class cv::Mat
Overview
ndimensional dense array class More…
#include <mat.hpp> class Mat { public: // enums enum { MAGIC_VAL = 0x42FF0000, AUTO_STEP = 0, CONTINUOUS_FLAG = CV_MAT_CONT_FLAG, SUBMATRIX_FLAG = CV_SUBMAT_FLAG, }; enum { MAGIC_MASK = 0xFFFF0000, TYPE_MASK = 0x00000FFF, DEPTH_MASK = 7, }; // fields MatAllocator* allocator; int cols; uchar* data; const uchar* dataend; const uchar* datalimit; const uchar* datastart; int dims; int flags; int rows; MatSize size; MatStep step; UMatData* u; // construction Mat(); Mat( int rows, int cols, int type ); Mat( Size size, int type ); Mat( int rows, int cols, int type, const Scalar& s ); Mat( Size size, int type, const Scalar& s ); Mat( int ndims, const int* sizes, int type ); Mat( const std::vector<int>& sizes, int type ); Mat( int ndims, const int* sizes, int type, const Scalar& s ); Mat( const std::vector<int>& sizes, int type, const Scalar& s ); Mat(const Mat& m); Mat( int rows, int cols, int type, void* data, size_t step = AUTO_STEP ); Mat( Size size, int type, void* data, size_t step = AUTO_STEP ); Mat( int ndims, const int* sizes, int type, void* data, const size_t* steps = 0 ); Mat( const std::vector<int>& sizes, int type, void* data, const size_t* steps = 0 ); Mat( const Mat& m, const Range& rowRange, const Range& colRange = Range::all() ); Mat( const Mat& m, const Rect& roi ); Mat( const Mat& m, const Range* ranges ); Mat( const Mat& m, const std::vector<Range>& ranges ); template <typename _Tp> Mat( const std::vector<_Tp>& vec, bool copyData = false ); template < typename _Tp, int n > Mat( const Vec<_Tp, n>& vec, bool copyData = true ); template < typename _Tp, int m, int n > Mat( const Matx<_Tp, m, n>& mtx, bool copyData = true ); template <typename _Tp> Mat( const Point_<_Tp>& pt, bool copyData = true ); template <typename _Tp> Mat( const Point3_<_Tp>& pt, bool copyData = true ); template <typename _Tp> Mat(const MatCommaInitializer_<_Tp>& commaInitializer); Mat(const cuda::GpuMat& m); // methods void addref(); Mat& adjustROI( int dtop, int dbottom, int dleft, int dright ); void assignTo( Mat& m, int type = 1 ) const; template <typename _Tp> _Tp& at(int i0 = 0); template <typename _Tp> const _Tp& at(int i0 = 0) const; template <typename _Tp> _Tp& at( int row, int col ); template <typename _Tp> const _Tp& at( int row, int col ) const; template <typename _Tp> _Tp& at( int i0, int i1, int i2 ); template <typename _Tp> const _Tp& at( int i0, int i1, int i2 ) const; template <typename _Tp> _Tp& at(const int* idx); template <typename _Tp> const _Tp& at(const int* idx) const; template < typename _Tp, int n > _Tp& at(const Vec<int, n>& idx); template < typename _Tp, int n > const _Tp& at(const Vec<int, n>& idx) const; template <typename _Tp> _Tp& at(Point pt); template <typename _Tp> const _Tp& at(Point pt) const; template <typename _Tp> MatIterator_<_Tp> begin(); template <typename _Tp> MatConstIterator_<_Tp> begin() const; int channels() const; int checkVector( int elemChannels, int depth = 1, bool requireContinuous = true ) const; Mat clone() const; Mat col(int x) const; Mat colRange( int startcol, int endcol ) const; Mat colRange(const Range& r) const; void convertTo( OutputArray m, int rtype, double alpha = 1, double beta = 0 ) const; void copySize(const Mat& m); void copyTo(OutputArray m) const; void copyTo( OutputArray m, InputArray mask ) const; void create( int rows, int cols, int type ); void create( Size size, int type ); void create( int ndims, const int* sizes, int type ); void create( const std::vector<int>& sizes, int type ); Mat cross(InputArray m) const; void deallocate(); int depth() const; Mat diag(int d = 0) const; double dot(InputArray m) const; size_t elemSize() const; size_t elemSize1() const; bool empty() const; template <typename _Tp> MatIterator_<_Tp> end(); template <typename _Tp> MatConstIterator_<_Tp> end() const; template < typename _Tp, typename Functor > void forEach(const Functor& operation); template < typename _Tp, typename Functor > void forEach(const Functor& operation) const; UMat getUMat( int accessFlags, UMatUsageFlags usageFlags = USAGE_DEFAULT ) const; MatExpr inv(int method = DECOMP_LU) const; bool isContinuous() const; bool isSubmatrix() const; void locateROI( Size& wholeSize, Point& ofs ) const; MatExpr mul( InputArray m, double scale = 1 ) const; template < typename _Tp, int m, int n > operator Matx< _Tp, m, n >() const; template <typename _Tp> operator std::vector< _Tp >() const; template < typename _Tp, int n > operator Vec< _Tp, n >() const; Mat operator()( Range rowRange, Range colRange ) const; Mat operator()(const Rect& roi) const; Mat operator()(const Range* ranges) const; Mat operator()(const std::vector<Range>& ranges) const; Mat& operator=(const Mat& m); Mat& operator=(const MatExpr& expr); Mat& operator=(const Scalar& s); void pop_back(size_t nelems = 1); uchar* ptr(int i0 = 0); const uchar* ptr(int i0 = 0) const; uchar* ptr( int row, int col ); const uchar* ptr( int row, int col ) const; uchar* ptr( int i0, int i1, int i2 ); const uchar* ptr( int i0, int i1, int i2 ) const; uchar* ptr(const int* idx); const uchar* ptr(const int* idx) const; template <int n> uchar* ptr(const Vec<int, n>& idx); template <int n> const uchar* ptr(const Vec<int, n>& idx) const; template <typename _Tp> _Tp* ptr(int i0 = 0); template <typename _Tp> const _Tp* ptr(int i0 = 0) const; template <typename _Tp> _Tp* ptr( int row, int col ); template <typename _Tp> const _Tp* ptr( int row, int col ) const; template <typename _Tp> _Tp* ptr( int i0, int i1, int i2 ); template <typename _Tp> const _Tp* ptr( int i0, int i1, int i2 ) const; template <typename _Tp> _Tp* ptr(const int* idx); template <typename _Tp> const _Tp* ptr(const int* idx) const; template < typename _Tp, int n > _Tp* ptr(const Vec<int, n>& idx); template < typename _Tp, int n > const _Tp* ptr(const Vec<int, n>& idx) const; template <typename _Tp> void push_back(const _Tp& elem); template <typename _Tp> void push_back(const Mat_<_Tp>& elem); void push_back(const Mat& m); void push_back_(const void* elem); void release(); void reserve(size_t sz); void reserveBuffer(size_t sz); Mat reshape( int cn, int rows = 0 ) const; Mat reshape( int cn, int newndims, const int* newsz ) const; Mat reshape( int cn, const std::vector<int>& newshape ) const; void resize(size_t sz); void resize( size_t sz, const Scalar& s ); Mat row(int y) const; Mat rowRange( int startrow, int endrow ) const; Mat rowRange(const Range& r) const; Mat& setTo( InputArray value, InputArray mask = noArray() ); size_t step1(int i = 0) const; MatExpr t() const; size_t total() const; size_t total( int startDim, int endDim = INT_MAX ) const; int type() const; static Mat diag(const Mat& d); static MatExpr eye( int rows, int cols, int type ); static MatExpr eye( Size size, int type ); static MatAllocator* getDefaultAllocator(); static MatAllocator* getStdAllocator(); static MatExpr ones( int rows, int cols, int type ); static MatExpr ones( Size size, int type ); static MatExpr ones( int ndims, const int* sz, int type ); static void setDefaultAllocator(MatAllocator* allocator); static MatExpr zeros( int rows, int cols, int type ); static MatExpr zeros( Size size, int type ); static MatExpr zeros( int ndims, const int* sz, int type ); protected: // methods template < typename _Tp, typename Functor > void forEach_impl(const Functor& operation); }; // direct descendants template <typename _Tp> class Mat_;
