EstervQrCode 1.1.1
Library for qr code manipulation
core.hpp
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44 
45 #ifndef OPENCV_CORE_HPP
46 #define OPENCV_CORE_HPP
47 
48 #ifndef __cplusplus
49 # error core.hpp header must be compiled as C++
50 #endif
51 
52 #include "opencv2/core/cvdef.h"
53 #include "opencv2/core/base.hpp"
54 #include "opencv2/core/cvstd.hpp"
55 #include "opencv2/core/traits.hpp"
56 #include "opencv2/core/matx.hpp"
57 #include "opencv2/core/types.hpp"
58 #include "opencv2/core/mat.hpp"
59 #include "opencv2/core/persistence.hpp"
60 
102 namespace cv {
103 
106 
115 {
116 public:
125  Exception(int _code, const String& _err, const String& _func, const String& _file, int _line);
126  virtual ~Exception() throw();
127 
131  virtual const char *what() const throw() CV_OVERRIDE;
132  void formatMessage();
133 
134  String msg;
135 
136  int code;
137  String err;
139  String file;
140  int line;
141 };
142 
152 
154  SORT_EVERY_COLUMN = 1,
157  SORT_ASCENDING = 0,
159  SORT_DESCENDING = 16
162  };
163 
165 
168 
202  COVAR_COLS = 16
203 };
204 
207 
219 };
220 
222 
225 
230  REDUCE_SUM2 = 4
231  };
232 
234 
237 CV_EXPORTS void swap(Mat& a, Mat& b);
239 CV_EXPORTS void swap( UMat& a, UMat& b );
240 
242 
245 
267 CV_EXPORTS_W int borderInterpolate(int p, int len, int borderType);
268 
318  int top, int bottom, int left, int right,
319  int borderType, const Scalar& value = Scalar() );
320 
361  InputArray mask = noArray(), int dtype = -1);
362 
404  InputArray mask = noArray(), int dtype = -1);
405 
406 
432  OutputArray dst, double scale = 1, int dtype = -1);
433 
463  double scale = 1, int dtype = -1);
464 
467  OutputArray dst, int dtype = -1);
468 
488 
516  double beta, double gamma, OutputArray dst, int dtype = -1);
517 
544  double alpha = 1, double beta = 0);
545 
559 
575 
584 
602 
621 
659 
672 
695 
733 
746  int normType = NORM_L2, InputArray mask = noArray());
751 CV_EXPORTS double norm( const SparseMat& src, int normType );
752 
773 
780  OutputArray dist, int dtype, OutputArray nidx,
781  int normType = NORM_L2, int K = 0,
782  InputArray mask = noArray(), int update = 0,
783  bool crosscheck = false);
784 
843 CV_EXPORTS_W void normalize( InputArray src, InputOutputArray dst, double alpha = 1, double beta = 0,
844  int norm_type = NORM_L2, int dtype = -1, InputArray mask = noArray());
845 
853 CV_EXPORTS void normalize( const SparseMat& src, SparseMat& dst, double alpha, int normType );
854 
873 CV_EXPORTS_W void minMaxLoc(InputArray src, CV_OUT double* minVal,
874  CV_OUT double* maxVal = 0, CV_OUT Point* minLoc = 0,
875  CV_OUT Point* maxLoc = 0, InputArray mask = noArray());
876 
892 CV_EXPORTS_W void reduceArgMin(InputArray src, OutputArray dst, int axis, bool lastIndex = false);
893 
909 CV_EXPORTS_W void reduceArgMax(InputArray src, OutputArray dst, int axis, bool lastIndex = false);
910 
931 CV_EXPORTS void minMaxIdx(InputArray src, double* minVal, double* maxVal = 0,
932  int* minIdx = 0, int* maxIdx = 0, InputArray mask = noArray());
933 
943 CV_EXPORTS void minMaxLoc(const SparseMat& a, double* minVal,
944  double* maxVal, int* minIdx = 0, int* maxIdx = 0);
945 
970 CV_EXPORTS_W void reduce(InputArray src, OutputArray dst, int dim, int rtype, int dtype = -1);
971 
991 CV_EXPORTS void merge(const Mat* mv, size_t count, OutputArray dst);
992 
1000 
1016 CV_EXPORTS void split(const Mat& src, Mat* mvbegin);
1017 
1023 
1065 CV_EXPORTS void mixChannels(const Mat* src, size_t nsrcs, Mat* dst, size_t ndsts,
1066  const int* fromTo, size_t npairs);
1067 
1083  const int* fromTo, size_t npairs);
1084 
1099  const std::vector<int>& fromTo);
1100 
1108 
1116 
1149 CV_EXPORTS_W void flip(InputArray src, OutputArray dst, int flipCode);
1150 
1157 
1164 
1169 };
1181 CV_EXPORTS_W void rotate(InputArray src, OutputArray dst, int rotateCode);
1182 
1196 CV_EXPORTS_W void repeat(InputArray src, int ny, int nx, OutputArray dst);
1197 
1205 CV_EXPORTS Mat repeat(const Mat& src, int ny, int nx);
1206 
1228 CV_EXPORTS void hconcat(const Mat* src, size_t nsrc, OutputArray dst);
1269 
1290 CV_EXPORTS void vconcat(const Mat* src, size_t nsrc, OutputArray dst);
1333 
1361 
1388 
1416 
1432  InputArray mask = noArray());
1433 
1461 
1493  InputArray upperb, OutputArray dst);
1494 
1522 
1538 CV_EXPORTS void min(const Mat& src1, const Mat& src2, Mat& dst);
1542 CV_EXPORTS void min(const UMat& src1, const UMat& src2, UMat& dst);
1543 
1559 CV_EXPORTS void max(const Mat& src1, const Mat& src2, Mat& dst);
1563 CV_EXPORTS void max(const UMat& src1, const UMat& src2, UMat& dst);
1564 
1575 
1600 
1616 
1629 
1651  OutputArray x, OutputArray y, bool angleInDegrees = false);
1652 
1673  bool angleInDegrees = false);
1674 
1692  bool angleInDegrees = false);
1693 
1706 
1722 CV_EXPORTS_W bool checkRange(InputArray a, bool quiet = true, CV_OUT Point* pos = 0,
1723  double minVal = -DBL_MAX, double maxVal = DBL_MAX);
1724 
