Mat (JavaCPP Presets for OpenCV 4.3.0-1.5.3 API)

java.lang.Object
- org.bytedeco.javacpp.Pointer
- - org.bytedeco.opencv.opencv_core.AbstractArray
  - - org.bytedeco.opencv.opencv_core.AbstractMat
    - - org.bytedeco.opencv.opencv_core.Mat

All Implemented Interfaces:

AutoCloseable, Indexable
```
@Namespace(value="cv")
 @NoOffset
 @Properties(inherit=opencv_core.class)
public class Mat
extends AbstractMat
```
\brief n-dimensional dense array class \anchor CVMat_Details
The class Mat represents an n-dimensional dense numerical single-channel or multi-channel array. It can be used to store real or complex-valued vectors and matrices, grayscale or color images, voxel volumes, vector fields, point clouds, tensors, histograms (though, very high-dimensional 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.dims-1}), where 0\leq i_k<M.size[k], is computed as:
```
 \[addr(M_{i_0,...,i_{M.dims-1}}) = M.data + M.step[0]*i_0 + M.step[1]*i_1 + ... + M.step[M.dims-1]*i_{M.dims-1}\]
```
In case of a 2-dimensional array, the above formula is reduced to:
```
 \[addr(M_{i,j}) = M.data + M.step[0]*i + M.step[1]*j\]
```
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 2-dimensional matrices are stored row-by-row, 3-dimensional matrices are stored plane-by-plane, and so on. M.step[M.dims-1] is minimal and always equal to the element size M.elemSize() .
So, the data layout in Mat is 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 user-allocated data and process it in-place 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 8-bit single-channel array, CV_32FC2 means a 2-channel (complex) floating-point 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 15-channel 8-bit 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 multi-dimensional array:
```
    // create a 100x100x100 8-bit 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 2-dimensional 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 5-th row, multiplied by 3 to the 3rd row
    M.row(3) = M.row(3) + M.row(5)*3;
    // now copy the 7-th column to the 1-st 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 sub-array 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 sub-matrices.
- Make a header for user-allocated 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 super-fast element access.
```
        double m[3][3] = {{a, b, c}, {d, e, f}, {g, h, i}};
        Mat M = Mat(3, 3, CV_64F, m).inv();
    