Detailed Documentation
ndimensional dense array class
The class Mat represents an ndimensional dense numerical singlechannel or multichannel array. It can be used to store real or complexvalued vectors and matrices, grayscale or color images, voxel volumes, vector fields, point clouds, tensors, histograms (though, very highdimensional histograms may be better stored in a SparseMat). The data layout of the array M
is defined by the array M.step[]
, so that the address of element \((i_0,...,i_{M.dims1})\), where \(0\leq i_k<M.size[k]\), is computed as:
In case of a 2dimensional array, the above formula is reduced to:
Note that M.step[i] >= M.step[i+1]
(in fact, M.step[i] >= M.step[i+1]*M.size[i+1]
). This means that 2dimensional matrices are stored rowbyrow, 3dimensional matrices are stored planebyplane, and so on. M.step[M.dims1] is minimal and always equal to the element size M.elemSize() .
So, the data layout in Mat is fully compatible with CvMat, IplImage, and CvMatND types from OpenCV 1.x. It is also compatible with the majority of dense array types from the standard toolkits and SDKs, such as Numpy (ndarray), Win32 (independent device bitmaps), and others, that is, with any array that uses steps (or strides) to compute the position of a pixel. Due to this compatibility, it is possible to make a Mat header for userallocated data and process it inplace using OpenCV functions.
There are many different ways to create a Mat object. The most popular options are listed below:
Use the create(nrows, ncols, type) method or the similar Mat(nrows, ncols, type[, fillValue]) constructor. A new array of the specified size and type is allocated. type has the same meaning as in the cvCreateMat method. For example, CV_8UC1 means a 8bit singlechannel array, CV_32FC2 means a 2channel (complex) floatingpoint array, and so on.
// make a 7x7 complex matrix filled with 1+3j. Mat M(7,7,CV_32FC2,Scalar(1,3)); // and now turn M to a 100x60 15channel 8bit matrix. // The old content will be deallocated M.create(100,60,CV_8UC(15));
As noted in the introduction to this chapter, create() allocates only a new array when the shape or type of the current array are different from the specified ones.
Create a multidimensional array:
// create a 100x100x100 8bit array int sz[] = {100, 100, 100}; Mat bigCube(3, sz, CV_8U, Scalar::all(0));
It passes the number of dimensions =1 to the Mat constructor but the created array will be 2dimensional with the number of columns set to 1. So, Mat::dims is always >= 2 (can also be 0 when the array is empty).
Use a copy constructor or assignment operator where there can be an array or expression on the right side (see below). As noted in the introduction, the array assignment is an O(1) operation because it only copies the header and increases the reference counter. The Mat::clone() method can be used to get a full (deep) copy of the array when you need it.
Construct a header for a part of another array. It can be a single row, single column, several rows, several columns, rectangular region in the array (called a minor in algebra) or a diagonal. Such operations are also O(1) because the new header references the same data. You can actually modify a part of the array using this feature, for example:
// add the 5th row, multiplied by 3 to the 3rd row M.row(3) = M.row(3) + M.row(5)*3; // now copy the 7th column to the 1st column // M.col(1) = M.col(7); // this will not work Mat M1 = M.col(1); M.col(7).copyTo(M1); // create a new 320x240 image Mat img(Size(320,240),CV_8UC3); // select a ROI Mat roi(img, Rect(10,10,100,100)); // fill the ROI with (0,255,0) (which is green in RGB space); // the original 320x240 image will be modified roi = Scalar(0,255,0);
Due to the additional datastart and dataend members, it is possible to compute a relative subarray position in the main container array using locateROI() :
Mat A = Mat::eye(10, 10, CV_32S); // extracts A columns, 1 (inclusive) to 3 (exclusive). Mat B = A(Range::all(), Range(1, 3)); // extracts B rows, 5 (inclusive) to 9 (exclusive). // that is, C \~ A(Range(5, 9), Range(1, 3)) Mat C = B(Range(5, 9), Range::all()); Size size; Point ofs; C.locateROI(size, ofs); // size will be (width=10,height=10) and the ofs will be (x=1, y=5)
As in case of whole matrices, if you need a deep copy, use the
clone()
method of the extracted submatrices.Make a header for userallocated data. It can be useful to do the following:
Process “foreign” data using OpenCV (for example, when you implement a DirectShow* filter or a processing module for gstreamer, and so on). For example:
void process_video_frame(const unsigned char* pixels, int width, int height, int step) { Mat img(height, width, CV_8UC3, pixels, step); GaussianBlur(img, img, Size(7,7), 1.5, 1.5); }
Quickly initialize small matrices and/or get a superfast element access.
double m[3][3] = {{a, b, c}, {d, e, f}, {g, h, i}}; Mat M = Mat(3, 3, CV_64F, m).inv();
Partial yet very common cases of this userallocated data case are conversions from CvMat and IplImage to Mat. For this purpose, there is function cv::cvarrToMat taking pointers to CvMat or IplImage and the optional flag indicating whether to copy the data or not.
Ptr<IplImage> iplimg(cvLoadImage(imagename.c_str())); // Ptr<T> is safe refcounting pointer class if(!iplimg) { fprintf(stderr, "Can not load image %s\n", imagename.c_str()); return 1; } Mat img = cv::cvarrToMat(iplimg); // cv::Mat replaces the CvMat and IplImage, but it's easy to convert // between the old and the new data structures (by default, only the header // is converted, while the data is shared)
Use MATLABstyle array initializers, zeros(), ones(), eye(), for example:
// create a doubleprecision identity matrix and add it to M. M += Mat::eye(M.rows, M.cols, CV_64F);
Use a commaseparated initializer:
// create a 3x3 doubleprecision identity matrix Mat M = (Mat_<double>(3,3) << 1, 0, 0, 0, 1, 0, 0, 0, 1);
With this approach, you first call a constructor of the Mat class with the proper parameters, and then you just put
<< operator
followed by commaseparated values that can be constants, variables, expressions, and so on. Also, note the extra parentheses required to avoid compilation errors.