1729 CV_EXPORTS_W void patchNaNs(InputOutputArray a, double val = 0);
1730 
1760  InputArray src3, double beta, OutputArray dst, int flags = 0);
1761 
1791  InputArray delta = noArray(),
1792  double scale = 1, int dtype = -1 );
1793 
1804 
1814 
1840 
1867 
1882 CV_EXPORTS_W void completeSymm(InputOutputArray m, bool lowerToUpper = false);
1883 
1900 
1915 
1924 
1951 
1975  OutputArray dst, int flags = DECOMP_LU);
1976 
1991 
2011 
2026 
2035 CV_EXPORTS_W double solvePoly(InputArray coeffs, OutputArray roots, int maxIters = 300);
2036 
2058 
2075 
2089 CV_EXPORTS void calcCovarMatrix( const Mat* samples, int nsamples, Mat& covar, Mat& mean,
2090  int flags, int ctype = CV_64F);
2091 
2101  InputOutputArray mean, int flags, int ctype = CV_64F);
2102 
2106 
2110  int maxComponents = 0);
2111 
2115 
2120 
2124 
2128 
2131 
2134  InputArray rhs, OutputArray dst );
2135 
2147 
2280 CV_EXPORTS_W void dft(InputArray src, OutputArray dst, int flags = 0, int nonzeroRows = 0);
2281 
2294 CV_EXPORTS_W void idft(InputArray src, OutputArray dst, int flags = 0, int nonzeroRows = 0);
2295 
2336 
2346 
2365  int flags, bool conjB = false);
2366 
2389 
2400 
2407 CV_EXPORTS_W void setRNGSeed(int seed);
2408 
2420 
2433 
2445 CV_EXPORTS_W void randShuffle(InputOutputArray dst, double iterFactor = 1., RNG* rng = 0);
2446 
2513 {
2514 public:
2515  enum Flags { DATA_AS_ROW = 0,
2516  DATA_AS_COL = 1,
2517  USE_AVG = 2
2518  };
2519 
2525  PCA();
2526 
2537 
2549 
2571 
2584 
2599  Mat project(InputArray vec) const;
2600 
2614 
2629 
2638 
2643  void write(FileStorage& fs) const;
2644 
2649  void read(const FileNode& fn);
2650 
2654 };
2655 
2669 {
2670 public:
2674  explicit LDA(int num_components = 0);
2675 
2681  LDA(InputArrayOfArrays src, InputArray labels, int num_components = 0);
2682 
2685  void save(const String& filename) const;
2686 
2689  void load(const String& filename);
2690 
2693  void save(FileStorage& fs) const;
2694 
2697  void load(const FileStorage& node);
2698 
2701  ~LDA();
2702 
2706 
2711 
2716 
2719  Mat eigenvectors() const { return _eigenvectors; }
2720 
2723  Mat eigenvalues() const { return _eigenvalues; }
2724 
2727 
2728 protected:
2733 };
2734 
2750 {
2751 public:
2752  enum Flags {
2755  MODIFY_A = 1,
2758  NO_UV = 2,
2762  FULL_UV = 4
2763  };
2764 
2769  SVD();
2770 
2776  SVD( InputArray src, int flags = 0 );
2777 
2789  SVD& operator ()( InputArray src, int flags = 0 );
2790 
2808  static void compute( InputArray src, OutputArray w,
2809  OutputArray u, OutputArray vt, int flags = 0 );
2810 
2817  static void compute( InputArray src, OutputArray w, int flags = 0 );
2818 
2821  static void backSubst( InputArray w, InputArray u,
2822  InputArray vt, InputArray rhs,
2823  OutputArray dst );
2824 
2835  static void solveZ( InputArray src, OutputArray dst );
2836 
2859  void backSubst( InputArray rhs, OutputArray dst ) const;
2860 
2862  template<typename _Tp, int m, int n, int nm> static
2864 
2866  template<typename _Tp, int m, int n, int nm> static
2868 
2870  template<typename _Tp, int m, int n, int nm, int nb> static
2872 
2873  Mat u, w, vt;
2874 };
2875 
2889 {
2890 public:
2891  enum { UNIFORM = 0,
2892  NORMAL = 1
2893  };
2894 
2903  RNG();
2907  RNG(uint64 state);
2910  unsigned next();
2911 
2918  operator uchar();
2920  operator schar();
2922  operator ushort();
2924  operator short();
2926  operator unsigned();
2928  operator int();
2930  operator float();
2932  operator double();
2933 
2941  unsigned operator ()();
2945  unsigned operator ()(unsigned N);
2946 
2983  int uniform(int a, int b);
2985  float uniform(float a, float b);
2987  double uniform(double a, double b);
2988 
3023  void fill( InputOutputArray mat, int distType, InputArray a, InputArray b, bool saturateRange = false );
3024 
3033  double gaussian(double sigma);
3034 
3036 
3037  bool operator ==(const RNG& other) const;
3038 };
3039 
3046 {
3047 public:
3049  RNG_MT19937(unsigned s);
3050  void seed(unsigned s);
3051 
3052  unsigned next();
3053 
3054  operator int();
3055  operator unsigned();
3056  operator float();
3057  operator double();
3058 
3059  unsigned operator ()(unsigned N);
3060  unsigned operator ()();
3061 
3063  int uniform(int a, int b);
3065  float uniform(float a, float b);
3067  double uniform(double a, double b);
3068 
3069 private:
3070  enum PeriodParameters {N = 624, M = 397};
3071  unsigned state[N];
3072  int mti;
3073 };
3074 
3076 
3079 
3118  TermCriteria criteria, int attempts,
3119  int flags, OutputArray centers = noArray() );
3120 
3122 
3125 
3127 
3130 {
3131 public:
3132  virtual const char* next() = 0;
3133  virtual void reset() = 0;
3134  virtual ~Formatted();
3135 };
3136 
3139 {
3140 public:
3141  enum FormatType {
3142  FMT_DEFAULT = 0,
3143  FMT_MATLAB = 1,
3144  FMT_CSV = 2,
3145  FMT_PYTHON = 3,
3146  FMT_NUMPY = 4,
3147  FMT_C = 5
3148  };
3149 
3150  virtual ~Formatter();
3151 
3152  virtual Ptr<Formatted> format(const Mat& mtx) const = 0;
3153 
