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org.opencv.core
Class Mat

java.lang.Object
  org.opencv.core.Mat

Direct Known Subclasses:: MatOfByte, MatOfDMatch, MatOfDouble, MatOfFloat, MatOfFloat4, MatOfFloat6, MatOfInt, MatOfInt4, MatOfKeyPoint, MatOfPoint, MatOfPoint2f, MatOfPoint3, MatOfPoint3f, MatOfRect

public class Mat
extends java.lang.Object
extends java.lang.Object

OpenCV C++ n-dimensional dense array class

class CV_EXPORTS Mat



 // C++ code:


 public:

 //... a lot of methods......

 / *! includes several bit-fields:

 - the magic signature

 - continuity flag

 - depth

 - number of channels
 
    /
 

 int flags;

 //! the array dimensionality, >= 2

 int dims;

 //! the number of rows and columns or (-1, -1) when the array has more than 2
 dimensions

 int rows, cols;

 //! pointer to the data

 uchar* data;

 //! pointer to the reference counter;

 // when array points to user-allocated data, the pointer is NULL

 int* refcount;

 // other members...

 };

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 <= 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 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 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.



 // C++ code:

 // 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:



 // C++ code:

 // 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:



 // C++ code:

 // 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():



 // C++ code:

 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:



 // C++ code:

 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.



 // C++ code:

 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 *user-allocated data* case are conversions from CvMat and IplImage to Mat. For this purpose, there are special constructors taking pointers to CvMat or IplImage and the optional flag indicating whether to copy the data or not.

Backward conversion from Mat to CvMat or IplImage is provided via cast operators Mat.operator CvMat() const and Mat.operator IplImage(). The operators do NOT copy the data.



 // C++ code:

 IplImage* img = cvLoadImage("greatwave.jpg", 1);

 Mat mtx(img); // convert IplImage* -> Mat

 CvMat oldmat = mtx; // convert Mat -> CvMat

 CV_Assert(oldmat.cols == img->width && oldmat.rows == img->height &&

 oldmat.data.ptr == (uchar*)img->imageData && oldmat.step == img->widthStep);

Use MATLAB-style array initializers, zeros(), ones(), eye(), for example:



 // C++ code:

 // create a double-precision identity martix and add it to M.

 M += Mat.eye(M.rows, M.cols, CV_64F);

Use a comma-separated initializer:



 // C++ code:

 // create a 3x3 double-precision identity matrix

 Mat M = (Mat_(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 elementM_(ij) of a 2-dimensional array as:



 // C++ code:

 M.at(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 [] :



 // C++ code:

 // compute sum of positive matrix elements

 // (assuming that M isa double-precision matrix)

 double sum=0;

 for(int i = 0; i < M.rows; i++)


 const double* Mi = M.ptr(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(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:



 // C++ code:

 // compute sum of positive matrix elements, iterator-based variant

 double sum=0;

 MatConstIterator_ it = M.begin(), it_end = M.end();

 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:

An example demonstrating the serial out capabilities of cv.Mat can be found at opencv_source_code/samples/cpp/cout_mat.cpp

See Also:: org.opencv.core.Mat

Field Summary
`long`	`nativeObj`

Constructor Summary
`Mat()` Various Mat constructors
`Mat(int rows, int cols, int type)` Various Mat constructors
`Mat(int rows, int cols, int type, Scalar s)` Various Mat constructors
`Mat(long addr)`
`Mat(Mat m, Range rowRange)` Various Mat constructors
`Mat(Mat m, Range rowRange, Range colRange)` Various Mat constructors
`Mat(Mat m, Rect roi)` Various Mat constructors
`Mat(Size size, int type)` Various Mat constructors
`Mat(Size size, int type, Scalar s)` Various Mat constructors