Once the array is created, it is automatically managed via a referencecounting mechanism. If the array header is built on top of userallocated data, you should handle the data by yourself. The array data is deallocated when no one points to it. If you want to release the data pointed by a array header before the array destructor is called, use Mat::release().
The next important thing to learn about the array class is element access. This manual already described how to compute an address of each array element. Normally, you are not required to use the formula directly in the code. If you know the array element type (which can be retrieved using the method Mat::type()), you can access the element \(M_{ij}\) of a 2dimensional array as:
M.at<double>(i,j) += 1.f;
assuming that M
is a doubleprecision floatingpoint array. There are several variants of the method at for a different number of dimensions.
If you need to process a whole row of a 2D array, the most efficient way is to get the pointer to the row first, and then just use the plain C operator [] :
// compute sum of positive matrix elements // (assuming that M is a doubleprecision matrix) double sum=0; for(int i = 0; i < M.rows; i++) { const double* Mi = M.ptr<double>(i); for(int j = 0; j < M.cols; j++) sum += std::max(Mi[j], 0.); }
Some operations, like the one above, do not actually depend on the array shape. They just process elements of an array one by one (or elements from multiple arrays that have the same coordinates, for example, array addition). Such operations are called elementwise. It makes sense to check whether all the input/output arrays are continuous, namely, have no gaps at the end of each row. If yes, process them as a long single row:
// compute the sum of positive matrix elements, optimized variant double sum=0; int cols = M.cols, rows = M.rows; if(M.isContinuous()) { cols *= rows; rows = 1; } for(int i = 0; i < rows; i++) { const double* Mi = M.ptr<double>(i); for(int j = 0; j < cols; j++) sum += std::max(Mi[j], 0.); }
In case of the continuous matrix, the outer loop body is executed just once. So, the overhead is smaller, which is especially noticeable in case of small matrices.
Finally, there are STLstyle iterators that are smart enough to skip gaps between successive rows:
// compute sum of positive matrix elements, iteratorbased variant double sum=0; MatConstIterator_<double> it = M.begin<double>(), it_end = M.end<double>(); for(; it != it_end; ++it) sum += std::max(*it, 0.);
The matrix iterators are randomaccess iterators, so they can be passed to any STL algorithm, including std::sort().
Matrix Expressions and arithmetic see MatExpr
Fields
MatAllocator* allocator
custom allocator
uchar* data
pointer to the data
const uchar* datastart
helper fields used in locateROI and adjustROI
int dims
the matrix dimensionality, >= 2
int flags
includes several bitfields:
 the magic signature
 continuity flag
 depth
 number of channels
int rows
the number of rows and columns or (1, 1) when the matrix has more than 2 dimensions
UMatData* u
interaction with UMat
Construction
Mat()
These are various constructors that form a matrix. As noted in the AutomaticAllocation, often the default constructor is enough, and the proper matrix will be allocated by an OpenCV function. The constructed matrix can further be assigned to another matrix or matrix expression or can be allocated with Mat::create. In the former case, the old content is dereferenced.
Mat( int rows, int cols, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
rows  Number of rows in a 2D array. 
cols  Number of columns in a 2D array. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
Mat( Size size, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
size  2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the number of columns go in the reverse order. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
Mat( int rows, int cols, int type, const Scalar& s )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
rows  Number of rows in a 2D array. 
cols  Number of columns in a 2D array. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
s  An optional value to initialize each matrix element with. To set all the matrix elements to the particular value after the construction, use the assignment operator Mat::operator=(const Scalar& value). 
Mat( Size size, int type, const Scalar& s )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
size  2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the number of columns go in the reverse order. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
s  An optional value to initialize each matrix element with. To set all the matrix elements to the particular value after the construction, use the assignment operator Mat::operator=(const Scalar& value). 
Mat( int ndims, const int* sizes, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
ndims  Array dimensionality. 
sizes  Array of integers specifying an ndimensional array shape. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
Mat( const std::vector<int>& sizes, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
sizes  Array of integers specifying an ndimensional array shape. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
Mat( int ndims, const int* sizes, int type, const Scalar& s )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
ndims  Array dimensionality. 
sizes  Array of integers specifying an ndimensional array shape. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
s  An optional value to initialize each matrix element with. To set all the matrix elements to the particular value after the construction, use the assignment operator Mat::operator=(const Scalar& value). 
Mat( const std::vector<int>& sizes, int type, const Scalar& s )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
sizes  Array of integers specifying an ndimensional array shape. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
s  An optional value to initialize each matrix element with. To set all the matrix elements to the particular value after the construction, use the assignment operator Mat::operator=(const Scalar& value). 
Mat(const Mat& m)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
m  Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied by these constructors. Instead, the header pointing to m data or its subarray is constructed and associated with it. The reference counter, if any, is incremented. So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . If you want to have an independent copy of the subarray, use Mat::clone(). 
Mat( int rows, int cols, int type, void* data, size_t step = AUTO_STEP )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
rows  Number of rows in a 2D array. 
cols  Number of columns in a 2D array. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
data  Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. This operation is very efficient and can be used to process external data using OpenCV functions. The external data is not automatically deallocated, so you should take care of it. 
step  Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize(). See Mat::elemSize. 
Mat( Size size, int type, void* data, size_t step = AUTO_STEP )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
size  2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the number of columns go in the reverse order. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
data  Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. This operation is very efficient and can be used to process external data using OpenCV functions. The external data is not automatically deallocated, so you should take care of it. 
step  Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize(). See Mat::elemSize. 
Mat( int ndims, const int* sizes, int type, void* data, const size_t* steps = 0 )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
ndims  Array dimensionality. 
sizes  Array of integers specifying an ndimensional array shape. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
data  Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. This operation is very efficient and can be used to process external data using OpenCV functions. The external data is not automatically deallocated, so you should take care of it. 
steps  Array of ndims1 steps in case of a multidimensional array (the last step is always set to the element size). If not specified, the matrix is assumed to be continuous. 
Mat( const std::vector<int>& sizes, int type, void* data, const size_t* steps = 0 )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
sizes  Array of integers specifying an ndimensional array shape. 
type  Array type. Use CV_8UC1, …, CV_64FC4 to create 14 channel matrices, or CV_8UC(n), …, CV_64FC(n) to create multichannel (up to CV_CN_MAX channels) matrices. 
data  Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. This operation is very efficient and can be used to process external data using OpenCV functions. The external data is not automatically deallocated, so you should take care of it. 
steps  Array of ndims1 steps in case of a multidimensional array (the last step is always set to the element size). If not specified, the matrix is assumed to be continuous. 