3154  virtual void set16fPrecision(int p = 4) = 0;
3155  virtual void set32fPrecision(int p = 8) = 0;
3156  virtual void set64fPrecision(int p = 16) = 0;
3157  virtual void setMultiline(bool ml = true) = 0;
3158 
3159  static Ptr<Formatter> get(Formatter::FormatType fmt = FMT_DEFAULT);
3160 
3161 };
3162 
3163 static inline
3165 {
3166  fmtd->reset();
3167  for(const char* str = fmtd->next(); str; str = fmtd->next())
3168  out += cv::String(str);
3169  return out;
3170 }
3171 
3172 static inline
3173 String& operator << (String& out, const Mat& mtx)
3174 {
3175  return out << Formatter::get()->format(mtx);
3176 }
3177 
3179 
3180 class CV_EXPORTS Algorithm;
3181 
3182 template<typename _Tp, typename _EnumTp = void> struct ParamType {};
3183 
3184 
3197 {
3198 public:
3200  virtual ~Algorithm();
3201 
3204  CV_WRAP virtual void clear() {}
3205 
3208  CV_WRAP virtual void write(FileStorage& fs) const { CV_UNUSED(fs); }
3209 
3213  CV_WRAP void write(FileStorage& fs, const String& name) const;
3214 #if CV_VERSION_MAJOR < 5
3216  void write(const Ptr<FileStorage>& fs, const String& name = String()) const;
3217 #endif
3218 
3221  CV_WRAP virtual void read(const FileNode& fn) { CV_UNUSED(fn); }
3222 
3225  CV_WRAP virtual bool empty() const { return false; }
3226 
3238  template<typename _Tp> static Ptr<_Tp> read(const FileNode& fn)
3239  {
3240  Ptr<_Tp> obj = _Tp::create();
3241  obj->read(fn);
3242  return !obj->empty() ? obj : Ptr<_Tp>();
3243  }
3244 
3257  template<typename _Tp> static Ptr<_Tp> load(const String& filename, const String& objname=String())
3258  {
3260  CV_Assert(fs.isOpened());
3261  FileNode fn = objname.empty() ? fs.getFirstTopLevelNode() : fs[objname];
3262  if (fn.empty()) return Ptr<_Tp>();
3263  Ptr<_Tp> obj = _Tp::create();
3264  obj->read(fn);
3265  return !obj->empty() ? obj : Ptr<_Tp>();
3266  }
3267 
3278  template<typename _Tp> static Ptr<_Tp> loadFromString(const String& strModel, const String& objname=String())
3279  {
3281  FileNode fn = objname.empty() ? fs.getFirstTopLevelNode() : fs[objname];
3282  Ptr<_Tp> obj = _Tp::create();
3283  obj->read(fn);
3284  return !obj->empty() ? obj : Ptr<_Tp>();
3285  }
3286 
3289  CV_WRAP virtual void save(const String& filename) const;
3290 
3293  CV_WRAP virtual String getDefaultName() const;
3294 
3295 protected:
3296  void writeFormat(FileStorage& fs) const;
3297 };
3298 
3299 enum struct Param {
3300  INT=0, BOOLEAN=1, REAL=2, STRING=3, MAT=4, MAT_VECTOR=5, ALGORITHM=6, FLOAT=7,
3301  UNSIGNED_INT=8, UINT64=9, UCHAR=11, SCALAR=12
3302 };
3303 
3304 
3305 
3306 template<> struct ParamType<bool>
3307 {
3308  typedef bool const_param_type;
3309  typedef bool member_type;
3310 
3311  static const Param type = Param::BOOLEAN;
3312 };
3313 
3314 template<> struct ParamType<int>
3315 {
3316  typedef int const_param_type;
3317  typedef int member_type;
3318 
3319  static const Param type = Param::INT;
3320 };
3321 
3322 template<> struct ParamType<double>
3323 {
3324  typedef double const_param_type;
3325  typedef double member_type;
3326 
3327  static const Param type = Param::REAL;
3328 };
3329 
3330 template<> struct ParamType<String>
3331 {
3332  typedef const String& const_param_type;
3334 
3335  static const Param type = Param::STRING;
3336 };
3337 
3338 template<> struct ParamType<Mat>
3339 {
3340  typedef const Mat& const_param_type;
3341  typedef Mat member_type;
3342 
3343  static const Param type = Param::MAT;
3344 };
3345 
3346 template<> struct ParamType<std::vector<Mat> >
3347 {
3350 
3351  static const Param type = Param::MAT_VECTOR;
3352 };
3353 
3354 template<> struct ParamType<Algorithm>
3355 {
3358 
3359  static const Param type = Param::ALGORITHM;
3360 };
3361 
3362 template<> struct ParamType<float>
3363 {
3364  typedef float const_param_type;
3365  typedef float member_type;
3366 
3367  static const Param type = Param::FLOAT;
3368 };
3369 
3370 template<> struct ParamType<unsigned>
3371 {
3372  typedef unsigned const_param_type;
3373  typedef unsigned member_type;
3374 
3376 };
3377 
3378 template<> struct ParamType<uint64>
3379 {
3382 
3383  static const Param type = Param::UINT64;
3384 };
3385 
3386 template<> struct ParamType<uchar>
3387 {
3390 
3391  static const Param type = Param::UCHAR;
3392 };
3393 
3394 template<> struct ParamType<Scalar>
3395 {
3396  typedef const Scalar& const_param_type;
3398 
3399  static const Param type = Param::SCALAR;
3400 };
3401 
3402 template<typename _Tp>
3403 struct ParamType<_Tp, typename std::enable_if< std::is_enum<_Tp>::value >::type>
3404 {
3407 
3408  static const Param type = Param::INT;
3409 };
3410 
3412 
3413 } //namespace cv
3414 
3415 #include "opencv2/core/operations.hpp"
3416 #include "opencv2/core/cvstd.inl.hpp"
3417 #include "opencv2/core/utility.hpp"
3418 #include "opencv2/core/optim.hpp"
3419 #include "opencv2/core/ovx.hpp"
3420 
3421 #endif /*OPENCV_CORE_HPP*/
This is a base class for all more or less complex algorithms in OpenCV.