```
.
- Use MATLAB-style array initializers, zeros(), ones(), eye(), for example:
```
    // create a double-precision identity matrix and add it to M.
    M += Mat::eye(M.rows, M.cols, CV_64F);
```
- Use a comma-separated initializer:
```
    // create a 3x3 double-precision 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 comma-separated 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 reference-counting mechanism. If the array header is built on top of user-allocated 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 2-dimensional array as:
```
    M.at<double>(i,j) += 1.f;
```
assuming that M is a double-precision floating-point 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 double-precision 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 *element-wise*. 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 STL-style iterators that are smart enough to skip gaps between successive rows:
```
    // compute sum of positive matrix elements, iterator-based 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 random-access iterators, so they can be passed to any STL algorithm, including std::sort().
\note Matrix Expressions and arithmetic see MatExpr

Nested Class Summary
- Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer
  Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter

Field Summary

Fields
Modifier and Type	Field and Description
`static int`	`AUTO_STEP` enum cv::Mat::
`static int`	`CONTINUOUS_FLAG` enum cv::Mat::
`static int`	`DEPTH_MASK` enum cv::Mat::
`static int`	`MAGIC_MASK` enum cv::Mat::
`static int`	`MAGIC_VAL` enum cv::Mat::
`static int`	`SUBMATRIX_FLAG` enum cv::Mat::
`static int`	`TYPE_MASK` enum cv::Mat::

Fields inherited from class org.bytedeco.opencv.opencv_core.AbstractMat
EMPTY

Fields inherited from class org.bytedeco.javacpp.Pointer
address, capacity, limit, position

Constructor Summary

Constructors
Constructor and Description
`Mat()` These are various constructors that form a matrix.
`Mat(byte... b)`
`Mat(byte[] b, boolean signed)`
`Mat(BytePointer p)`
`Mat(BytePointer p, boolean signed)`
`Mat(CvArr arr)`
`Mat(double... d)`
`Mat(DoublePointer p)`
`Mat(float... f)`
`Mat(FloatPointer p)`
`Mat(GpuMat m)` download data from GpuMat
`Mat(int... n)`
`Mat(int[] sizes, int type)`
`Mat(int[] sizes, int type, Pointer data)`
`Mat(int[] sizes, int type, Pointer data, SizeTPointer steps)`
`Mat(int[] sizes, int type, Scalar s)`
`Mat(IntBuffer sizes, int type)`
`Mat(IntBuffer sizes, int type, Pointer data)`
`Mat(IntBuffer sizes, int type, Pointer data, SizeTPointer steps)`
`Mat(IntBuffer sizes, int type, Scalar s)`
`Mat(int ndims, int[] sizes, int type)`
`Mat(int ndims, int[] sizes, int type, Pointer data)`
`Mat(int ndims, int[] sizes, int type, Pointer data, SizeTPointer steps)`
`Mat(int ndims, int[] sizes, int type, Scalar s)`
`Mat(int ndims, IntBuffer sizes, int type)`
`Mat(int ndims, IntBuffer sizes, int type, Pointer data)`
`Mat(int ndims, IntBuffer sizes, int type, Pointer data, SizeTPointer steps)`
`Mat(int ndims, IntBuffer sizes, int type, Scalar s)`
`Mat(int rows, int cols, int type)` \overload
`Mat(int rows, int cols, int type, Pointer data)`
`Mat(int rows, int cols, int type, Pointer data, long step)` \overload
`Mat(int rows, int cols, int type, Scalar s)` \overload
`Mat(int ndims, IntPointer sizes, int type)` \overload
`Mat(int ndims, IntPointer sizes, int type, Pointer data)`
`Mat(int ndims, IntPointer sizes, int type, Pointer data, SizeTPointer steps)` \overload
`Mat(int ndims, IntPointer sizes, int type, Scalar s)` \overload
`Mat(IntPointer p)`
`Mat(IntPointer sizes, int type)` \overload
`Mat(IntPointer sizes, int type, Pointer data)`
`Mat(IntPointer sizes, int type, Pointer data, SizeTPointer steps)` \overload
`Mat(IntPointer sizes, int type, Scalar s)` \overload
`Mat(long size)` Native array allocator.
`Mat(Mat m)` \overload
`Mat(Mat m, Range rowRange)`
`Mat(Mat m, Range rowRange, Range colRange)` \overload
`Mat(Mat m, Rect roi)` \overload
`Mat(Point points)`
`Mat(Point2d points)`
`Mat(Point2f points)`
`Mat(Point3d points)`
`Mat(Point3f points)`
`Mat(Point3i points)`
`Mat(Pointer p)` Pointer cast constructor.
`Mat(Scalar scalar)`
`Mat(Scalar4i scalar)`
`Mat(short... s)`
`Mat(short[] s, boolean signed)`
`Mat(ShortPointer p)`
`Mat(ShortPointer p, boolean signed)`
`Mat(Size size, int type)` \overload
`Mat(Size size, int type, Pointer data)`
`Mat(Size size, int type, Pointer data, long step)` \overload
`Mat(Size size, int type, Scalar s)` \overload

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`_deallocate()` internal use function, consider to use 'release' method instead; deallocates the matrix data
`void`	`addref()` \brief Increments the reference counter.
`Mat`	`adjustROI(int dtop, int dbottom, int dleft, int dright)` \brief Adjusts a submatrix size and position within the parent matrix.
`MatAllocator`	`allocator()` custom allocator
`Mat`	`allocator(MatAllocator setter)`
`Mat`	`apply(Range ranges)` \overload
`Mat`	`apply(Range rowRange, Range colRange)` \brief Extracts a rectangular submatrix.
`Mat`	`apply(Rect roi)` \overload
`void`	`assignTo(Mat m)`
`void`	`assignTo(Mat m, int type)` \brief Provides a functional form of convertTo.
`int`	`channels()` \brief Returns the number of matrix channels.
`int`	`checkVector(int elemChannels)`
`int`	`checkVector(int elemChannels, int depth, boolean requireContinuous)`
`Mat`	`clone()` \brief Creates a full copy of the array and the underlying data.
`Mat`	`col(int x)` \brief Creates a matrix header for the specified matrix column.
`Mat`	`colRange(int startcol, int endcol)` \brief Creates a matrix header for the specified column span.
`Mat`	`colRange(Range r)` \overload
`int`	`cols()`
`Mat`	`cols(int setter)`
`void`	`convertTo(GpuMat m, int rtype)`
`void`	`convertTo(GpuMat m, int rtype, double alpha, double beta)`
`void`	`convertTo(Mat m, int rtype)`
`void`	`convertTo(Mat m, int rtype, double alpha, double beta)` \brief Converts an array to another data type with optional scaling.
`void`	`convertTo(UMat m, int rtype)`
`void`	`convertTo(UMat m, int rtype, double alpha, double beta)`
`void`	`copySize(Mat m)` internal use function; properly re-allocates _size, _step arrays
`void`	`copyTo(GpuMat m)`
`void`	`copyTo(GpuMat m, GpuMat mask)`
`void`	`copyTo(Mat m)` \brief Copies the matrix to another one.
`void`	`copyTo(Mat m, Mat mask)` \overload
`void`	`copyTo(UMat m)`
`void`	`copyTo(UMat m, UMat mask)`
`void`	`create(int[] sizes, int type)`
`void`	`create(IntBuffer sizes, int type)`
`void`	`create(int ndims, int[] sizes, int type)`
`void`	`create(int ndims, IntBuffer sizes, int type)`
`void`	`create(int rows, int cols, int type)` \brief Allocates new array data if needed.
`void`	`create(int ndims, IntPointer sizes, int type)` \overload
`void`	`create(IntPointer sizes, int type)` \overload
`void`	`create(Size size, int type)` \overload
`Mat`	`cross(GpuMat m)`
`Mat`	`cross(Mat m)` \brief Computes a cross-product of two 3-element vectors.
`Mat`	`cross(UMat m)`
`BytePointer`	`data()` pointer to the data
`Mat`	`data(BytePointer setter)`
`BytePointer`	`dataend()`