Mat( const Mat& m, const Range& rowRange, const Range& colRange = Range::all() )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
m  Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied by these constructors. Instead, the header pointing to m data or its subarray is constructed and associated with it. The reference counter, if any, is incremented. So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . If you want to have an independent copy of the subarray, use Mat::clone(). 
rowRange  Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. Use Range::all() to take all the rows. 
colRange  Range of the m columns to take. Use Range::all() to take all the columns. 
Mat( const Mat& m, const Rect& roi )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
m  Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied by these constructors. Instead, the header pointing to m data or its subarray is constructed and associated with it. The reference counter, if any, is incremented. So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . If you want to have an independent copy of the subarray, use Mat::clone(). 
roi  Region of interest. 
Mat( const Mat& m, const Range* ranges )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
m  Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied by these constructors. Instead, the header pointing to m data or its subarray is constructed and associated with it. The reference counter, if any, is incremented. So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . If you want to have an independent copy of the subarray, use Mat::clone(). 
ranges  Array of selected ranges of m along each dimensionality. 
Mat( const Mat& m, const std::vector<Range>& ranges )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
m  Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied by these constructors. Instead, the header pointing to m data or its subarray is constructed and associated with it. The reference counter, if any, is incremented. So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . If you want to have an independent copy of the subarray, use Mat::clone(). 
ranges  Array of selected ranges of m along each dimensionality. 
template <typename _Tp> Mat( const std::vector<_Tp>& vec, bool copyData = false )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
vec  STL vector whose elements form the matrix. The matrix has a single column and the number of rows equal to the number of vector elements. Type of the matrix matches the type of vector elements. The constructor can handle arbitrary types, for which there is a properly declared DataType. This means that the vector elements must be primitive numbers or unitype numerical tuples of numbers. Mixedtype structures are not supported. The corresponding constructor is explicit. Since STL vectors are not automatically converted to Mat instances, you should write Mat(vec) explicitly. Unless you copy the data into the matrix ( copyData=true ), no new elements will be added to the vector because it can potentially yield vector data reallocation, and, thus, the matrix data pointer will be invalid. 
copyData  Flag to specify whether the underlying data of the STL vector should be copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. 
template < typename _Tp, int n > Mat( const Vec<_Tp, n>& vec, bool copyData = true )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template < typename _Tp, int m, int n > Mat( const Matx<_Tp, m, n>& mtx, bool copyData = true )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> Mat( const Point_<_Tp>& pt, bool copyData = true )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> Mat( const Point3_<_Tp>& pt, bool copyData = true )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> Mat(const MatCommaInitializer_<_Tp>& commaInitializer)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Mat(const cuda::GpuMat& m)
download data from GpuMat
Methods
void addref()
Increments the reference counter.
The method increments the reference counter associated with the matrix data. If the matrix header points to an external data set (see Mat::Mat), the reference counter is NULL, and the method has no effect in this case. Normally, to avoid memory leaks, the method should not be called explicitly. It is called implicitly by the matrix assignment operator. The reference counter increment is an atomic operation on the platforms that support it. Thus, it is safe to operate on the same matrices asynchronously in different threads.
Mat& adjustROI( int dtop, int dbottom, int dleft, int dright )
Adjusts a submatrix size and position within the parent matrix.
The method is complimentary to Mat::locateROI. The typical use of these functions is to determine the submatrix position within the parent matrix and then shift the position somehow. Typically, it can be required for filtering operations when pixels outside of the ROI should be taken into account. When all the method parameters are positive, the ROI needs to grow in all directions by the specified amount, for example:
A.adjustROI(2, 2, 2, 2);
In this example, the matrix size is increased by 4 elements in each direction. The matrix is shifted by 2 elements to the left and 2 elements up, which brings in all the necessary pixels for the filtering with the 5x5 kernel.
adjustROI forces the adjusted ROI to be inside of the parent matrix that is boundaries of the adjusted ROI are constrained by boundaries of the parent matrix. For example, if the submatrix A is located in the first row of a parent matrix and you called A.adjustROI(2, 2, 2, 2) then A will not be increased in the upward direction.
The function is used internally by the OpenCV filtering functions, like filter2D , morphological operations, and so on.
Parameters:
dtop  Shift of the top submatrix boundary upwards. 
dbottom  Shift of the bottom submatrix boundary downwards. 
dleft  Shift of the left submatrix boundary to the left. 
dright  Shift of the right submatrix boundary to the right. 
See also:
void assignTo( Mat& m, int type = 1 ) const
Provides a functional form of convertTo.
This is an internally used method called by the MatrixExpressions engine.
Parameters:
m  Destination array. 
type  Desired destination array depth (or 1 if it should be the same as the source type). 
template <typename _Tp> _Tp& at(int i0 = 0)
Returns a reference to the specified array element.
The template methods return a reference to the specified array element. For the sake of higher performance, the index range checks are only performed in the Debug configuration.
Note that the variants with a single index (i) can be used to access elements of singlerow or singlecolumn 2dimensional arrays. That is, if, for example, A is a 1 x N floatingpoint matrix and B is an M x 1 integer matrix, you can simply write A.at<float>(k+4)
and B.at<int>(2*i+1)
instead of A.at<float>(0,k+4)
and B.at<int>(2*i+1,0)
, respectively.
The example below initializes a Hilbert matrix:
Mat H(100, 100, CV_64F); for(int i = 0; i < H.rows; i++) for(int j = 0; j < H.cols; j++) H.at<double>(i,j)=1./(i+j+1);
Keep in mind that the size identifier used in the at operator cannot be chosen at random. It depends on the image from which you are trying to retrieve the data. The table below gives a better insight in this:
 If matrix is of type
CV_8U
then useMat.at<uchar>(y,x)
.  If matrix is of type
CV_8S
then useMat.at<schar>(y,x)
.  If matrix is of type
CV_16U
then useMat.at<ushort>(y,x)
.  If matrix is of type
CV_16S
then useMat.at<short>(y,x)
.  If matrix is of type
CV_32S
then useMat.at<int>(y,x)
.  If matrix is of type
CV_32F
then useMat.at<float>(y,x)
.  If matrix is of type
CV_64F
then useMat.at<double>(y,x)
.
Parameters:
i0  Index along the dimension 0 
template <typename _Tp> const _Tp& at(int i0 = 0) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
i0  Index along the dimension 0 
template <typename _Tp> _Tp& at( int row, int col )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
row  Index along the dimension 0 
col  Index along the dimension 1 
template <typename _Tp> const _Tp& at( int row, int col ) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
row  Index along the dimension 0 
col  Index along the dimension 1 
template <typename _Tp> _Tp& at( int i0, int i1, int i2 )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
i0  Index along the dimension 0 
i1  Index along the dimension 1 
i2  Index along the dimension 2 
template <typename _Tp> const _Tp& at( int i0, int i1, int i2 ) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
i0  Index along the dimension 0 
i1  Index along the dimension 1 
i2  Index along the dimension 2 
template <typename _Tp> _Tp& at(const int* idx)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
idx  Array of Mat::dims indices. 
template <typename _Tp> const _Tp& at(const int* idx) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
idx  Array of Mat::dims indices. 
template < typename _Tp, int n > _Tp& at(const Vec<int, n>& idx)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template < typename _Tp, int n > const _Tp& at(const Vec<int, n>& idx) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> _Tp& at(Point pt)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. special versions for 2D arrays (especially convenient for referencing image pixels)
Parameters:
pt  Element position specified as Point(j,i) . 
template <typename _Tp> const _Tp& at(Point pt) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. special versions for 2D arrays (especially convenient for referencing image pixels)
Parameters:
pt  Element position specified as Point(j,i) . 
template <typename _Tp> MatIterator_<_Tp> begin()
Returns the matrix iterator and sets it to the first matrix element.