Definition: core.hpp:3197
virtual CV_WRAP void clear()
Clears the algorithm state.
Definition: core.hpp:3204
static Ptr< _Tp > loadFromString(const String &strModel, const String &objname=String())
Loads algorithm from a String.
Definition: core.hpp:3278
virtual CV_WRAP void write(FileStorage &fs) const
Stores algorithm parameters in a file storage.
Definition: core.hpp:3208
static Ptr< _Tp > load(const String &filename, const String &objname=String())
Loads algorithm from the file.
Definition: core.hpp:3257
void writeFormat(FileStorage &fs) const
virtual CV_WRAP String getDefaultName() const
void write(const Ptr< FileStorage > &fs, const String &name=String()) const
virtual ~Algorithm()
virtual CV_WRAP void read(const FileNode &fn)
Reads algorithm parameters from a file storage.
Definition: core.hpp:3221
CV_WRAP void write(FileStorage &fs, const String &name) const
static Ptr< _Tp > read(const FileNode &fn)
Reads algorithm from the file node.
Definition: core.hpp:3238
virtual CV_WRAP bool empty() const
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
Definition: core.hpp:3225
virtual CV_WRAP void save(const String &filename) const
Class passed to an error.
Definition: core.hpp:115
Exception(int _code, const String &_err, const String &_func, const String &_file, int _line)
virtual ~Exception()
File Storage Node class.
Definition: persistence.hpp:482
CV_WRAP bool empty() const
returns true if the node is empty
XML/YAML/JSON file storage class that encapsulates all the information necessary for writing or readi...
Definition: persistence.hpp:304
CV_WRAP FileNode getFirstTopLevelNode() const
Returns the first element of the top-level mapping.
@ READ
value, open the file for reading
Definition: persistence.hpp:309
@ MEMORY
Definition: persistence.hpp:312
virtual CV_WRAP bool isOpened() const
Checks whether the file is opened.
Definition: core.hpp:3130
virtual void reset()=0
virtual ~Formatted()
virtual const char * next()=0
Definition: core.hpp:3139
virtual ~Formatter()
virtual Ptr< Formatted > format(const Mat &mtx) const =0
static Ptr< Formatter > get(Formatter::FormatType fmt=FMT_DEFAULT)
virtual void set16fPrecision(int p=4)=0
virtual void setMultiline(bool ml=true)=0
FormatType
Definition: core.hpp:3141
virtual void set64fPrecision(int p=16)=0
virtual void set32fPrecision(int p=8)=0
Linear Discriminant Analysis.
Definition: core.hpp:2669
Mat eigenvalues() const
Definition: core.hpp:2723
void lda(InputArrayOfArrays src, InputArray labels)
void save(FileStorage &fs) const
LDA(InputArrayOfArrays src, InputArray labels, int num_components=0)
Mat reconstruct(InputArray src)
void save(const String &filename) const
void compute(InputArrayOfArrays src, InputArray labels)
static Mat subspaceProject(InputArray W, InputArray mean, InputArray src)
LDA(int num_components=0)
constructor Initializes a LDA with num_components (default 0).
Mat eigenvectors() const
Definition: core.hpp:2719
Mat _eigenvectors
Definition: core.hpp:2730
void load(const String &filename)
Mat _eigenvalues
Definition: core.hpp:2731
Mat project(InputArray src)
static Mat subspaceReconstruct(InputArray W, InputArray mean, InputArray src)
void load(const FileStorage &node)
int _num_components
Definition: core.hpp:2729
n-dimensional dense array class
Definition: mat.hpp:812
Template class for small matrices whose type and size are known at compilation time.
Definition: matx.hpp:100
Principal Component Analysis.
Definition: core.hpp:2513
void project(InputArray vec, OutputArray result) const
Mat mean
mean value subtracted before the projection and added after the back projection
Definition: core.hpp:2653
Mat eigenvalues
eigenvalues of the covariation matrix
Definition: core.hpp:2652
PCA & operator()(InputArray data, InputArray mean, int flags, int maxComponents=0)
performs PCA
void backProject(InputArray vec, OutputArray result) const
PCA()
default constructor
PCA(InputArray data, InputArray mean, int flags, int maxComponents=0)
Mat backProject(InputArray vec) const
Reconstructs vectors from their PC projections.
Mat project(InputArray vec) const
Projects vector(s) to the principal component subspace.
void write(FileStorage &fs) const
write PCA objects
Mat eigenvectors
eigenvectors of the covariation matrix
Definition: core.hpp:2651
void read(const FileNode &fn)
load PCA objects
Flags
Definition: core.hpp:2515
PCA(InputArray data, InputArray mean, int flags, double retainedVariance)
PCA & operator()(InputArray data, InputArray mean, int flags, double retainedVariance)
Template class for 2D points specified by its coordinates x and y.
Definition: types.hpp:163
Mersenne Twister random number generator.
Definition: core.hpp:3046
void seed(unsigned s)
int uniform(int a, int b)
returns uniformly distributed integer random number from [a,b) range
float uniform(float a, float b)
returns uniformly distributed floating-point random number from [a,b) range
double uniform(double a, double b)
returns uniformly distributed double-precision floating-point random number from [a,...
RNG_MT19937(unsigned s)
unsigned next()
Random Number Generator.
Definition: core.hpp:2889
RNG()
constructor
RNG(uint64 state)
float uniform(float a, float b)
double uniform(double a, double b)
double gaussian(double sigma)
Returns the next random number sampled from the Gaussian distribution.
uint64 state
Definition: core.hpp:3035
int uniform(int a, int b)
returns uniformly distributed integer random number from [a,b) range
void fill(InputOutputArray mat, int distType, InputArray a, InputArray b, bool saturateRange=false)
Fills arrays with random numbers.
unsigned next()
Singular Value Decomposition.