`Mat`	`dataend(BytePointer setter)`
`BytePointer`	`datalimit()`
`Mat`	`datalimit(BytePointer setter)`
`BytePointer`	`datastart()` helper fields used in locateROI and adjustROI
`Mat`	`datastart(BytePointer setter)`
`int`	`depth()` \brief Returns the depth of a matrix element.
`Mat`	`diag()`
`Mat`	`diag(int d)` \brief Extracts a diagonal from a matrix
`static Mat`	`diag(Mat d)` \brief creates a diagonal matrix
`int`	`dims()` the matrix dimensionality, >= 2
`Mat`	`dims(int setter)`
`double`	`dot(GpuMat m)`
`double`	`dot(Mat m)` \brief Computes a dot-product of two vectors.
`double`	`dot(UMat m)`
`long`	`elemSize()` \brief Returns the matrix element size in bytes.
`long`	`elemSize1()` \brief Returns the size of each matrix element channel in bytes.
`boolean`	`empty()` \brief Returns true if the array has no elements.
`static MatExpr`	`eye(int rows, int cols, int type)` \brief Returns an identity matrix of the specified size and type.
`static MatExpr`	`eye(Size size, int type)` \overload
`int`	`flags()` includes several bit-fields: - the magic signature - continuity flag - depth - number of channels
`Mat`	`flags(int setter)`
`static MatAllocator`	`getDefaultAllocator()`
`static MatAllocator`	`getStdAllocator()` and the standard allocator
`UMat`	`getUMat(int accessFlags)`
`UMat`	`getUMat(int accessFlags, int usageFlags)` retrieve UMat from Mat
`MatExpr`	`inv()`
`MatExpr`	`inv(int method)` \brief Inverses a matrix.
`boolean`	`isContinuous()` \brief Reports whether the matrix is continuous or not.
`boolean`	`isSubmatrix()` returns true if the matrix is a submatrix of another matrix
`void`	`locateROI(Size wholeSize, Point ofs)` \brief Locates the matrix header within a parent matrix.
`MatExpr`	`mul(GpuMat m)`
`MatExpr`	`mul(GpuMat m, double scale)`
`MatExpr`	`mul(Mat m)`
`MatExpr`	`mul(Mat m, double scale)` \brief Performs an element-wise multiplication or division of the two matrices.
`MatExpr`	`mul(UMat m)`
`MatExpr`	`mul(UMat m, double scale)`
`static MatExpr`	`ones(int rows, int cols, int type)` \brief Returns an array of all 1's of the specified size and type.
`static MatExpr`	`ones(Size size, int type)` \overload
`void`	`pop_back()`
`void`	`pop_back(long nelems)` \brief Removes elements from the bottom of the matrix.
`Mat`	`position(long position)`
`BytePointer`	`ptr()`
`BytePointer`	`ptr(int i0)` \brief Returns a pointer to the specified matrix row.
`byte[]`	`ptr(int[] idx)`
`ByteBuffer`	`ptr(IntBuffer idx)`
`BytePointer`	`ptr(int row, int col)` \overload
`BytePointer`	`ptr(int i0, int i1, int i2)` \overload
`BytePointer`	`ptr(IntPointer idx)` \overload
`void`	`push_back_(Pointer elem)` internal function
`void`	`push_back(Mat m)` \overload
`Mat`	`put(Mat m)` \brief assignment operators
`Mat`	`put(MatExpr expr)` \overload
`Mat`	`put(Scalar s)` \brief Sets all or some of the array elements to the specified value.
`void`	`release()` \brief Decrements the reference counter and deallocates the matrix if needed.
`void`	`reserve(long sz)` \brief Reserves space for the certain number of rows.
`void`	`reserveBuffer(long sz)` \brief Reserves space for the certain number of bytes.
`Mat`	`reshape(int cn)`
`Mat`	`reshape(int cn, int rows)` \brief Changes the shape and/or the number of channels of a 2D matrix without copying the data.
`Mat`	`reshape(int cn, int[] newshape)`
`Mat`	`reshape(int cn, IntBuffer newshape)`
`Mat`	`reshape(int cn, int newndims, int[] newsz)`
`Mat`	`reshape(int cn, int newndims, IntBuffer newsz)`
`Mat`	`reshape(int cn, int newndims, IntPointer newsz)` \overload
`Mat`	`reshape(int cn, IntPointer newshape)` \overload
`void`	`resize(long sz)` \brief Changes the number of matrix rows.
`void`	`resize(long sz, Scalar s)` \overload
`Mat`	`row(int y)` \brief Creates a matrix header for the specified matrix row.
`Mat`	`rowRange(int startrow, int endrow)` \brief Creates a matrix header for the specified row span.
`Mat`	`rowRange(Range r)` \overload
`int`	`rows()` the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
`Mat`	`rows(int setter)`
`static void`	`setDefaultAllocator(MatAllocator allocator)`
`Mat`	`setTo(GpuMat value)`
`Mat`	`setTo(GpuMat value, GpuMat mask)`
`Mat`	`setTo(Mat value)`
`Mat`	`setTo(Mat value, Mat mask)` \brief Sets all or some of the array elements to the specified value.
`Mat`	`setTo(UMat value)`
`Mat`	`setTo(UMat value, UMat mask)`
`Size`	`size()`
`int`	`size(int i)`
`long`	`step()`
`long`	`step(int i)`
`long`	`step1()`
`long`	`step1(int i)` \brief Returns a normalized step.
`MatExpr`	`t()` \brief Transposes a matrix.
`long`	`total()` \brief Returns the total number of array elements.
`long`	`total(int startDim)`
`long`	`total(int startDim, int endDim)` \brief Returns the total number of array elements.
`int`	`type()` \brief Returns the type of a matrix element.
`UMatData`	`u()` interaction with UMat
`Mat`	`u(UMatData setter)`
`void`	`updateContinuityFlag()` internal use method: updates the continuity flag
`static MatExpr`	`zeros(int rows, int cols, int type)` \brief Returns a zero array of the specified size and type.
`static MatExpr`	`zeros(Size size, int type)` \overload

Methods inherited from class org.bytedeco.opencv.opencv_core.AbstractMat
arrayChannels, arrayData, arrayDepth, arrayHeight, arrayOrigin, arrayOrigin, arrayROI, arraySize, arrayStep, arrayWidth, createIndexer

Methods inherited from class org.bytedeco.opencv.opencv_core.AbstractArray
createBuffer, createBuffer, createIndexer, cvSize, getByteBuffer, getByteBuffer, getDoubleBuffer, getDoubleBuffer, getFloatBuffer, getFloatBuffer, getIntBuffer, getIntBuffer, getShortBuffer, getShortBuffer, highValue, toString

Methods inherited from class org.bytedeco.javacpp.Pointer
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object
finalize, getClass, notify, notifyAll, wait, wait, wait

- Field Detail
  - MAGIC_VAL
```
public static final int MAGIC_VAL
```
    enum cv::Mat::
    
    See Also:
    
    Constant Field Values
  - AUTO_STEP
```
public static final int AUTO_STEP
```
    enum cv::Mat::
    
    See Also:
    
    Constant Field Values
  - CONTINUOUS_FLAG
```
public static final int CONTINUOUS_FLAG
```
    enum cv::Mat::
    
    See Also:
    
    Constant Field Values
  - SUBMATRIX_FLAG
```
public static final int SUBMATRIX_FLAG
```
    enum cv::Mat::
    
    See Also:
    
    Constant Field Values
  - MAGIC_MASK
```
public static final int MAGIC_MASK
```
    enum cv::Mat::
    
    See Also:
    
    Constant Field Values
  - TYPE_MASK
```
public static final int TYPE_MASK
```
    enum cv::Mat::
    
    See Also:
    
    Constant Field Values
  - DEPTH_MASK
```
public static final int DEPTH_MASK
```
    enum cv::Mat::
    
    See Also:
    
    Constant Field Values
- Constructor Detail
  - Mat
```
public Mat(Pointer p)
```
    Pointer cast constructor. Invokes Pointer.Pointer(Pointer).
  - Mat
```
public Mat(long size)
```
    Native array allocator. Access with Pointer.position(long).
  - Mat
```
public 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 de-referenced.
  - Mat
```
public Mat(int rows,
           int cols,
           int type)
```
    \overload
    