The methods return the matrix readonly or readwrite iterators. The use of matrix iterators is very similar to the use of bidirectional STL iterators. In the example below, the alpha blending function is rewritten using the matrix iterators:
template<typename T> void alphaBlendRGBA(const Mat& src1, const Mat& src2, Mat& dst) { typedef Vec<T, 4> VT; const float alpha_scale = (float)std::numeric_limits<T>::max(), inv_scale = 1.f/alpha_scale; CV_Assert( src1.type() == src2.type() && src1.type() == DataType<VT>::type && src1.size() == src2.size()); Size size = src1.size(); dst.create(size, src1.type()); MatConstIterator_<VT> it1 = src1.begin<VT>(), it1_end = src1.end<VT>(); MatConstIterator_<VT> it2 = src2.begin<VT>(); MatIterator_<VT> dst_it = dst.begin<VT>(); for( ; it1 != it1_end; ++it1, ++it2, ++dst_it ) { VT pix1 = *it1, pix2 = *it2; float alpha = pix1[3]*inv_scale, beta = pix2[3]*inv_scale; *dst_it = VT(saturate_cast<T>(pix1[0]*alpha + pix2[0]*beta), saturate_cast<T>(pix1[1]*alpha + pix2[1]*beta), saturate_cast<T>(pix1[2]*alpha + pix2[2]*beta), saturate_cast<T>((1  (1alpha)*(1beta))*alpha_scale)); } }
int channels() const
Returns the number of matrix channels.
The method returns the number of matrix channels.
int checkVector( int elemChannels, int depth = 1, bool requireContinuous = true ) const
returns N if the matrix is 1channel (N x ptdim) or ptdimchannel (1 x N) or (N x 1); negative number otherwise
Mat clone() const
Creates a full copy of the array and the underlying data.
The method creates a full copy of the array. The original step[] is not taken into account. So, the array copy is a continuous array occupying total() *elemSize() bytes.
Mat col(int x) const
Creates a matrix header for the specified matrix column.
The method makes a new header for the specified matrix column and returns it. This is an O(1) operation, regardless of the matrix size. The underlying data of the new matrix is shared with the original matrix. See also the Mat::row description.
Parameters:
x  A 0based column index. 
Mat colRange( int startcol, int endcol ) const
Creates a matrix header for the specified column span.
The method makes a new header for the specified column span of the matrix. Similarly to Mat::row and Mat::col, this is an O(1) operation.
Parameters:
startcol  An inclusive 0based start index of the column span. 
endcol  An exclusive 0based ending index of the column span. 
Mat colRange(const Range& r) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
r  Range structure containing both the start and the end indices. 
void convertTo( OutputArray m, int rtype, double alpha = 1, double beta = 0 ) const
Converts an array to another data type with optional scaling.
The method converts source pixel values to the target data type. saturate_cast<> is applied at the end to avoid possible overflows:
Parameters:
m  output matrix; if it does not have a proper size or type before the operation, it is reallocated. 
rtype  desired output matrix type or, rather, the depth since the number of channels are the same as the input has; if rtype is negative, the output matrix will have the same type as the input. 
alpha  optional scale factor. 
beta  optional delta added to the scaled values. 
void copySize(const Mat& m)
internal use function; properly reallocates _size, _step arrays
void copyTo(OutputArray m) const
Copies the matrix to another one.
The method copies the matrix data to another matrix. Before copying the data, the method invokes :
m.create(this>size(), this>type());
so that the destination matrix is reallocated if needed. While m.copyTo(m); works flawlessly, the function does not handle the case of a partial overlap between the source and the destination matrices.
When the operation mask is specified, if the Mat::create call shown above reallocates the matrix, the newly allocated matrix is initialized with all zeros before copying the data.
Parameters:
m  Destination matrix. If it does not have a proper size or type before the operation, it is reallocated. 
void copyTo( OutputArray m, InputArray mask ) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
m  Destination matrix. If it does not have a proper size or type before the operation, it is reallocated. 
mask  Operation mask. Its nonzero elements indicate which matrix elements need to be copied. The mask has to be of type CV_8U and can have 1 or multiple channels. 
void create( int rows, int cols, int type )
Allocates new array data if needed.
This is one of the key Mat methods. Most newstyle OpenCV functions and methods that produce arrays call this method for each output array. The method uses the following algorithm:
 If the current array shape and the type match the new ones, return immediately. Otherwise, dereference the previous data by calling Mat::release.
 Initialize the new header.
 Allocate the new data of total() *elemSize() bytes.
 Allocate the new, associated with the data, reference counter and set it to 1.
Such a scheme makes the memory management robust and efficient at the same time and helps avoid extra typing for you. This means that usually there is no need to explicitly allocate output arrays. That is, instead of writing:
Mat color; ... Mat gray(color.rows, color.cols, color.depth()); cvtColor(color, gray, COLOR_BGR2GRAY);
you can simply write:
Mat color; ... Mat gray; cvtColor(color, gray, COLOR_BGR2GRAY);
because cvtColor, as well as the most of OpenCV functions, calls Mat::create() for the output array internally.
Parameters:
rows  New number of rows. 
cols  New number of columns. 
type  New matrix type. 
void create( Size size, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
size  Alternative new matrix size specification: Size(cols, rows) 
type  New matrix type. 
void create( int ndims, const int* sizes, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
ndims  New array dimensionality. 
sizes  Array of integers specifying a new array shape. 
type  New matrix type. 
void create( const std::vector<int>& sizes, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
sizes  Array of integers specifying a new array shape. 
type  New matrix type. 
Mat cross(InputArray m) const
Computes a crossproduct of two 3element vectors.
The method computes a crossproduct of two 3element vectors. The vectors must be 3element floatingpoint vectors of the same shape and size. The result is another 3element vector of the same shape and type as operands.
Parameters:
m  Another crossproduct operand. 
void deallocate()
deallocates the matrix data
int depth() const
Returns the depth of a matrix element.