Definition: core.hpp:2750
SVD()
the default constructor
Flags
Definition: core.hpp:2752
SVD(InputArray src, int flags=0)
static void compute(const Matx< _Tp, m, n > &a, Matx< _Tp, nm, 1 > &w)
static void compute(const Matx< _Tp, m, n > &a, Matx< _Tp, nm, 1 > &w, Matx< _Tp, m, nm > &u, Matx< _Tp, n, nm > &vt)
static void compute(InputArray src, OutputArray w, OutputArray u, OutputArray vt, int flags=0)
decomposes matrix and stores the results to user-provided matrices
static void backSubst(InputArray w, InputArray u, InputArray vt, InputArray rhs, OutputArray dst)
performs back substitution
void backSubst(InputArray rhs, OutputArray dst) const
performs a singular value back substitution.
static void compute(InputArray src, OutputArray w, int flags=0)
static void solveZ(InputArray src, OutputArray dst)
solves an under-determined singular linear system
Mat u
Definition: core.hpp:2873
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)
The class SparseMat represents multi-dimensional sparse numerical arrays.
Definition: mat.hpp:2735
The class defining termination criteria for iterative algorithms.
Definition: types.hpp:886
Definition: mat.hpp:2433
Definition: mat.hpp:387
This type is very similar to InputArray except that it is used for input/output and output function p...
Definition: mat.hpp:296
CV_EXPORTS_AS(calibrateCameraExtended) double calibrateCamera(InputArrayOfArrays objectPoints
Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
InputArrayOfArrays Size InputOutputArray InputOutputArray OutputArrayOfArrays OutputArrayOfArrays OutputArray OutputArray OutputArray int flags
Definition: calib3d.hpp:1617
InputArrayOfArrays InputArrayOfArrays InputOutputArray InputOutputArray InputOutputArray InputOutputArray Size InputOutputArray R
Definition: calib3d.hpp:1867
InputArrayOfArrays Size InputOutputArray InputOutputArray OutputArrayOfArrays OutputArrayOfArrays OutputArray OutputArray OutputArray int TermCriteria criteria
Definition: calib3d.hpp:1617
CV_EXPORTS_W void insertChannel(InputArray src, InputOutputArray dst, int coi)
Inserts a single channel to dst (coi is 0-based index)
CV_EXPORTS_W int borderInterpolate(int p, int len, int borderType)
Computes the source location of an extrapolated pixel.
CV_EXPORTS void minMaxIdx(InputArray src, double *minVal, double *maxVal=0, int *minIdx=0, int *maxIdx=0, InputArray mask=noArray())
Finds the global minimum and maximum in an array.
CV_EXPORTS_W void bitwise_xor(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
Calculates the per-element bit-wise "exclusive or" operation on two arrays or an array and a scalar.
CV_EXPORTS_W void convertScaleAbs(InputArray src, OutputArray dst, double alpha=1, double beta=0)
Scales, calculates absolute values, and converts the result to 8-bit.
CV_EXPORTS_W void PCACompute(InputArray data, InputOutputArray mean, OutputArray eigenvectors, int maxComponents=0)
CV_EXPORTS_W void SVDecomp(InputArray src, OutputArray w, OutputArray u, OutputArray vt, int flags=0)
InputOutputArray OutputArray OutputArray eigenvalues
Definition: core.hpp:2109
CV_EXPORTS_W bool eigen(InputArray src, OutputArray eigenvalues, OutputArray eigenvectors=noArray())
Calculates eigenvalues and eigenvectors of a symmetric matrix.
void CV_EXPORTS_W copyTo(InputArray src, OutputArray dst, InputArray mask)
This is an overloaded member function, provided for convenience (python) Copies the matrix to another...
CV_EXPORTS_W void gemm(InputArray src1, InputArray src2, double alpha, InputArray src3, double beta, OutputArray dst, int flags=0)
Performs generalized matrix multiplication.
CV_EXPORTS_W void reduce(InputArray src, OutputArray dst, int dim, int rtype, int dtype=-1)
Reduces a matrix to a vector.
ReduceTypes
Definition: core.hpp:226
CV_EXPORTS_W double Mahalanobis(InputArray v1, InputArray v2, InputArray icovar)
Calculates the Mahalanobis distance between two vectors.
CV_EXPORTS_W void transform(InputArray src, OutputArray dst, InputArray m)
Performs the matrix transformation of every array element.
CV_EXPORTS void split(const Mat &src, Mat *mvbegin)
Divides a multi-channel array into several single-channel arrays.
CV_EXPORTS_W void mulSpectrums(InputArray a, InputArray b, OutputArray c, int flags, bool conjB=false)
Performs the per-element multiplication of two Fourier spectrums.
CV_EXPORTS_W void polarToCart(InputArray magnitude, InputArray angle, OutputArray x, OutputArray y, bool angleInDegrees=false)
Calculates x and y coordinates of 2D vectors from their magnitude and angle.
CV_EXPORTS_W int solveCubic(InputArray coeffs, OutputArray roots)
Finds the real roots of a cubic equation.
CV_EXPORTS_W void sortIdx(InputArray src, OutputArray dst, int flags)
Sorts each row or each column of a matrix.
CV_EXPORTS void merge(const Mat *mv, size_t count, OutputArray dst)
Creates one multi-channel array out of several single-channel ones.
CV_EXPORTS_W void cartToPolar(InputArray x, InputArray y, OutputArray magnitude, OutputArray angle, bool angleInDegrees=false)
Calculates the magnitude and angle of 2D vectors.
CV_EXPORTS_W void dct(InputArray src, OutputArray dst, int flags=0)
Performs a forward or inverse discrete Cosine transform of 1D or 2D array.
CV_EXPORTS_W void flipND(InputArray src, OutputArray dst, int axis)
Flips a n-dimensional at given axis.
CV_EXPORTS_W void reduceArgMin(InputArray src, OutputArray dst, int axis, bool lastIndex=false)
Finds indices of min elements along provided axis.