    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 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
  - Mat
```
public Mat(@ByVal
           Size size,
           int type)
```
    \overload
    
    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 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
  - Mat
```
public Mat(int rows,
           int cols,
           int type,
           @Const @ByRef
           Scalar s)
```
    \overload
    
    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 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (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
```
public Mat(@ByVal
           Size size,
           int type,
           @Const @ByRef
           Scalar s)
```
    \overload
    
    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 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (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
```
public Mat(int ndims,
           @Const
           IntPointer sizes,
           int type)
```
    \overload
    
    Parameters:
    
    ndims - Array dimensionality.
    
    sizes - Array of integers specifying an n-dimensional array shape.
    
    type - Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
  - Mat
```
public Mat(int ndims,
           @Const
           IntBuffer sizes,
           int type)
```
  - Mat
```
public Mat(int ndims,
           @Const
           int[] sizes,
           int type)
```
  - Mat
```
public Mat(@StdVector
           IntPointer sizes,
           int type)
```
    \overload
    
    Parameters:
    
    sizes - Array of integers specifying an n-dimensional array shape.
    
    type - Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
  - Mat
```
public Mat(@StdVector
           IntBuffer sizes,
           int type)
```
  - Mat
```
public Mat(@StdVector
           int[] sizes,
           int type)
```
  - Mat
```
public Mat(int ndims,
           @Const
           IntPointer sizes,
           int type,
           @Const @ByRef
           Scalar s)
```
    \overload
    
    Parameters:
    
    ndims - Array dimensionality.
    
    sizes - Array of integers specifying an n-dimensional array shape.
    
    type - Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (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
```
public Mat(int ndims,
           @Const
           IntBuffer sizes,
           int type,
           @Const @ByRef
           Scalar s)
```
  - Mat
```
public Mat(int ndims,
           @Const
           int[] sizes,
           int type,
           @Const @ByRef
           Scalar s)
```
  - Mat
```
public Mat(@StdVector
           IntPointer sizes,
           int type,
           @Const @ByRef
           Scalar s)
```
    \overload
    
    Parameters:
    
    sizes - Array of integers specifying an n-dimensional array shape.
    
    type - Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (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
```
public Mat(@StdVector
           IntBuffer sizes,
           int type,
           @Const @ByRef
           Scalar s)
```
  - Mat
```
public Mat(@StdVector
           int[] sizes,
           int type,
           @Const @ByRef
           Scalar s)
```
  - Mat
```
public Mat(@Const @ByRef
           Mat m)
```
    \overload
    
    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 sub-array 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 sub-array, use Mat::clone() .
  - Mat
```
public Mat(int rows,
           int cols,
           int type,
           Pointer data,
           @Cast(value="size_t")
           long step)
```
    \overload
    
    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 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (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
```
public Mat(int rows,
           int cols,
           int type,
           Pointer data)
```
  - Mat
```
public Mat(CvArr arr)
```
  - Mat
```
public Mat(Point points)
```
  - Mat
```
public Mat(Point2f points)
```
  - Mat
```
public Mat(Point2d points)
```
  - Mat
```
public Mat(Point3i points)
```
  - Mat
```
public Mat(Point3f points)
```
  - Mat
```
public Mat(Point3d points)
```
  - Mat
```
public Mat(Scalar scalar)
```
  - Mat
```
public Mat(Scalar4i scalar)
```
  - Mat
```
public Mat(byte... b)
```
  - Mat
```
public Mat(byte[] b,
           boolean signed)
```
  - Mat
```
public Mat(short... s)
```
  - Mat
```
public Mat(short[] s,
           boolean signed)
```
  - Mat
```
public Mat(int... n)
```
  - Mat
```
public Mat(double... d)
```
  - Mat
```
public Mat(float... f)
```
  - Mat
```
public Mat(BytePointer p)
```
  - Mat
```
public Mat(BytePointer p,
           boolean signed)
```
  - Mat
```
public Mat(ShortPointer p)
```
  - Mat
```
public Mat(ShortPointer p,
           boolean signed)
```
  - Mat
```
public Mat(IntPointer p)
```
  - Mat
```
public Mat(FloatPointer p)
```
  - Mat
```
public Mat(DoublePointer p)
```
  - Mat
```
public Mat(@ByVal
           Size size,
           int type,
           Pointer data,
           @Cast(value="size_t")
           long step)
```
    \overload
    
    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 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (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
```
public Mat(@ByVal
           Size size,
           int type,
           Pointer data)
```
  - Mat
```
public Mat(int ndims,
           @Const
           IntPointer sizes,
           int type,
           Pointer data,
           @Cast(value="const size_t*")
           SizeTPointer steps)
```
    \overload
    
    Parameters:
    
    ndims - Array dimensionality.
    
    sizes - Array of integers specifying an n-dimensional array shape.
    
    type - Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (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 ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). If not specified, the matrix is assumed to be continuous.
  - Mat
```
public Mat(int ndims,
           @Const
           IntPointer sizes,
           int type,
           Pointer data)
```
  - Mat
```
public Mat(int ndims,
           @Const
           IntBuffer sizes,
           int type,
           Pointer data,
           @Cast(value="const size_t*")
           SizeTPointer steps)
```
  - Mat
```
public Mat(int ndims,
           @Const
           IntBuffer sizes,
           int type,
           Pointer data)
```
  - Mat
```
public Mat(int ndims,
           @Const
           int[] sizes,
           int type,
           Pointer data,
           @Cast(value="const size_t*")
           SizeTPointer steps)
```
  - Mat
```
public Mat(int ndims,
           @Const
           int[] sizes,
           int type,
           Pointer data)
```
  - Mat
```
public Mat(@StdVector
           IntPointer sizes,
           int type,
           Pointer data,
           @Cast(value="const size_t*")
           SizeTPointer steps)
```
    \overload
    
    Parameters:
    
    sizes - Array of integers specifying an n-dimensional array shape.
    