Method Summary
`Mat`	`adjustROI(int dtop, int dbottom, int dleft, int dright)` Adjusts a submatrix size and position within the parent matrix.
`void`	`assignTo(Mat m)` Provides a functional form of `convertTo`.
`void`	`assignTo(Mat m, int type)` Provides a functional form of `convertTo`.
`int`	`channels()` Returns the number of matrix channels.
`int`	`checkVector(int elemChannels)`
`int`	`checkVector(int elemChannels, int depth)`
`int`	`checkVector(int elemChannels, int depth, boolean requireContinuous)`
`Mat`	`clone()` Creates a full copy of the array and the underlying data.
`Mat`	`col(int x)` Creates a matrix header for the specified matrix column.
`Mat`	`colRange(int startcol, int endcol)` Creates a matrix header for the specified column span.
`Mat`	`colRange(Range r)` Creates a matrix header for the specified column span.
`int`	`cols()`
`void`	`convertTo(Mat m, int rtype)` Converts an array to another data type with optional scaling.
`void`	`convertTo(Mat m, int rtype, double alpha)` Converts an array to another data type with optional scaling.
`void`	`convertTo(Mat m, int rtype, double alpha, double beta)` Converts an array to another data type with optional scaling.
`void`	`copyTo(Mat m)` Copies the matrix to another one.
`void`	`copyTo(Mat m, Mat mask)` Copies the matrix to another one.
`void`	`create(int rows, int cols, int type)` Allocates new array data if needed.
`void`	`create(Size size, int type)` Allocates new array data if needed.
`Mat`	`cross(Mat m)` Computes a cross-product of two 3-element vectors.
`long`	`dataAddr()`
`int`	`depth()` Returns the depth of a matrix element.
`Mat`	`diag()` Extracts a diagonal from a matrix, or creates a diagonal matrix.
`Mat`	`diag(int d)` Extracts a diagonal from a matrix, or creates a diagonal matrix.
`static Mat`	`diag(Mat d)` Extracts a diagonal from a matrix, or creates a diagonal matrix.
`int`	`dims()`
`double`	`dot(Mat m)` Computes a dot-product of two vectors.
`java.lang.String`	`dump()`
`long`	`elemSize()` Returns the matrix element size in bytes.
`long`	`elemSize1()` Returns the size of each matrix element channel in bytes.
`boolean`	`empty()` Returns `true` if the array has no elements.
`static Mat`	`eye(int rows, int cols, int type)` Returns an identity matrix of the specified size and type.
`static Mat`	`eye(Size size, int type)` Returns an identity matrix of the specified size and type.
`double[]`	`get(int row, int col)`
`int`	`get(int row, int col, byte[] data)`
`int`	`get(int row, int col, double[] data)`
`int`	`get(int row, int col, float[] data)`
`int`	`get(int row, int col, int[] data)`
`int`	`get(int row, int col, short[] data)`
`long`	`getNativeObjAddr()`
`int`	`height()`
`Mat`	`inv()` Inverses a matrix.
`Mat`	`inv(int method)` Inverses a matrix.
`boolean`	`isContinuous()` Reports whether the matrix is continuous or not.
`boolean`	`isSubmatrix()`
`void`	`locateROI(Size wholeSize, Point ofs)` Locates the matrix header within a parent matrix.
`Mat`	`mul(Mat m)` Performs an element-wise multiplication or division of the two matrices.
`Mat`	`mul(Mat m, double scale)` Performs an element-wise multiplication or division of the two matrices.
`static Mat`	`ones(int rows, int cols, int type)` Returns an array of all 1's of the specified size and type.
`static Mat`	`ones(Size size, int type)` Returns an array of all 1's of the specified size and type.
`void`	`push_back(Mat m)` Adds elements to the bottom of the matrix.
`int`	`put(int row, int col, byte[] data)`
`int`	`put(int row, int col, double... data)`
`int`	`put(int row, int col, float[] data)`
`int`	`put(int row, int col, int[] data)`
`int`	`put(int row, int col, short[] data)`
`void`	`release()` Decrements the reference counter and deallocates the matrix if needed.
`Mat`	`reshape(int cn)` Changes the shape and/or the number of channels of a 2D matrix without copying the data.
`Mat`	`reshape(int cn, int rows)` Changes the shape and/or the number of channels of a 2D matrix without copying the data.
`Mat`	`row(int y)` Creates a matrix header for the specified matrix row.
`Mat`	`rowRange(int startrow, int endrow)` Creates a matrix header for the specified row span.
`Mat`	`rowRange(Range r)` Creates a matrix header for the specified row span.
`int`	`rows()`
`Mat`	`setTo(Mat value)` Sets all or some of the array elements to the specified value.
`Mat`	`setTo(Mat value, Mat mask)` Sets all or some of the array elements to the specified value.
`Mat`	`setTo(Scalar s)`
`Mat`	`setTo(Scalar value, Mat mask)` Sets all or some of the array elements to the specified value.
`Size`	`size()` Returns a matrix size.
`long`	`step1()` Returns a normalized step.
`long`	`step1(int i)` Returns a normalized step.
`Mat`	`submat(int rowStart, int rowEnd, int colStart, int colEnd)` Extracts a rectangular submatrix.
`Mat`	`submat(Range rowRange, Range colRange)` Extracts a rectangular submatrix.
`Mat`	`submat(Rect roi)` Extracts a rectangular submatrix.
`Mat`	`t()` Transposes a matrix.
`java.lang.String`	`toString()`
`long`	`total()` Returns the total number of array elements.
`int`	`type()` Returns the type of a matrix element.
`int`	`width()`
`static Mat`	`zeros(int rows, int cols, int type)` Returns a zero array of the specified size and type.
`static Mat`	`zeros(Size size, int type)` Returns a zero array of the specified size and type.