CV_EXPORTS_W void completeSymm(InputOutputArray m, bool lowerToUpper=false)
Copies the lower or the upper half of a square matrix to its another half.
CV_EXPORTS_W void SVBackSubst(InputArray w, InputArray u, InputArray vt, InputArray rhs, OutputArray dst)
CV_EXPORTS_W void LUT(InputArray src, InputArray lut, OutputArray dst)
Performs a look-up table transform of an array.
CV_EXPORTS_W void idct(InputArray src, OutputArray dst, int flags=0)
Calculates the inverse Discrete Cosine Transform of a 1D or 2D array.
CV_EXPORTS_W void phase(InputArray x, InputArray y, OutputArray angle, bool angleInDegrees=false)
Calculates the rotation angle of 2D vectors.
CV_EXPORTS_W void reduceArgMax(InputArray src, OutputArray dst, int axis, bool lastIndex=false)
Finds indices of max elements along provided axis.
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())
Finds the global minimum and maximum in an array.
CV_EXPORTS void vconcat(const Mat *src, size_t nsrc, OutputArray dst)
Applies vertical concatenation to given matrices.
CV_EXPORTS_W void eigenNonSymmetric(InputArray src, OutputArray eigenvalues, OutputArray eigenvectors)
Calculates eigenvalues and eigenvectors of a non-symmetric matrix (real eigenvalues only).
CV_EXPORTS_W int getOptimalDFTSize(int vecsize)
Returns the optimal DFT size for a given vector size.
CV_EXPORTS_W void meanStdDev(InputArray src, OutputArray mean, OutputArray stddev, InputArray mask=noArray())
CV_EXPORTS_W void copyMakeBorder(InputArray src, OutputArray dst, int top, int bottom, int left, int right, int borderType, const Scalar &value=Scalar())
Forms a border around an image.
RotateFlags
Definition: core.hpp:1165
CV_EXPORTS_W void compare(InputArray src1, InputArray src2, OutputArray dst, int cmpop)
Performs the per-element comparison of two arrays or an array and scalar value.
InputOutputArray mean
Definition: core.hpp:2108
CV_EXPORTS_W void bitwise_or(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
Calculates the per-element bit-wise disjunction of two arrays or an array and a scalar.
CV_EXPORTS RNG & theRNG()
Returns the default random number generator.
CV_EXPORTS_W void idft(InputArray src, OutputArray dst, int flags=0, int nonzeroRows=0)
Calculates the inverse Discrete Fourier Transform of a 1D or 2D array.
CV_EXPORTS_W int countNonZero(InputArray src)
Counts non-zero array elements.
InputOutputArray OutputArray OutputArray double retainedVariance
Definition: core.hpp:2119
CV_EXPORTS void hconcat(const Mat *src, size_t nsrc, OutputArray dst)
Applies horizontal concatenation to given matrices.
CV_EXPORTS_W void broadcast(InputArray src, InputArray shape, OutputArray dst)
Broadcast the given Mat to the given shape.
CV_EXPORTS void mixChannels(const Mat *src, size_t nsrcs, Mat *dst, size_t ndsts, const int *fromTo, size_t npairs)
Copies specified channels from input arrays to the specified channels of output arrays.
CV_EXPORTS_W void rotate(InputArray src, OutputArray dst, int rotateCode)
Rotates a 2D array in multiples of 90 degrees. The function cv::rotate rotates the array in one of th...
CV_EXPORTS_W void scaleAdd(InputArray src1, double alpha, InputArray src2, OutputArray dst)
Calculates the sum of a scaled array and another array.
CV_EXPORTS_W void repeat(InputArray src, int ny, int nx, OutputArray dst)
Fills the output array with repeated copies of the input array.
CV_EXPORTS_W double invert(InputArray src, OutputArray dst, int flags=DECOMP_LU)
Finds the inverse or pseudo-inverse of a matrix.
CV_EXPORTS_W void magnitude(InputArray x, InputArray y, OutputArray magnitude)
Calculates the magnitude of 2D vectors.
CV_EXPORTS_W void mulTransposed(InputArray src, OutputArray dst, bool aTa, InputArray delta=noArray(), double scale=1, int dtype=-1)
Calculates the product of a matrix and its transposition.
CV_EXPORTS_W bool hasNonZero(InputArray src)
Checks for the presence of at least one non-zero array element.
CV_EXPORTS_W bool solve(InputArray src1, InputArray src2, OutputArray dst, int flags=DECOMP_LU)
Solves one or more linear systems or least-squares problems.
CV_EXPORTS_W void extractChannel(InputArray src, OutputArray dst, int coi)
Extracts a single channel from src (coi is 0-based index)
CV_EXPORTS_W void bitwise_not(InputArray src, OutputArray dst, InputArray mask=noArray())
Inverts every bit of an array.
CV_EXPORTS_W double PSNR(InputArray src1, InputArray src2, double R=255.)
Computes the Peak Signal-to-Noise Ratio (PSNR) image quality metric.
CV_EXPORTS_W void transposeND(InputArray src, const std::vector< int > &order, OutputArray dst)
Transpose for n-dimensional matrices.
CV_EXPORTS_W void sort(InputArray src, OutputArray dst, int flags)
Sorts each row or each column of a matrix.
CV_EXPORTS_W bool checkRange(InputArray a, bool quiet=true, CV_OUT Point *pos=0, double minVal=-DBL_MAX, double maxVal=DBL_MAX)
Checks every element of an input array for invalid values.
CV_EXPORTS_W void PCABackProject(InputArray data, InputArray mean, InputArray eigenvectors, OutputArray result)
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)
naive nearest neighbor finder
CV_EXPORTS_W void flip(InputArray src, OutputArray dst, int flipCode)
Flips a 2D array around vertical, horizontal, or both axes.
CV_EXPORTS_W void absdiff(InputArray src1, InputArray src2, OutputArray dst)
Calculates the per-element absolute difference between two arrays or between an array and a scalar.
CV_EXPORTS_W void randu(InputOutputArray dst, InputArray low, InputArray high)
Generates a single uniformly-distributed random number or an array of random numbers.