    type - Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (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 ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). If not specified, the matrix is assumed to be continuous.
  - Mat
```
public Mat(@StdVector
           IntPointer sizes,
           int type,
           Pointer data)
```
  - Mat
```
public Mat(@StdVector
           IntBuffer sizes,
           int type,
           Pointer data,
           @Cast(value="const size_t*")
           SizeTPointer steps)
```
  - Mat
```
public Mat(@StdVector
           IntBuffer sizes,
           int type,
           Pointer data)
```
  - Mat
```
public Mat(@StdVector
           int[] sizes,
           int type,
           Pointer data,
           @Cast(value="const size_t*")
           SizeTPointer steps)
```
  - Mat
```
public Mat(@StdVector
           int[] sizes,
           int type,
           Pointer data)
```
  - Mat
```
public Mat(@Const @ByRef
           Mat m,
           @Const @ByRef
           Range rowRange,
           @Const @ByRef(nullValue="cv::Range::all()")
           Range colRange)
```
    \overload
    
    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 sub-array 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 sub-array, 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
```
public Mat(@Const @ByRef
           Mat m,
           @Const @ByRef
           Range rowRange)
```
  - Mat
```
public Mat(@Const @ByRef
           Mat m,
           @Const @ByRef
           Rect roi)
```
    \overload
    
    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 sub-array 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 sub-array, use Mat::clone() .
    
    roi - Region of interest.
  - Mat
```
public Mat(@Const @ByRef
           GpuMat m)
```
    download data from GpuMat
- Method Detail
  - position
```
public Mat position(long position)
```
    Overrides:
    
    position in class Pointer
  - put
```
@ByRef
 @Name(value="operator =")
public Mat put(@Const @ByRef
                                                 Mat m)
```
    \brief assignment operators
    These are available assignment operators. Since they all are very different, make sure to read the operator parameters description.
    
    Parameters:
    
    m - Assigned, right-hand-side 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 de-referenced via Mat::release .
  - put
```
@ByRef
 @Name(value="operator =")
public Mat put(@Const @ByRef
                                                 MatExpr expr)
```
    \overload
    
    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.
  - getUMat
```
@ByVal
public UMat getUMat(@Cast(value="cv::AccessFlag")
                           int accessFlags,
                           @Cast(value="cv::UMatUsageFlags")
                           int usageFlags)
```
    retrieve UMat from Mat
  - getUMat
```
@ByVal
public UMat getUMat(@Cast(value="cv::AccessFlag")
                           int accessFlags)
```
  - row
```
@ByVal
public Mat row(int y)
```
    \brief 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;
        }
    