The method returns the identifier of the matrix element depth (the type of each individual channel). For example, for a 16bit signed element array, the method returns CV_16S . A complete list of matrix types contains the following values:
 CV_8U  8bit unsigned integers ( 0..255 )
 CV_8S  8bit signed integers ( 128..127 )
 CV_16U  16bit unsigned integers ( 0..65535 )
 CV_16S  16bit signed integers ( 32768..32767 )
 CV_32S  32bit signed integers ( 2147483648..2147483647 )
 CV_32F  32bit floatingpoint numbers ( FLT_MAX..FLT_MAX, INF, NAN )
 CV_64F  64bit floatingpoint numbers ( DBL_MAX..DBL_MAX, INF, NAN )
Mat diag(int d = 0) const
Extracts a diagonal from a matrix.
The method makes a new header for the specified matrix diagonal. The new matrix is represented as a singlecolumn matrix. Similarly to Mat::row and Mat::col, this is an O(1) operation.
Parameters:
d  index of the diagonal, with the following values:

double dot(InputArray m) const
Computes a dotproduct of two vectors.
The method computes a dotproduct of two matrices. If the matrices are not singlecolumn or singlerow vectors, the toptobottom lefttoright scan ordering is used to treat them as 1D vectors. The vectors must have the same size and type. If the matrices have more than one channel, the dot products from all the channels are summed together.
Parameters:
m  another dotproduct operand. 
size_t elemSize() const
Returns the matrix element size in bytes.
The method returns the matrix element size in bytes. For example, if the matrix type is CV_16SC3 , the method returns 3*sizeof(short) or 6.
size_t elemSize1() const
Returns the size of each matrix element channel in bytes.
The method returns the matrix element channel size in bytes, that is, it ignores the number of channels. For example, if the matrix type is CV_16SC3 , the method returns sizeof(short) or 2.
bool empty() const
Returns true if the array has no elements.
The method returns true if Mat::total() is 0 or if Mat::data is NULL. Because of pop_back() and resize() methods M.total() == 0
does not imply that M.data == NULL
.
template <typename _Tp> MatIterator_<_Tp> end()
Returns the matrix iterator and sets it to the afterlast matrix element.
The methods return the matrix readonly or readwrite iterators, set to the point following the last matrix element.
template < typename _Tp, typename Functor > void forEach(const Functor& operation)
Runs the given functor over all matrix elements in parallel.
The operation passed as argument has to be a function pointer, a function object or a lambda(C++11).
Example 1. All of the operations below put 0xFF the first channel of all matrix elements:
Mat image(1920, 1080, CV_8UC3); typedef cv::Point3_<uint8_t> Pixel; // first. raw pointer access. for (int r = 0; r < image.rows; ++r) { Pixel* ptr = image.ptr<Pixel>(r, 0); const Pixel* ptr_end = ptr + image.cols; for (; ptr != ptr_end; ++ptr) { ptr>x = 255; } } // Using MatIterator. (Simple but there are a Iterator's overhead) for (Pixel &p : cv::Mat_<Pixel>(image)) { p.x = 255; } // Parallel execution with function object. struct Operator { void operator ()(Pixel &pixel, const int * position) { pixel.x = 255; } }; image.forEach<Pixel>(Operator()); // Parallel execution using C++11 lambda. image.forEach<Pixel>([](Pixel &p, const int * position) > void { p.x = 255; });
Example 2. Using the pixel’s position:
// Creating 3D matrix (255 x 255 x 255) typed uint8_t // and initialize all elements by the value which equals elements position. // i.e. pixels (x,y,z) = (1,2,3) is (b,g,r) = (1,2,3). int sizes[] = { 255, 255, 255 }; typedef cv::Point3_<uint8_t> Pixel; Mat_<Pixel> image = Mat::zeros(3, sizes, CV_8UC3); image.forEach<Pixel>([&](Pixel& pixel, const int position[]) > void { pixel.x = position[0]; pixel.y = position[1]; pixel.z = position[2]; });
template < typename _Tp, typename Functor > void forEach(const Functor& operation) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
UMat getUMat( int accessFlags, UMatUsageFlags usageFlags = USAGE_DEFAULT ) const
MatExpr inv(int method = DECOMP_LU) const
Inverses a matrix.
The method performs a matrix inversion by means of matrix expressions. This means that a temporary matrix inversion object is returned by the method and can be used further as a part of more complex matrix expressions or can be assigned to a matrix.
Parameters:
method  Matrix inversion method. One of cv::DecompTypes 
bool isContinuous() const
Reports whether the matrix is continuous or not.
The method returns true if the matrix elements are stored continuously without gaps at the end of each row. Otherwise, it returns false. Obviously, 1x1 or 1xN matrices are always continuous. Matrices created with Mat::create are always continuous. But if you extract a part of the matrix using Mat::col, Mat::diag, and so on, or constructed a matrix header for externally allocated data, such matrices may no longer have this property.
The continuity flag is stored as a bit in the Mat::flags field and is computed automatically when you construct a matrix header. Thus, the continuity check is a very fast operation, though theoretically it could be done as follows:
// alternative implementation of Mat::isContinuous() bool myCheckMatContinuity(const Mat& m) { //return (m.flags & Mat::CONTINUOUS_FLAG) != 0; return m.rows == 1  m.step == m.cols*m.elemSize(); }
The method is used in quite a few of OpenCV functions. The point is that elementwise operations (such as arithmetic and logical operations, math functions, alpha blending, color space transformations, and others) do not depend on the image geometry. Thus, if all the input and output arrays are continuous, the functions can process them as very long singlerow vectors. The example below illustrates how an alphablending function can be implemented:
template<typename T> void alphaBlendRGBA(const Mat& src1, const Mat& src2, Mat& dst) { const float alpha_scale = (float)std::numeric_limits<T>::max(), inv_scale = 1.f/alpha_scale; CV_Assert( src1.type() == src2.type() && src1.type() == CV_MAKETYPE(DataType<T>::depth, 4) && src1.size() == src2.size()); Size size = src1.size(); dst.create(size, src1.type()); // here is the idiom: check the arrays for continuity and, // if this is the case, // treat the arrays as 1D vectors if( src1.isContinuous() && src2.isContinuous() && dst.isContinuous() ) { size.width *= size.height; size.height = 1; } size.width *= 4; for( int i = 0; i < size.height; i++ ) { // when the arrays are continuous, // the outer loop is executed only once const T* ptr1 = src1.ptr<T>(i); const T* ptr2 = src2.ptr<T>(i); T* dptr = dst.ptr<T>(i); for( int j = 0; j < size.width; j += 4 ) { float alpha = ptr1[j+3]*inv_scale, beta = ptr2[j+3]*inv_scale; dptr[j] = saturate_cast<T>(ptr1[j]*alpha + ptr2[j]*beta); dptr[j+1] = saturate_cast<T>(ptr1[j+1]*alpha + ptr2[j+1]*beta); dptr[j+2] = saturate_cast<T>(ptr1[j+2]*alpha + ptr2[j+2]*beta); dptr[j+3] = saturate_cast<T>((1  (1alpha)*(1beta))*alpha_scale); } } }
This approach, while being very simple, can boost the performance of a simple elementoperation by 1020 percents, especially if the image is rather small and the operation is quite simple.