CV_EXPORTS_W void transpose(InputArray src, OutputArray dst)
Transposes a matrix.
CV_EXPORTS_W void setIdentity(InputOutputArray mtx, const Scalar &s=Scalar(1))
Initializes a scaled identity matrix.
CV_EXPORTS_W void add(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray(), int dtype=-1)
Calculates the per-element sum of two arrays or an array and a scalar.
CV_EXPORTS_W void randShuffle(InputOutputArray dst, double iterFactor=1., RNG *rng=0)
Shuffles the array elements randomly.
InputOutputArray OutputArray eigenvectors
Definition: core.hpp:2109
CV_EXPORTS_W void divide(InputArray src1, InputArray src2, OutputArray dst, double scale=1, int dtype=-1)
Performs per-element division of two arrays or a scalar by an array.
InputOutputArray OutputArray OutputArray int maxComponents
Definition: core.hpp:2110
CV_EXPORTS_W double solvePoly(InputArray coeffs, OutputArray roots, int maxIters=300)
Finds the real or complex roots of a polynomial equation.
CV_EXPORTS_W void bitwise_and(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
computes bitwise conjunction of the two arrays (dst = src1 & src2) Calculates the per-element bit-wis...
CV_EXPORTS_W void convertFp16(InputArray src, OutputArray dst)
Converts an array to half precision floating number.
CV_EXPORTS_W void inRange(InputArray src, InputArray lowerb, InputArray upperb, OutputArray dst)
Checks if array elements lie between the elements of two other arrays.
CV_EXPORTS_W void findNonZero(InputArray src, OutputArray idx)
Returns the list of locations of non-zero pixels.
CV_EXPORTS_W void randn(InputOutputArray dst, InputArray mean, InputArray stddev)
Fills the array with normally distributed random numbers.
CV_EXPORTS_W void multiply(InputArray src1, InputArray src2, OutputArray dst, double scale=1, int dtype=-1)
Calculates the per-element scaled product of two arrays.
CV_EXPORTS_W void subtract(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray(), int dtype=-1)
Calculates the per-element difference between two arrays or array and a scalar.
CV_EXPORTS_W void patchNaNs(InputOutputArray a, double val=0)
Replaces NaNs by given number.
CV_EXPORTS_W void PCAProject(InputArray data, InputArray mean, InputArray eigenvectors, OutputArray result)
CV_EXPORTS_W void perspectiveTransform(InputArray src, OutputArray dst, InputArray m)
Performs the perspective matrix transformation of vectors.
CV_EXPORTS void calcCovarMatrix(const Mat *samples, int nsamples, Mat &covar, Mat &mean, int flags, int ctype=CV_64F)
Calculates the covariance matrix of a set of vectors.
CV_EXPORTS_W void setRNGSeed(int seed)
Sets state of default random number generator.
CV_EXPORTS_W void dft(InputArray src, OutputArray dst, int flags=0, int nonzeroRows=0)
Performs a forward or inverse Discrete Fourier transform of a 1D or 2D floating-point array.
CV_EXPORTS_W void addWeighted(InputArray src1, double alpha, InputArray src2, double beta, double gamma, OutputArray dst, int dtype=-1)
Calculates the weighted sum of two arrays.
@ REDUCE_SUM
the output is the sum of all rows/columns of the matrix.
Definition: core.hpp:226
@ REDUCE_MIN
the output is the minimum (column/row-wise) of all rows/columns of the matrix.
Definition: core.hpp:229
@ REDUCE_AVG
the output is the mean vector of all rows/columns of the matrix.
Definition: core.hpp:227
@ REDUCE_MAX
the output is the maximum (column/row-wise) of all rows/columns of the matrix.
Definition: core.hpp:228
@ REDUCE_SUM2
the output is the sum of all squared rows/columns of the matrix.
Definition: core.hpp:230
@ ROTATE_90_CLOCKWISE
Rotate 90 degrees clockwise.
Definition: core.hpp:1166
@ ROTATE_90_COUNTERCLOCKWISE
Rotate 270 degrees clockwise.
Definition: core.hpp:1168
@ ROTATE_180
Rotate 180 degrees clockwise.
Definition: core.hpp:1167
@ DECOMP_LU
Definition: base.hpp:135
@ NORM_L2
Definition: base.hpp:185
static double determinant(const Matx< _Tp, m, m > &a)
std::string String
Definition: cvstd.hpp:151
Vec< _Tp, cn > normalize(const Vec< _Tp, cn > &v)
Definition: matx.inl.hpp:952
static double trace(const Matx< _Tp, m, n > &a)
static double norm(const Matx< _Tp, m, n > &M)
Scalar_< double > Scalar
Definition: types.hpp:702
CV_EXPORTS InputOutputArray noArray()
static bool operator==(const Matx< _Tp, m, n > &a, const Matx< _Tp, m, n > &b)
InputArray InputArrayOfArrays
Definition: mat.hpp:443
Param
Definition: core.hpp:3299
CV__DEBUG_NS_END typedef const _InputArray & InputArray
Definition: mat.hpp:442
class CV_EXPORTS Algorithm
Definition: core.hpp:3180
const CvArr * angle
Definition: core_c.h:1194
CvMat * roots
Definition: core_c.h:1263
CvCmpFunc func
Definition: core_c.h:1712
CvArr int order
Definition: core_c.h:1311
int CvScalar value
Definition: core_c.h:720
const CvArr const CvArr const CvArr * src3
Definition: core_c.h:994
CvArr * W
Definition: core_c.h:1335
double const CvArr double beta
Definition: core_c.h:1094
const int * idx
Definition: core_c.h:668
CvArr const CvMat * mat
Definition: core_c.h:1308
CvMemStoragePos * pos
Definition: core_c.h:1573
CvScalar scale
Definition: core_c.h:1088
const CvArr const CvArr * src2
Definition: core_c.h:994
int coi
Definition: core_c.h:172
const CvArr * src1
Definition: core_c.h:993
int int type
Definition: core_c.h:221
CvRNG * rng
Definition: core_c.h:1250
int count
Definition: core_c.h:1413
CvArr const CvArr * lut
Definition: core_c.h:1893
const char const char ** filename
Definition: core_c.h:2630
void * data
Definition: core_c.h:427
const CvArr CvArr * x
Definition: core_c.h:1195
double const CvArr double double gamma
Definition: core_c.h:1095
double alpha
Definition: core_c.h:1093
const CvArr const CvArr CvArr * result
Definition: core_c.h:1423
const CvArr * y
Definition: core_c.h:1187
KmeansFlags
k-Means flags
Definition: core.hpp:209
CV_EXPORTS_W double kmeans(InputArray data, int K, InputOutputArray bestLabels, TermCriteria criteria, int attempts, int flags, OutputArray centers=noArray())
Finds centers of clusters and groups input samples around the clusters.