```
    \note 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 j-th row to be copied to the i-th 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 0-based row index.
  - col
```
@ByVal
public Mat col(int x)
```
    \brief 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 0-based column index.
  - rowRange
```
@ByVal
public Mat rowRange(int startrow,
                           int endrow)
```
    \brief 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 0-based start index of the row span.
    
    endrow - An exclusive 0-based ending index of the row span.
  - rowRange
```
@ByVal
public Mat rowRange(@Const @ByRef
                           Range r)
```
    \overload
    
    Parameters:
    
    r - Range structure containing both the start and the end indices.
  - colRange
```
@ByVal
public Mat colRange(int startcol,
                           int endcol)
```
    \brief 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 0-based start index of the column span.
    
    endcol - An exclusive 0-based ending index of the column span.
  - colRange
```
@ByVal
public Mat colRange(@Const @ByRef
                           Range r)
```
    \overload
    
    Parameters:
    
    r - Range structure containing both the start and the end indices.
  - diag
```
@ByVal
public Mat diag(int d)
```
    \brief Extracts a diagonal from a matrix
    The method makes a new header for the specified matrix diagonal. The new matrix is represented as a single-column matrix. Similarly to Mat::row and Mat::col, this is an O(1) operation.
    Parameters:
    d - index of the diagonal, with the following values: - d=0 is the main diagonal. - d<0 is a diagonal from the lower half. For example, d=-1 means the diagonal is set immediately below the main one. - d>0 is a diagonal from the upper half. For example, d=1 means the diagonal is set immediately above the main one. For example:
    Mat m = (Mat_<int>(3,3) << 1,2,3, 4,5,6, 7,8,9); Mat d0 = m.diag(0); Mat d1 = m.diag(1); Mat d_1 = m.diag(-1);
    The resulting matrices are
    d0 = [1; 5; 9] d1 = [2; 6] d_1 = [4; 8]
  - diag
```
@ByVal
public Mat diag()
```
  - diag
```
@ByVal
public static Mat diag(@Const @ByRef
                              Mat d)
```
    \brief creates a diagonal matrix
    The method creates a square diagonal matrix from specified main diagonal.
    
    Parameters:
    
    d - One-dimensional matrix that represents the main diagonal.
  - clone
```
@ByVal
public Mat clone()
```
    \brief 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.
    
    Overrides:
    
    clone in class Object
  - copyTo
```
public void copyTo(@ByVal
                   Mat m)
```
    \brief 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.
  - copyTo
```
public void copyTo(@ByVal
                   UMat m)
```
  - copyTo
```
public void copyTo(@ByVal
                   GpuMat m)
```
  - copyTo
```
public void copyTo(@ByVal
                   Mat m,
                   @ByVal
                   Mat mask)
```
    \overload
    
    Parameters:
    
    m - Destination matrix. If it does not have a proper size or type before the operation, it is reallocated.
    
    mask - Operation mask of the same size as \*this. Its non-zero 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.
  - copyTo
```
public void copyTo(@ByVal
                   UMat m,
                   @ByVal
                   UMat mask)
```
  - copyTo
```
public void copyTo(@ByVal
                   GpuMat m,
                   @ByVal
                   GpuMat mask)
```
  - convertTo
```
public void convertTo(@ByVal
                      Mat m,
                      int rtype,
                      double alpha,
                      double beta)
```
    \brief 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:
```
 \[m(x,y) = saturate \_ cast<rType>( \alpha (*this)(x,y) +  \beta )\]
```
    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.
  - convertTo
```
public void convertTo(@ByVal
                      Mat m,
                      int rtype)
```
  - convertTo
```
public void convertTo(@ByVal
                      UMat m,
                      int rtype,
                      double alpha,
                      double beta)
```
  - convertTo
```
public void convertTo(@ByVal
                      UMat m,
                      int rtype)
```
  - convertTo
```
public void convertTo(@ByVal
                      GpuMat m,
                      int rtype,
                      double alpha,
                      double beta)
```
  - convertTo
```
public void convertTo(@ByVal
                      GpuMat m,
                      int rtype)
```
  - assignTo
```
public void assignTo(@ByRef
                     Mat m,
                     int type)
```
    \brief Provides a functional form of convertTo.
    This is an internally used method called by the \ref MatrixExpressions engine.
    
    Parameters:
    
    m - Destination array.
    
    type - Desired destination array depth (or -1 if it should be the same as the source type).
  - assignTo
```
public void assignTo(@ByRef
                     Mat m)
```
  - put
```
@ByRef
 @Name(value="operator =")
public Mat put(@Const @ByRef
                                                 Scalar s)
```
    \brief Sets all or some of the array elements to the specified value.
    
    Parameters:
    
    s - Assigned scalar converted to the actual array type.
  - setTo
```
@ByRef
public Mat setTo(@ByVal
                        Mat value,
                        @ByVal(nullValue="cv::InputArray(cv::noArray())")
                        Mat mask)
```
    \brief 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. Its non-zero 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
  - setTo
```
@ByRef
public Mat setTo(@ByVal
                        Mat value)
```
  - setTo
```
@ByRef
public Mat setTo(@ByVal
                        UMat value,
                        @ByVal(nullValue="cv::InputArray(cv::noArray())")
                        UMat mask)
```
  - setTo
```
@ByRef
public Mat setTo(@ByVal
                        UMat value)
```
  - setTo
```
@ByRef
public Mat setTo(@ByVal
                        GpuMat value,
                        @ByVal(nullValue="cv::InputArray(cv::noArray())")
                        GpuMat mask)
```
  - setTo
```
@ByRef
public Mat setTo(@ByVal
                        GpuMat value)
```
  - reshape
```
@ByVal
public Mat reshape(int cn,
                          int rows)
```
    \brief 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 1-channel matrix out of Nx1 3-channel.
                                      // 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.
  - reshape
```
@ByVal
public Mat reshape(int cn)
```
  - reshape
```
@ByVal
public Mat reshape(int cn,
                          int newndims,
                          @Const
                          IntPointer newsz)
```
    \overload
  - reshape
```
@ByVal
public Mat reshape(int cn,
                          int newndims,
                          @Const
                          IntBuffer newsz)
```
  - reshape
```
@ByVal
public Mat reshape(int cn,
                          int newndims,
                          @Const
                          int[] newsz)
```
  - reshape
```
@ByVal
public Mat reshape(int cn,
                          @StdVector
                          IntPointer newshape)
```
    \overload
  - reshape
```
@ByVal
public Mat reshape(int cn,
                          @StdVector
                          IntBuffer newshape)
```
  - reshape
```
@ByVal
public Mat reshape(int cn,
                          @StdVector
                          int[] newshape)
```
  - t
```
@ByVal
public MatExpr t()
```
    \brief 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)
    
```
  - inv
```
@ByVal
public MatExpr inv(int method)
```
    \brief 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
  - inv
```
@ByVal
public MatExpr inv()
```
  - mul
```
@ByVal
public MatExpr mul(@ByVal
                          Mat m,
                          double scale)
```
    \brief Performs an element-wise multiplication or division of the two matrices.
    The method returns a temporary object encoding per-element 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.
  - mul
```
@ByVal
public MatExpr mul(@ByVal
                          Mat m)
```
  - mul
```
@ByVal
public MatExpr mul(@ByVal
                          UMat m,
                          double scale)
```
  - mul
```
@ByVal
public MatExpr mul(@ByVal
                          UMat m)
```
  - mul
```
@ByVal
public MatExpr mul(@ByVal
                          GpuMat m,
                          double scale)
```
  - mul
```
@ByVal
public MatExpr mul(@ByVal
                          GpuMat m)
```
  - cross
```
@ByVal
public Mat cross(@ByVal
                        Mat m)
```
    \brief Computes a cross-product of two 3-element vectors.
    The method computes a cross-product of two 3-element vectors. The vectors must be 3-element floating-point vectors of the same shape and size. The result is another 3-element vector of the same shape and type as operands.
    
    Parameters:
    
    m - Another cross-product operand.
  - cross
```
@ByVal
public Mat cross(@ByVal
                        UMat m)
```
  - cross
```
@ByVal
public Mat cross(@ByVal
                        GpuMat m)
```
  - dot
```
public double dot(@ByVal
                  Mat m)
```
    \brief Computes a dot-product of two vectors.
    The method computes a dot-product of two matrices. If the matrices are not single-column or single-row vectors, the top-to-bottom left-to-right 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 dot-product operand.
  - dot
```
public double dot(@ByVal
                  UMat m)
```
  - dot
```
public double dot(@ByVal
                  GpuMat m)
```
  - zeros
```
@ByVal
public static MatExpr zeros(int rows,
                                   int cols,
                                   int type)
```
    \brief Returns a zero array of the specified size and type.
    The method returns a Matlab-style 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 floating-point matrix. Otherwise, the existing matrix A is filled with zeros.
    Parameters:
    
    rows - Number of rows.
    
    cols - Number of columns.
    
    type - Created matrix type.
  - zeros
```
@ByVal
public static MatExpr zeros(@ByVal
                                   Size size,
                                   int type)
```
    \overload
    
    Parameters:
    
    size - Alternative to the matrix size specification Size(cols, rows) .
    
    type - Created matrix type.
  - ones
```
@ByVal
public static MatExpr ones(int rows,
                                  int cols,
                                  int type)
```
    \brief Returns an array of all 1's of the specified size and type.
    The method returns a Matlab-style 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. \note In case of multi-channels type, only the first channel will be initialized with 1's, the others will be set to 0's.
    Parameters:
    
    rows - Number of rows.
    
    cols - Number of columns.
    
    type - Created matrix type.
  - ones
```
@ByVal
public static MatExpr ones(@ByVal
                                  Size size,
                                  int type)
```
    \overload
    
    Parameters:
    
    size - Alternative to the matrix size specification Size(cols, rows) .
    