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Field Detail

nativeObj

public final long nativeObj

Constructor Detail

Mat

public Mat()

Various Mat constructors

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.

See Also:: org.opencv.core.Mat.Mat

Mat

public Mat(int rows,
           int cols,
           int type)

Various Mat constructors

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.
See Also:: org.opencv.core.Mat.Mat

Mat

public Mat(int rows,
           int cols,
           int type,
           Scalar s)

Various Mat constructors

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).
See Also:: org.opencv.core.Mat.Mat

Mat

public Mat(long addr)

Mat

public Mat(Mat m,
           Range rowRange)

Various Mat constructors

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.
See Also:: org.opencv.core.Mat.Mat

Mat

public Mat(Mat m,
           Range rowRange,
           Range colRange)

Various Mat constructors

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.
See Also:: org.opencv.core.Mat.Mat

Mat

public Mat(Mat m,
           Rect roi)

Various Mat constructors

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.
See Also:: org.opencv.core.Mat.Mat

Mat

public Mat(Size size,
           int type)

Various Mat constructors

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.
See Also:: org.opencv.core.Mat.Mat

Mat

public Mat(Size size,
           int type,
           Scalar s)

Various Mat constructors

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).
See Also:: org.opencv.core.Mat.Mat

Method Detail

adjustROI

public 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:



 // C++ code:

 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:: org.opencv.core.Mat.adjustROI, Imgproc.copyMakeBorder(org.opencv.core.Mat, org.opencv.core.Mat, int, int, int, int, int, org.opencv.core.Scalar)

assignTo

public void assignTo(Mat m)

Provides a functional form of convertTo.

This is an internally used method called by the "MatrixExpressions" engine.

Parameters:: m - Destination array.
See Also:: org.opencv.core.Mat.assignTo

assignTo

public void assignTo(Mat m,
                     int type)

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).
See Also:: org.opencv.core.Mat.assignTo

channels

public int channels()

Returns the number of matrix channels.

The method returns the number of matrix channels.

See Also:: org.opencv.core.Mat.channels

checkVector

public int checkVector(int elemChannels)

checkVector

public int checkVector(int elemChannels,
                       int depth)

checkVector

public int checkVector(int elemChannels,
                       int depth,
                       boolean requireContinuous)

clone

public Mat clone()

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 java.lang.Object

See Also:: org.opencv.core.Mat.clone

col

public Mat col(int x)

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.
See Also:: org.opencv.core.Mat.col

colRange

public Mat colRange(int startcol,
                    int endcol)

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.
See Also:: org.opencv.core.Mat.colRange

colRange

public Mat colRange(Range r)

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:: r - "Range" structure containing both the start and the end indices.
See Also:: org.opencv.core.Mat.colRange

cols

public int cols()

convertTo

public void convertTo(Mat m,
                      int rtype)

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.
See Also:: org.opencv.core.Mat.convertTo

convertTo

public void convertTo(Mat m,
                      int rtype,
                      double alpha)

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.
See Also:: org.opencv.core.Mat.convertTo

convertTo

public void convertTo(Mat m,
                      int rtype,
                      double alpha,
                      double beta)

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.
See Also:: org.opencv.core.Mat.convertTo

copyTo

public void copyTo(Mat m)

Copies the matrix to another one.

The method copies the matrix data to another matrix. Before copying the data, the method invokes



 // C++ code:

 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, and the Mat.create call shown above reallocated 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.
See Also:: org.opencv.core.Mat.copyTo

copyTo

public void copyTo(Mat m,
                   Mat mask)

Copies the matrix to another one.

The method copies the matrix data to another matrix. Before copying the data, the method invokes



 // C++ code:

 m.create(this->size(), this->type);

When the operation mask is specified, and the Mat.create call shown above reallocated 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.; mask - Operation mask. Its non-zero elements indicate which matrix elements need to be copied.
See Also:: org.opencv.core.Mat.copyTo

create

public void create(int rows,
                   int cols,
                   int type)

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:



 // C++ code:

 Mat color;...