@ KMEANS_USE_INITIAL_LABELS
Definition: core.hpp:218
@ KMEANS_PP_CENTERS
Definition: core.hpp:213
@ KMEANS_RANDOM_CENTERS
Definition: core.hpp:211
signed char schar
Definition: interface.h:48
#define CV_64F
Definition: interface.h:79
unsigned char uchar
Definition: interface.h:51
unsigned short ushort
Definition: interface.h:52
uint64_t uint64
Definition: interface.h:62
softfloat max(const softfloat &a, const softfloat &b)
Definition: softfloat.hpp:440
softfloat min(const softfloat &a, const softfloat &b)
Min and Max functions.
Definition: softfloat.hpp:437
CV_EXPORTS softfloat pow(const softfloat &a, const softfloat &b)
Raising to the power.
#define CV_EXPORTS
Definition: cvdef.h:435
#define CV_OVERRIDE
Definition: cvdef.h:792
#define CV_OUT
Definition: cvdef.h:478
#define CV_EXPORTS_W
Definition: cvdef.h:472
#define CV_NORETURN
Definition: cvdef.h:735
SortFlags
Definition: core.hpp:153
CV_EXPORTS CV_NORETURN void error(int _code, const String &_err, const char *_func, const char *_file, int _line)
Signals an error and raises the exception.
#define CV_WRAP
Definition: cvdef.h:481
#define CV_Assert(expr)
Checks a condition at runtime and throws exception if it fails.
Definition: base.hpp:342
@ SORT_EVERY_COLUMN
Definition: core.hpp:154
@ SORT_ASCENDING
Definition: core.hpp:157
@ SORT_EVERY_ROW
each matrix row is sorted independently
Definition: core.hpp:153
@ SORT_DESCENDING
Definition: core.hpp:159
CovarFlags
Covariation flags.
Definition: core.hpp:170
Quat< S > sqrt(const Quat< S > &q, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT)
std::ostream & operator<<(std::ostream &, const DualQuat< _Tp > &)
@ COVAR_USE_AVG
Definition: core.hpp:189
@ COVAR_NORMAL
Definition: core.hpp:183
@ COVAR_SCRAMBLED
Definition: core.hpp:178
@ COVAR_COLS
Definition: core.hpp:202
@ COVAR_SCALE
Definition: core.hpp:194
@ COVAR_ROWS
Definition: core.hpp:198
CvArr CvPoint2D32f double M
Definition: imgproc_c.h:270
CvSize int int int CvPoint int delta
Definition: imgproc_c.h:1168
int int int int shape
Definition: imgproc_c.h:301
CvArr int code
Definition: imgproc_c.h:203
CV_EXPORTS_W void line(InputOutputArray img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws a line segment connecting two points.
CV_EXPORTS OutputArray int double double InputArray mask
Definition: imgproc.hpp:2132
InputArray int distType
Definition: imgproc.hpp:3387
OutputArray dst
Definition: imgproc.hpp:3564
OutputArray sum
Definition: imgproc.hpp:2882
OutputArray OutputArray labels
Definition: imgproc.hpp:3565
"black box" representation of the file storage associated with a file on disk.
Definition: calib3d.hpp:441
static CV__DEBUG_NS_BEGIN void swap(MatExpr &a, MatExpr &b)
Definition: mat.inl.hpp:3409
DualQuat< T > power(const DualQuat< T > &dq, const T t, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT)
Definition: dualquaternion.inl.hpp:358
DualQuat< T > log(const DualQuat< T > &dq, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT)
Definition: dualquaternion.inl.hpp:344
DualQuat< T > exp(const DualQuat< T > &dq)
Definition: dualquaternion.inl.hpp:312
Ptr< Algorithm > member_type
Definition: core.hpp:3357
const Ptr< Algorithm > & const_param_type
Definition: core.hpp:3356
Mat member_type
Definition: core.hpp:3341
const Mat & const_param_type
Definition: core.hpp:3340
Scalar member_type
Definition: core.hpp:3397
const Scalar & const_param_type
Definition: core.hpp:3396
const String & const_param_type
Definition: core.hpp:3332
String member_type
Definition: core.hpp:3333
std::underlying_type< _Tp >::type const_param_type
Definition: core.hpp:3405
std::underlying_type< _Tp >::type member_type
Definition: core.hpp:3406
bool const_param_type
Definition: core.hpp:3308
bool member_type
Definition: core.hpp:3309
double member_type
Definition: core.hpp:3325
double const_param_type
Definition: core.hpp:3324
float const_param_type
Definition: core.hpp:3364
float member_type
Definition: core.hpp:3365
int member_type
Definition: core.hpp:3317
int const_param_type
Definition: core.hpp:3316
std::vector< Mat > member_type
Definition: core.hpp:3349
const std::vector< Mat > & const_param_type
Definition: core.hpp:3348
uchar member_type
Definition: core.hpp:3389
uchar const_param_type
Definition: core.hpp:3388
uint64 member_type
Definition: core.hpp:3381
uint64 const_param_type
Definition: core.hpp:3380
unsigned member_type
Definition: core.hpp:3373
unsigned const_param_type
Definition: core.hpp:3372
Definition: core.hpp:3182
Definition: cvstd_wrapper.hpp:74
void reset(const std::true_type &, Y *ptr)
Definition: cvstd_wrapper.hpp:107
bool empty() const
Definition: cvstd_wrapper.hpp:130