    type - Created matrix type.
  - eye
```
@ByVal
public static MatExpr eye(int rows,
                                 int cols,
                                 int type)
```
    \brief Returns an identity matrix of the specified size and type.
    The method returns a Matlab-style 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;
    
```
    \note In case of multi-channels type, identity matrix will be initialized only for the first channel, the others will be set to 0's
    Parameters:
    
    rows - Number of rows.
    
    cols - Number of columns.
    
    type - Created matrix type.
  - eye
```
@ByVal
public static MatExpr eye(@ByVal
                                 Size size,
                                 int type)
```
    \overload
    
    Parameters:
    
    size - Alternative matrix size specification as Size(cols, rows) .
    
    type - Created matrix type.
  - create
```
public void create(int rows,
                   int cols,
                   int type)
```
    \brief Allocates new array data if needed.
    This is one of the key Mat methods. Most new-style 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, de-reference 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.
    Specified by:
    
    create in class AbstractMat
    
    Parameters:
    
    rows - New number of rows.
    
    cols - New number of columns.
    
    type - New matrix type.
  - create
```
public void create(@ByVal
                   Size size,
                   int type)
```
    \overload
    
    Parameters:
    
    size - Alternative new matrix size specification: Size(cols, rows)
    
    type - New matrix type.
  - create
```
public void create(int ndims,
                   @Const
                   IntPointer sizes,
                   int type)
```
    \overload
    
    Parameters:
    
    ndims - New array dimensionality.
    
    sizes - Array of integers specifying a new array shape.
    
    type - New matrix type.
  - create
```
public void create(int ndims,
                   @Const
                   IntBuffer sizes,
                   int type)
```
  - create
```
public void create(int ndims,
                   @Const
                   int[] sizes,
                   int type)
```
  - create
```
public void create(@StdVector
                   IntPointer sizes,
                   int type)
```
    \overload
    
    Parameters:
    
    sizes - Array of integers specifying a new array shape.
    
    type - New matrix type.
  - create
```
public void create(@StdVector
                   IntBuffer sizes,
                   int type)
```
  - create
```
public void create(@StdVector
                   int[] sizes,
                   int type)
```
  - addref
```
public void addref()
```
    \brief 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.
  - release
```
public void release()
```
    \brief 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.
    
    Specified by:
    
    release in class AbstractMat
  - _deallocate
```
@Name(value="deallocate")
public void _deallocate()
```
    internal use function, consider to use 'release' method instead; deallocates the matrix data
  - copySize
```
public void copySize(@Const @ByRef
                     Mat m)
```
    internal use function; properly re-allocates _size, _step arrays
  - reserve
```
public void reserve(@Cast(value="size_t")
                    long sz)
```
    \brief 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.
  - reserveBuffer
```
public void reserveBuffer(@Cast(value="size_t")
                          long sz)
```
    \brief 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.
  - resize
```
public void resize(@Cast(value="size_t")
                   long sz)
```
    \brief 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.
  - resize
```
public void resize(@Cast(value="size_t")
                   long sz,
                   @Const @ByRef
                   Scalar s)
```
    \overload
    
    Parameters:
    
    sz - New number of rows.
    
    s - Value assigned to the newly added elements.
  - push_back_
```
public void push_back_(@Const
                       Pointer elem)
```
    internal function
  - push_back
```
public void push_back(@Const @ByRef
                      Mat m)
```
    \overload
    
    Parameters:
    
    m - Added line(s).
  - pop_back
```
public void pop_back(@Cast(value="size_t")
                     long nelems)
```
    \brief 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.
  - pop_back
```
public void pop_back()
```
  - locateROI
```
public void locateROI(@ByRef
                      Size wholeSize,
                      @ByRef
                      Point ofs)
```
    \brief 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.
  - adjustROI
```
@ByRef
public Mat adjustROI(int dtop,
                            int dbottom,
                            int dleft,
                            int dright)
```
    \brief 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:
    
    copyMakeBorder
  - apply
```
@ByVal
 @Name(value="operator ()")
public Mat apply(@ByVal
                                                    Range rowRange,
                                                    @ByVal
                                                    Range colRange)
```
    \brief Extracts a rectangular submatrix.
    The operators make a new header for the specified sub-array 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().
  - apply
```
@ByVal
 @Name(value="operator ()")
public Mat apply(@Const @ByRef
                                                    Rect roi)
```
    \overload
    
    Parameters:
    
    roi - Extracted submatrix specified as a rectangle.
  - apply
```
@ByVal
 @Name(value="operator ()")
public Mat apply(@Const
                                                    Range ranges)
```
    \overload
    
    Parameters:
    
    ranges - Array of selected ranges along each array dimension.
  - isContinuous
```
@Cast(value="bool")
public boolean isContinuous()
```
    \brief 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 element-wise 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 single-row vectors. The example below illustrates how an alpha-blending 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(traits::Depth<T>::value, 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 - (1-alpha)*(1-beta))*alpha_scale);
                }
            }
        }
    
```
    This approach, while being very simple, can boost the performance of a simple element-operation by 10-20 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.
  - isSubmatrix
```
@Cast(value="bool")
public boolean isSubmatrix()
```
    returns true if the matrix is a submatrix of another matrix
  - elemSize
```
@Cast(value="size_t")
public long elemSize()
```
    \brief 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.
  - elemSize1
```
@Cast(value="size_t")
public long elemSize1()
```
    \brief 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.
    
    Specified by:
    
    elemSize1 in class AbstractMat
  - type
```
public int type()
```
    \brief 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 16-bit signed 3-channel array, and so on.
    
    Specified by:
    
    type in class AbstractMat
  - depth
```
public int depth()
```
    \brief 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 16-bit signed element array, the method returns CV_16S . A complete list of matrix types contains the following values: - CV_8U - 8-bit unsigned integers ( 0..255 ) - CV_8S - 8-bit signed integers ( -128..127 ) - CV_16U - 16-bit unsigned integers ( 0..65535 ) - CV_16S - 16-bit signed integers ( -32768..32767 ) - CV_32S - 32-bit signed integers ( -2147483648..2147483647 ) - CV_32F - 32-bit floating-point numbers ( -FLT_MAX..FLT_MAX, INF, NAN ) - CV_64F - 64-bit floating-point numbers ( -DBL_MAX..DBL_MAX, INF, NAN )
    
    Specified by:
    
    depth in class AbstractMat
  - channels
```
public int channels()
```
    \brief Returns the number of matrix channels.
    The method returns the number of matrix channels.
    
