);
 
    PCA(InputArray data, InputArray mean, int flags, double retainedVariance);
 
    PCA& operator()(InputArray data, InputArray mean, int flags, int maxComponents = 0);
 
    PCA& operator()(InputArray data, InputArray mean, int flags, double retainedVariance);
 
    Mat project(InputArray vec) const;
 
    void project(InputArray vec, OutputArray result) const;
 
    Mat backProject(InputArray vec) const;
 
    void backProject(InputArray vec, OutputArray result) const;
 
    void write(FileStorage& fs) const;
 
    void read(const FileNode& fn);
 
    Mat eigenvectors; 
    Mat eigenvalues; 
    Mat mean; 
};
 
class CV_EXPORTS LDA
{
public:
    explicit LDA(int num_components = 0);
 
    LDA(InputArrayOfArrays src, InputArray labels, int num_components = 0);
 
    void save(const String& filename) const;
 
    void load(const String& filename);
 
    void save(FileStorage& fs) const;
 
    void load(const FileStorage& node);
 
    ~LDA();
 
    void compute(InputArrayOfArrays src, InputArray labels);
 
    Mat project(InputArray src);
 
    Mat reconstruct(InputArray src);
 
    Mat eigenvectors() const { return _eigenvectors; }
 
    Mat eigenvalues() const { return _eigenvalues; }
 
    static Mat subspaceProject(InputArray W, InputArray mean, InputArray src);
    static Mat subspaceReconstruct(InputArray W, InputArray mean, InputArray src);
 
protected:
    int _num_components;
    Mat _eigenvectors;
    Mat _eigenvalues;
    void lda(InputArrayOfArrays src, InputArray labels);
};
 
class CV_EXPORTS SVD
{
public:
    enum Flags {
        MODIFY_A = 1,
        NO_UV    = 2,
        FULL_UV  = 4
    };
 
    SVD();
 
    SVD( InputArray src, int flags = 0 );
 
    SVD& operator ()( InputArray src, int flags = 0 );
 
    static void compute( InputArray src, OutputArray w,
                         OutputArray u, OutputArray vt, int flags = 0 );
 
    static void compute( InputArray src, OutputArray w, int flags = 0 );
 
    static void backSubst( InputArray w, InputArray u,
                           InputArray vt, InputArray rhs,
                           OutputArray dst );
 
    static void solveZ( InputArray src, OutputArray dst );
 
    void backSubst( InputArray rhs, OutputArray dst ) const;
 
    template<typename _Tp, int m, int n, int nm> static
    void compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w, Matx<_Tp, m, nm>& u, Matx<_Tp, n, nm>& vt );
 
    template<typename _Tp, int m, int n, int nm> static
    void compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w );
 
    template<typename _Tp, int m, int n, int nm, int nb> static
    void backSubst( const Matx<_Tp, nm, 1>& w, const Matx<_Tp, m, nm>& u, const Matx<_Tp, n, nm>& vt, const Matx<_Tp, m, nb>& rhs, Matx<_Tp, n, nb>& dst );
 
    Mat u, w, vt;
};
 
class CV_EXPORTS RNG
{
public:
    enum { UNIFORM = 0,
           NORMAL  = 1
         };
 
    RNG();
    RNG(uint64 state);
    unsigned next();
 
    operator uchar();
    operator schar();
    operator ushort();
    operator short();
    operator unsigned();
    operator int();
    operator float();
    operator double();
 
    unsigned operator ()();
    unsigned operator ()(unsigned N);
 
    int uniform(int a, int b);
    float uniform(float a, float b);
    double uniform(double a, double b);
 
    void fill( InputOutputArray mat, int distType, InputArray a, InputArray b, bool saturateRange = false );
 
    double gaussian(double sigma);
 
    uint64 state;
 
    bool operator ==(const RNG& other) const;
};
 
class CV_EXPORTS RNG_MT19937
{
public:
    RNG_MT19937();
    RNG_MT19937(unsigned s);
    void seed(unsigned s);
 
    unsigned next();
 
    operator int();
    operator unsigned();
    operator float();
    operator double();
 
    unsigned operator ()(unsigned N);
    unsigned operator ()();
 
    int uniform(int a, int b);
    float uniform(float a, float b);
    double uniform(double a, double b);
 
private:
    enum PeriodParameters {N = 624, M = 397};
    unsigned state[N];
    int mti;
};
 
 
 
CV_EXPORTS_W double kmeans( InputArray data, int K, InputOutputArray bestLabels,
                            TermCriteria criteria, int attempts,
                            int flags, OutputArray centers = noArray() );
 
 
 
 
class CV_EXPORTS Formatted
{
public:
    virtual const char* next() = 0;
    virtual void reset() = 0;
    virtual ~Formatted();
};
 
class CV_EXPORTS Formatter
{
public:
    enum FormatType {
           FMT_DEFAULT = 0,
           FMT_MATLAB  = 1,
           FMT_CSV     = 2,
           FMT_PYTHON  = 3,
           FMT_NUMPY   = 4,
           FMT_C       = 5
         };
 
    virtual ~Formatter();
 
    virtual Ptr<Formatted> format(const Mat& mtx) const = 0;
 
    virtual void set16fPrecision(int p = 4) = 0;
    virtual void set32fPrecision(int p = 8) = 0;
    virtual void set64fPrecision(int p = 16) = 0;
    virtual void setMultiline(bool ml = true) = 0;
 
    static Ptr<Formatter> get(Formatter::FormatType fmt = FMT_DEFAULT);
 