 Mat gray(color.rows, color.cols, color.depth());

 cvtColor(color, gray, CV_BGR2GRAY);

 you can simply write:

 Mat color;...

 Mat gray;

 cvtColor(color, gray, CV_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.
See Also:: org.opencv.core.Mat.create

create

public void create(Size size,
                   int type)

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.



 // C++ code:

 Mat color;...

 Mat gray(color.rows, color.cols, color.depth());

 cvtColor(color, gray, CV_BGR2GRAY);

 you can simply write:

 Mat color;...

 Mat gray;

 cvtColor(color, gray, CV_BGR2GRAY);

because cvtColor, as well as the most of OpenCV functions, calls Mat.create() for the output array internally.

Parameters:: size - Alternative new matrix size specification: Size(cols, rows); type - New matrix type.
See Also:: org.opencv.core.Mat.create

cross

public Mat cross(Mat m)

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.
See Also:: org.opencv.core.Mat.cross

dataAddr

public long dataAddr()

depth

public int depth()

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)

See Also:: org.opencv.core.Mat.depth

diag

public Mat diag()

Extracts a diagonal from a matrix, or creates a diagonal 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.

See Also:: org.opencv.core.Mat.diag

diag

public Mat diag(int d)

Extracts a diagonal from a matrix, or creates a diagonal 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 - Single-column matrix that forms a diagonal matrix or 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.

See Also:

org.opencv.core.Mat.diag

diag

public static Mat diag(Mat d)

Extracts a diagonal from a matrix, or creates a diagonal 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 - Single-column matrix that forms a diagonal matrix or 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.

See Also:

org.opencv.core.Mat.diag

dims

public int dims()

dot

public double dot(Mat m)

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.
See Also:: org.opencv.core.Mat.dot

dump

public java.lang.String dump()

elemSize

public long elemSize()

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.

See Also:: org.opencv.core.Mat.elemSize

elemSize1

public long elemSize1()

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.

See Also:: org.opencv.core.Mat.elemSize1

empty

public boolean empty()

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.

See Also:: org.opencv.core.Mat.empty

eye

public static Mat eye(int rows,
                      int cols,
                      int type)

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:



 // C++ code:

 // 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.
See Also:: org.opencv.core.Mat.eye





eye
public static Mat eye(Size size,
                      int type)

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: 


 // C++ code:

 // make a 4x4 diagonal matrix with 0.1's on the diagonal.

 Mat A = Mat.eye(4, 4, CV_32F)*0.1;


Parameters:
size - Alternative matrix size specification as Size(cols,
 rows).
type - Created matrix type.
See Also:
org.opencv.core.Mat.eye






get
public double[] get(int row,
                    int col)








get
public int get(int row,
               int col,
               byte[] data)








get
public int get(int row,
               int col,
               double[] data)








get
public int get(int row,
               int col,
               float[] data)








get
public int get(int row,
               int col,
               int[] data)








get
public int get(int row,
               int col,
               short[] data)








getNativeObjAddr
public long getNativeObjAddr()








height
public int height()








inv
public Mat inv()

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.


See Also:
org.opencv.core.Mat.inv





inv
public Mat inv(int method)

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. Possible values are the following:
 
    DECOMP_LU is the LU decomposition. The matrix must be non-singular.
   
 DECOMP_CHOLESKY is the Cholesky LL^T decomposition for
 symmetrical positively defined matrices only. This type is about twice faster
 than LU on big matrices.
   
 DECOMP_SVD is the SVD decomposition. If the matrix is singular or even
 non-square, the pseudo inversion is computed.
 
See Also:
org.opencv.core.Mat.inv





isContinuous
public boolean isContinuous()

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: 


 // C++ code:

 // 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

 void alphaBlendRGBA(const Mat& src1, const Mat& src2, Mat& dst)


 const float alpha_scale = (float)std.numeric_limits.max(),

 inv_scale = 1.f/alpha_scale;

 CV_Assert(src1.type() == src2.type() &&

 src1.type() == CV_MAKETYPE(DataType.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(i);

 const T* ptr2 = src2.ptr(i);

 T* dptr = dst.ptr(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(ptr1[j]*alpha + ptr2[j]*beta);

 dptr[j+1] = saturate_cast(ptr1[j+1]*alpha + ptr2[j+1]*beta);

 dptr[j+2] = saturate_cast(ptr1[j+2]*alpha + ptr2[j+2]*beta);

 dptr[j+3] = saturate_cast((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.