Another OpenCV idiom in this function, a call of Mat::create for the destination array, that allocates the destination array unless it already has the proper size and type. And while the newly allocated arrays are always continuous, you still need to check the destination array because Mat::create does not always allocate a new matrix.
bool isSubmatrix() const
returns true if the matrix is a submatrix of another matrix
void locateROI( Size& wholeSize, Point& ofs ) const
Locates the matrix header within a parent matrix.
After you extracted a submatrix from a matrix using Mat::row, Mat::col, Mat::rowRange, Mat::colRange, and others, the resultant submatrix points just to the part of the original big matrix. However, each submatrix contains information (represented by datastart and dataend fields) that helps reconstruct the original matrix size and the position of the extracted submatrix within the original matrix. The method locateROI does exactly that.
Parameters:
wholeSize  Output parameter that contains the size of the whole matrix containing this as a part. 
ofs  Output parameter that contains an offset of this inside the whole matrix. 
MatExpr mul( InputArray m, double scale = 1 ) const
Performs an elementwise multiplication or division of the two matrices.
The method returns a temporary object encoding perelement array multiplication, with optional scale. Note that this is not a matrix multiplication that corresponds to a simpler “\*” operator.
Example:
Mat C = A.mul(5/B); // equivalent to divide(A, B, C, 5)
Parameters:
m  Another array of the same type and the same size as *this, or a matrix expression. 
scale  Optional scale factor. 
Mat operator()( Range rowRange, Range colRange ) const
Extracts a rectangular submatrix.
The operators make a new header for the specified subarray of *this . They are the most generalized forms of Mat::row, Mat::col, Mat::rowRange, and Mat::colRange. For example, A(Range(0, 10), Range::all())
is equivalent to A.rowRange(0, 10)
. Similarly to all of the above, the operators are O(1) operations, that is, no matrix data is copied.
Parameters:
rowRange  Start and end row of the extracted submatrix. The upper boundary is not included. To select all the rows, use Range::all(). 
colRange  Start and end column of the extracted submatrix. The upper boundary is not included. To select all the columns, use Range::all(). 
Mat operator()(const Rect& roi) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
roi  Extracted submatrix specified as a rectangle. 
Mat operator()(const Range* ranges) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
ranges  Array of selected ranges along each array dimension. 
Mat operator()(const std::vector<Range>& ranges) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
ranges  Array of selected ranges along each array dimension. 
Mat& operator=(const Mat& m)
assignment operators
These are available assignment operators. Since they all are very different, make sure to read the operator parameters description.
Parameters:
m  Assigned, righthandside matrix. Matrix assignment is an O(1) operation. This means that no data is copied but the data is shared and the reference counter, if any, is incremented. Before assigning new data, the old data is dereferenced via Mat::release. 
Mat& operator=(const MatExpr& expr)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
expr  Assigned matrix expression object. As opposite to the first form of the assignment operation, the second form can reuse already allocated matrix if it has the right size and type to fit the matrix expression result. It is automatically handled by the real function that the matrix expressions is expanded to. For example, C=A+B is expanded to add(A, B, C), and add takes care of automatic C reallocation. 
Mat& operator=(const Scalar& s)
Sets all or some of the array elements to the specified value.
Parameters:
s  Assigned scalar converted to the actual array type. 
void pop_back(size_t nelems = 1)
Removes elements from the bottom of the matrix.
The method removes one or more rows from the bottom of the matrix.
Parameters:
nelems  Number of removed rows. If it is greater than the total number of rows, an exception is thrown. 
uchar* ptr(int i0 = 0)
Returns a pointer to the specified matrix row.
The methods return uchar*
or typed pointer to the specified matrix row. See the sample in Mat::isContinuous to know how to use these methods.
Parameters:
i0  A 0based row index. 
const uchar* ptr(int i0 = 0) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
uchar* ptr( int row, int col )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
row  Index along the dimension 0 
col  Index along the dimension 1 
const uchar* ptr( int row, int col ) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
row  Index along the dimension 0 
col  Index along the dimension 1 
uchar* ptr( int i0, int i1, int i2 )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
const uchar* ptr( int i0, int i1, int i2 ) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
uchar* ptr(const int* idx)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
const uchar* ptr(const int* idx) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <int n> uchar* ptr(const Vec<int, n>& idx)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <int n> const uchar* ptr(const Vec<int, n>& idx) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> _Tp* ptr(int i0 = 0)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> const _Tp* ptr(int i0 = 0) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> _Tp* ptr( int row, int col )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
row  Index along the dimension 0 
col  Index along the dimension 1 
template <typename _Tp> const _Tp* ptr( int row, int col ) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
row  Index along the dimension 0 
col  Index along the dimension 1 
template <typename _Tp> _Tp* ptr( int i0, int i1, int i2 )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> const _Tp* ptr( int i0, int i1, int i2 ) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> _Tp* ptr(const int* idx)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> const _Tp* ptr(const int* idx) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template < typename _Tp, int n > _Tp* ptr(const Vec<int, n>& idx)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template < typename _Tp, int n > const _Tp* ptr(const Vec<int, n>& idx) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
template <typename _Tp> void push_back(const _Tp& elem)
Adds elements to the bottom of the matrix.
The methods add one or more elements to the bottom of the matrix. They emulate the corresponding method of the STL vector class. When elem is Mat, its type and the number of columns must be the same as in the container matrix.
Parameters:
elem  Added element(s). 
template <typename _Tp> void push_back(const Mat_<_Tp>& elem)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
elem  Added element(s). 
void push_back(const Mat& m)
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
m  Added line(s). 
void push_back_(const void* elem)
internal function
void release()
Decrements the reference counter and deallocates the matrix if needed.
The method decrements the reference counter associated with the matrix data. When the reference counter reaches 0, the matrix data is deallocated and the data and the reference counter pointers are set to NULL’s. If the matrix header points to an external data set (see Mat::Mat), the reference counter is NULL, and the method has no effect in this case.
This method can be called manually to force the matrix data deallocation. But since this method is automatically called in the destructor, or by any other method that changes the data pointer, it is usually not needed. The reference counter decrement and check for 0 is an atomic operation on the platforms that support it. Thus, it is safe to operate on the same matrices asynchronously in different threads.
void reserve(size_t sz)
Reserves space for the certain number of rows.
The method reserves space for sz rows. If the matrix already has enough space to store sz rows, nothing happens. If the matrix is reallocated, the first Mat::rows rows are preserved. The method emulates the corresponding method of the STL vector class.
Parameters:
sz  Number of rows. 
void reserveBuffer(size_t sz)
Reserves space for the certain number of bytes.
The method reserves space for sz bytes. If the matrix already has enough space to store sz bytes, nothing happens. If matrix has to be reallocated its previous content could be lost.
Parameters:
sz  Number of bytes. 
Mat reshape( int cn, int rows = 0 ) const
Changes the shape and/or the number of channels of a 2D matrix without copying the data.