};
 
static inline
String& operator << (String& out, Ptr<Formatted> fmtd)
{
    fmtd->reset();
    for(const char* str = fmtd->next(); str; str = fmtd->next())
        out += cv::String(str);
    return out;
}
 
static inline
String& operator << (String& out, const Mat& mtx)
{
    return out << Formatter::get()->format(mtx);
}
 
 
class CV_EXPORTS Algorithm;
 
template<typename _Tp, typename _EnumTp = void> struct ParamType {};
 
 
class CV_EXPORTS_W Algorithm
{
public:
    Algorithm();
    virtual ~Algorithm();
 
    CV_WRAP virtual void clear() {}
 
    virtual void write(FileStorage& fs) const { CV_UNUSED(fs); }
 
    CV_WRAP void write(const Ptr<FileStorage>& fs, const String& name = String()) const;
 
    CV_WRAP virtual void read(const FileNode& fn) { CV_UNUSED(fn); }
 
    CV_WRAP virtual bool empty() const { return false; }
 
    template<typename _Tp> static Ptr<_Tp> read(const FileNode& fn)
    {
        Ptr<_Tp> obj = _Tp::create();
        obj->read(fn);
        return !obj->empty() ? obj : Ptr<_Tp>();
    }
 
    template<typename _Tp> static Ptr<_Tp> load(const String& filename, const String& objname=String())
    {
        FileStorage fs(filename, FileStorage::READ);
        CV_Assert(fs.isOpened());
        FileNode fn = objname.empty() ? fs.getFirstTopLevelNode() : fs[objname];
        if (fn.empty()) return Ptr<_Tp>();
        Ptr<_Tp> obj = _Tp::create();
        obj->read(fn);
        return !obj->empty() ? obj : Ptr<_Tp>();
    }
 
    template<typename _Tp> static Ptr<_Tp> loadFromString(const String& strModel, const String& objname=String())
    {
        FileStorage fs(strModel, FileStorage::READ + FileStorage::MEMORY);
        FileNode fn = objname.empty() ? fs.getFirstTopLevelNode() : fs[objname];
        Ptr<_Tp> obj = _Tp::create();
        obj->read(fn);
        return !obj->empty() ? obj : Ptr<_Tp>();
    }
 
    CV_WRAP virtual void save(const String& filename) const;
 
    CV_WRAP virtual String getDefaultName() const;
 
protected:
    void writeFormat(FileStorage& fs) const;
};
 
enum struct Param {
    INT=0, BOOLEAN=1, REAL=2, STRING=3, MAT=4, MAT_VECTOR=5, ALGORITHM=6, FLOAT=7,
    UNSIGNED_INT=8, UINT64=9, UCHAR=11, SCALAR=12
};
 
 
 
template<> struct ParamType<bool>
{
    typedef bool const_param_type;
    typedef bool member_type;
 
    static const Param type = Param::BOOLEAN;
};
 
template<> struct ParamType<int>
{
    typedef int const_param_type;
    typedef int member_type;
 
    static const Param type = Param::INT;
};
 
template<> struct ParamType<double>
{
    typedef double const_param_type;
    typedef double member_type;
 
    static const Param type = Param::REAL;
};
 
template<> struct ParamType<String>
{
    typedef const String& const_param_type;
    typedef String member_type;
 
    static const Param type = Param::STRING;
};
 
template<> struct ParamType<Mat>
{
    typedef const Mat& const_param_type;
    typedef Mat member_type;
 
    static const Param type = Param::MAT;
};
 
template<> struct ParamType<std::vector<Mat> >
{
    typedef const std::vector<Mat>& const_param_type;
    typedef std::vector<Mat> member_type;
 
    static const Param type = Param::MAT_VECTOR;
};
 
template<> struct ParamType<Algorithm>
{
    typedef const Ptr<Algorithm>& const_param_type;
    typedef Ptr<Algorithm> member_type;
 
    static const Param type = Param::ALGORITHM;
};
 
template<> struct ParamType<float>
{
    typedef float const_param_type;
    typedef float member_type;
 
    static const Param type = Param::FLOAT;
};
 
template<> struct ParamType<unsigned>
{
    typedef unsigned const_param_type;
    typedef unsigned member_type;
 
    static const Param type = Param::UNSIGNED_INT;
};
 
template<> struct ParamType<uint64>
{
    typedef uint64 const_param_type;
    typedef uint64 member_type;
 
    static const Param type = Param::UINT64;
};
 
template<> struct ParamType<uchar>
{
    typedef uchar const_param_type;
    typedef uchar member_type;
 
    static const Param type = Param::UCHAR;
};
 
template<> struct ParamType<Scalar>
{
    typedef const Scalar& const_param_type;
    typedef Scalar member_type;
 
    static const Param type = Param::SCALAR;
};
 
template<typename _Tp>
struct ParamType<_Tp, typename std::enable_if< std::is_enum<_Tp>::value >::type>
{
    typedef typename std::underlying_type<_Tp>::type const_param_type;
    typedef typename std::underlying_type<_Tp>::type member_type;
 
    static const Param type = Param::INT;
};
 
 
} //namespace cv
 
#include "opencv2/core/operations.hpp"
#include "opencv2/core/cvstd.inl.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/core/optim.hpp"
#include "opencv2/core/ovx.hpp"
 
#endif /*OPENCV_CORE_HPP*/