    Specified by:
    
    channels in class AbstractMat
  - step1
```
@Cast(value="size_t")
public long step1(int i)
```
    \brief 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.
  - step1
```
@Cast(value="size_t")
public long step1()
```
  - empty
```
@Cast(value="bool")
public boolean empty()
```
    \brief 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.
  - total
```
@Cast(value="size_t")
public long total()
```
    \brief 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).
  - total
```
@Cast(value="size_t")
public long total(int startDim,
                                        int endDim)
```
    \brief Returns the total number of array elements.
    The method returns the number of elements within a certain sub-array slice with startDim <= dim < endDim
  - total
```
@Cast(value="size_t")
public long total(int startDim)
```
  - checkVector
```
public int checkVector(int elemChannels,
                       int depth,
                       @Cast(value="bool")
                       boolean requireContinuous)
```
    Parameters:
    
    elemChannels - Number of channels or number of columns the matrix should have. For a 2-D matrix, when the matrix has only 1 column, then it should have elemChannels channels; When the matrix has only 1 channel, then it should have elemChannels columns. For a 3-D matrix, it should have only one channel. Furthermore, if the number of planes is not one, then the number of rows within every plane has to be 1; if the number of rows within every plane is not 1, then the number of planes has to be 1.
    
    depth - The depth the matrix should have. Set it to -1 when any depth is fine.
    
    requireContinuous - Set it to true to require the matrix to be continuous
    
    Returns:
    
    -1 if the requirement is not satisfied. Otherwise, it returns the number of elements in the matrix. Note that an element may have multiple channels. The following code demonstrates its usage for a 2-d matrix: \snippet snippets/core_mat_checkVector.cpp example-2d The following code demonstrates its usage for a 3-d matrix: \snippet snippets/core_mat_checkVector.cpp example-3d
  - checkVector
```
public int checkVector(int elemChannels)
```
  - ptr
```
@Cast(value="uchar*")
public BytePointer ptr(int i0)
```
    \brief 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 0-based row index.
  - ptr
```
@Cast(value="uchar*")
public BytePointer ptr()
```
  - ptr
```
@Cast(value="uchar*")
public BytePointer ptr(int row,
                                             int col)
```
    \overload
    
    Parameters:
    
    row - Index along the dimension 0
    
    col - Index along the dimension 1
  - ptr
```
@Cast(value="uchar*")
public BytePointer ptr(int i0,
                                             int i1,
                                             int i2)
```
    \overload
  - ptr
```
@Cast(value="uchar*")
public BytePointer ptr(@Const
                                             IntPointer idx)
```
    \overload
  - ptr
```
@Cast(value="uchar*")
public ByteBuffer ptr(@Const
                                            IntBuffer idx)
```
  - ptr
```
@Cast(value="uchar*")
public byte[] ptr(@Const
                                        int[] idx)
```
  - flags
```
public int flags()
```
    includes several bit-fields: - the magic signature - continuity flag - depth - number of channels
  - flags
```
public Mat flags(int setter)
```
  - dims
```
public int dims()
```
    the matrix dimensionality, >= 2
    
    Specified by:
    
    dims in class AbstractMat
  - dims
```
public Mat dims(int setter)
```
  - rows
```
public int rows()
```
    the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
    
    Specified by:
    
    rows in class AbstractMat
  - rows
```
public Mat rows(int setter)
```
  - cols
```
public int cols()
```
    Specified by:
    
    cols in class AbstractMat
  - cols
```
public Mat cols(int setter)
```
  - data
```
@Cast(value="uchar*")
public BytePointer data()
```
    pointer to the data
    
    Specified by:
    
    data in class AbstractMat
  - data
```
public Mat data(BytePointer setter)
```
  - datastart
```
@Cast(value="const uchar*")
public BytePointer datastart()
```
    helper fields used in locateROI and adjustROI
  - datastart
```
public Mat datastart(BytePointer setter)
```
  - dataend
```
@Cast(value="const uchar*")
public BytePointer dataend()
```
  - dataend
```
public Mat dataend(BytePointer setter)
```
  - datalimit
```
@Cast(value="const uchar*")
public BytePointer datalimit()
```
  - datalimit
```
public Mat datalimit(BytePointer setter)
```
  - allocator
```
public MatAllocator allocator()
```
    custom allocator
  - allocator
```
public Mat allocator(MatAllocator setter)
```
  - getStdAllocator
```
public static MatAllocator getStdAllocator()
```
    and the standard allocator
  - getDefaultAllocator
```
public static MatAllocator getDefaultAllocator()
```
  - setDefaultAllocator
```
public static void setDefaultAllocator(MatAllocator allocator)
```
  - updateContinuityFlag
```
public void updateContinuityFlag()
```
    internal use method: updates the continuity flag
  - u
```
public UMatData u()
```
    interaction with UMat
  - u
```
public Mat u(UMatData setter)
```
  - size
```
@ByVal
public Size size()
```
  - size
```
@MemberGetter
public int size(int i)
```
    Specified by:
    
    size in class AbstractMat
  - step
```
@MemberGetter
public long step()
```
  - step
```
@MemberGetter
public long step(int i)
```
    Specified by:
    
    step in class AbstractMat

Class Mat

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Field Summary

Fields inherited from class org.bytedeco.opencv.opencv_core.AbstractMat

Fields inherited from class org.bytedeco.javacpp.Pointer

Constructor Summary

Method Summary

Methods inherited from class org.bytedeco.opencv.opencv_core.AbstractMat

Methods inherited from class org.bytedeco.opencv.opencv_core.AbstractArray

Methods inherited from class org.bytedeco.javacpp.Pointer

Methods inherited from class java.lang.Object

Field Detail

MAGIC_VAL

AUTO_STEP

CONTINUOUS_FLAG

SUBMATRIX_FLAG

MAGIC_MASK

TYPE_MASK

DEPTH_MASK

Constructor Detail

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