The method makes a new matrix header for *this elements. The new matrix may have a different size and/or different number of channels. Any combination is possible if:
 No extra elements are included into the new matrix and no elements are excluded. Consequently, the product rows*cols*channels() must stay the same after the transformation.
 No data is copied. That is, this is an O(1) operation. Consequently, if you change the number of rows, or the operation changes the indices of elements row in some other way, the matrix must be continuous. See Mat::isContinuous.
For example, if there is a set of 3D points stored as an STL vector, and you want to represent the points as a 3xN matrix, do the following:
std::vector<Point3f> vec; ... Mat pointMat = Mat(vec). // convert vector to Mat, O(1) operation reshape(1). // make Nx3 1channel matrix out of Nx1 3channel. // Also, an O(1) operation t(); // finally, transpose the Nx3 matrix. // This involves copying all the elements
Parameters:
cn  New number of channels. If the parameter is 0, the number of channels remains the same. 
rows  New number of rows. If the parameter is 0, the number of rows remains the same. 
Mat reshape( int cn, int newndims, const int* newsz ) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Mat reshape( int cn, const std::vector<int>& newshape ) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
void resize(size_t sz)
Changes the number of matrix rows.
The methods change the number of matrix rows. If the matrix is reallocated, the first min(Mat::rows, sz) rows are preserved. The methods emulate the corresponding methods of the STL vector class.
Parameters:
sz  New number of rows. 
void resize( size_t sz, const Scalar& s )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
sz  New number of rows. 
s  Value assigned to the newly added elements. 
Mat row(int y) const
Creates a matrix header for the specified matrix row.
The method makes a new header for the specified matrix row and returns it. This is an O(1) operation, regardless of the matrix size. The underlying data of the new matrix is shared with the original matrix. Here is the example of one of the classical basic matrix processing operations, axpy, used by LU and many other algorithms:
inline void matrix_axpy(Mat& A, int i, int j, double alpha) { A.row(i) += A.row(j)*alpha; }
In the current implementation, the following code does not work as expected:
Mat A; ... A.row(i) = A.row(j); // will not work
This happens because A.row(i) forms a temporary header that is further assigned to another header. Remember that each of these operations is O(1), that is, no data is copied. Thus, the above assignment is not true if you may have expected the jth row to be copied to the ith row. To achieve that, you should either turn this simple assignment into an expression or use the Mat::copyTo method:
Mat A; ... // works, but looks a bit obscure. A.row(i) = A.row(j) + 0; // this is a bit longer, but the recommended method. A.row(j).copyTo(A.row(i));
Parameters:
y  A 0based row index. 
Mat rowRange( int startrow, int endrow ) const
Creates a matrix header for the specified row span.
The method makes a new header for the specified row span of the matrix. Similarly to Mat::row and Mat::col, this is an O(1) operation.
Parameters:
startrow  An inclusive 0based start index of the row span. 
endrow  An exclusive 0based ending index of the row span. 
Mat rowRange(const Range& r) const
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
r  Range structure containing both the start and the end indices. 
Mat& setTo( InputArray value, InputArray mask = noArray() )
Sets all or some of the array elements to the specified value.
This is an advanced variant of the Mat::operator=(const Scalar& s) operator.
Parameters:
value  Assigned scalar converted to the actual array type. 
mask  Operation mask of the same size as *this. 
size_t step1(int i = 0) const
Returns a normalized step.
The method returns a matrix step divided by Mat::elemSize1(). It can be useful to quickly access an arbitrary matrix element.
MatExpr t() const
Transposes a matrix.
The method performs matrix transposition by means of matrix expressions. It does not perform the actual transposition but returns a temporary matrix transposition object that can be further used as a part of more complex matrix expressions or can be assigned to a matrix:
Mat A1 = A + Mat::eye(A.size(), A.type())*lambda; Mat C = A1.t()*A1; // compute (A + lambda*I)^t * (A + lamda*I)
size_t total() const
Returns the total number of array elements.
The method returns the number of array elements (a number of pixels if the array represents an image).
size_t total( int startDim, int endDim = INT_MAX ) const
Returns the total number of array elements.
The method returns the number of elements within a certain subarray slice with startDim <= dim < endDim
int type() const
Returns the type of a matrix element.
The method returns a matrix element type. This is an identifier compatible with the CvMat type system, like CV_16SC3 or 16bit signed 3channel array, and so on.
static Mat diag(const Mat& d)
creates a diagonal matrix
The method creates a square diagonal matrix from specified main diagonal.
Parameters:
d  Onedimensional matrix that represents the main diagonal. 
static MatExpr eye( int rows, int cols, int type )
Returns an identity matrix of the specified size and type.
The method returns a Matlabstyle identity matrix initializer, similarly to Mat::zeros. Similarly to Mat::ones, you can use a scale operation to create a scaled identity matrix efficiently:
// make a 4x4 diagonal matrix with 0.1's on the diagonal. Mat A = Mat::eye(4, 4, CV_32F)*0.1;
Parameters:
rows  Number of rows. 
cols  Number of columns. 
type  Created matrix type. 
static MatExpr eye( Size size, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
size  Alternative matrix size specification as Size(cols, rows) . 
type  Created matrix type. 
static MatAllocator* getStdAllocator()
and the standard allocator
static MatExpr ones( int rows, int cols, int type )
Returns an array of all 1’s of the specified size and type.
The method returns a Matlabstyle 1’s array initializer, similarly to Mat::zeros. Note that using this method you can initialize an array with an arbitrary value, using the following Matlab idiom:
Mat A = Mat::ones(100, 100, CV_8U)*3; // make 100x100 matrix filled with 3.
The above operation does not form a 100x100 matrix of 1’s and then multiply it by 3. Instead, it just remembers the scale factor (3 in this case) and use it when actually invoking the matrix initializer.
Parameters:
rows  Number of rows. 
cols  Number of columns. 
type  Created matrix type. 
static MatExpr ones( Size size, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
size  Alternative to the matrix size specification Size(cols, rows) . 
type  Created matrix type. 
static MatExpr ones( int ndims, const int* sz, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
ndims  Array dimensionality. 
sz  Array of integers specifying the array shape. 
type  Created matrix type. 
static MatExpr zeros( int rows, int cols, int type )
Returns a zero array of the specified size and type.
The method returns a Matlabstyle zero array initializer. It can be used to quickly form a constant array as a function parameter, part of a matrix expression, or as a matrix initializer. :
Mat A; A = Mat::zeros(3, 3, CV_32F);
In the example above, a new matrix is allocated only if A is not a 3x3 floatingpoint matrix. Otherwise, the existing matrix A is filled with zeros.
Parameters:
rows  Number of rows. 
cols  Number of columns. 
type  Created matrix type. 
static MatExpr zeros( Size size, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
size  Alternative to the matrix size specification Size(cols, rows) . 
type  Created matrix type. 
static MatExpr zeros( int ndims, const int* sz, int type )
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
Parameters:
ndims  Array dimensionality. 
sz  Array of integers specifying the array shape. 
type  Created matrix type. 