See Also:
org.opencv.core.Mat.isContinuous





isSubmatrix
public boolean isSubmatrix()








locateROI
public void locateROI(Size wholeSize,
                      Point ofs)

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.
See Also:
org.opencv.core.Mat.locateROI





mul
public Mat mul(Mat m)

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: 


 // C++ code:

 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.
See Also:
org.opencv.core.Mat.mul






mul
public Mat mul(Mat m,
               double scale)

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: 


 // C++ code:

 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.
See Also:
org.opencv.core.Mat.mul






ones
public static Mat ones(int rows,
                       int cols,
                       int type)

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: 


 // C++ code:

 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.
See Also:
org.opencv.core.Mat.ones





ones
public static Mat ones(Size size,
                       int type)

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: 


 // C++ code:

 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:
size - Alternative to the matrix size specification Size(cols,
 rows).
type - Created matrix type.
See Also:
org.opencv.core.Mat.ones





push_back
public void push_back(Mat m)

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:
m - Added line(s).
See Also:
org.opencv.core.Mat.push_back





put
public int put(int row,
               int col,
               byte[] data)








put
public int put(int row,
               int col,
               double... data)








put
public int put(int row,
               int col,
               float[] data)








put
public int put(int row,
               int col,
               int[] data)








put
public int put(int row,
               int col,
               short[] data)








release
public 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.


See Also:
org.opencv.core.Mat.release





reshape
public Mat reshape(int cn)

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:
 


 // C++ code:

 std.vector 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.
See Also:
org.opencv.core.Mat.reshape






reshape
public Mat reshape(int cn,
                   int rows)

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:
 


 // C++ code:

 std.vector 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.
See Also:
org.opencv.core.Mat.reshape






row
public Mat row(int y)

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: 


 // C++ code:

 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:
 


 // C++ code:

 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.
See Also:
org.opencv.core.Mat.row






rowRange
public Mat rowRange(int startrow,
                    int endrow)

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.
See Also:
org.opencv.core.Mat.rowRange





rowRange
public Mat rowRange(Range r)

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:
r - "Range" structure containing both the start and the end indices.
See Also:
org.opencv.core.Mat.rowRange





rows
public int rows()








setTo
public Mat setTo(Mat value)

Sets all or some of the array elements to the specified value.


Parameters:
value - Assigned scalar converted to the actual array type.
See Also:
org.opencv.core.Mat.setTo





setTo
public Mat setTo(Mat value,
                 Mat mask)

Sets all or some of the array elements to the specified value.


Parameters:
value - Assigned scalar converted to the actual array type.
mask - Operation mask of the same size as *this. This is an
 advanced variant of the Mat.operator=(const Scalar& s)
 operator.
See Also:
org.opencv.core.Mat.setTo





setTo
public Mat setTo(Scalar s)








setTo
public Mat setTo(Scalar value,
                 Mat mask)

Sets all or some of the array elements to the specified value.


Parameters:
value - Assigned scalar converted to the actual array type.
mask - Operation mask of the same size as *this. This is an
 advanced variant of the Mat.operator=(const Scalar& s)
 operator.
See Also:
org.opencv.core.Mat.setTo





size
public Size size()

Returns a matrix size.

 The method returns a matrix size: Size(cols, rows). When the
 matrix is more than 2-dimensional, the returned size is (-1, -1).


See Also:
org.opencv.core.Mat.size





step1
public long step1()

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.


See Also:
org.opencv.core.Mat.step1





step1
public long step1(int i)

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.


Parameters:
i - a i
See Also:
org.opencv.core.Mat.step1





submat
public Mat submat(int rowStart,
                  int rowEnd,
                  int colStart,
                  int colEnd)

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:
rowStart - a rowStart
rowEnd - a rowEnd
colStart - a colStart
colEnd - a colEnd
See Also:
org.opencv.core.Mat.operator()





submat
public Mat submat(Range rowRange,
                  Range colRange)

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().
See Also:
org.opencv.core.Mat.operator()





submat
public Mat submat(Rect roi)

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:
roi - Extracted submatrix specified as a rectangle.
See Also:
org.opencv.core.Mat.operator()





t
public Mat t()

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: 


 // C++ code:

 Mat A1 = A + Mat.eye(A.size(), A.type)*lambda;

 Mat C = A1.t()*A1; // compute (A + lambda*I)^t * (A + lamda*I)


See Also:
org.opencv.core.Mat.t






toString
public java.lang.String toString()


Overrides:
toString in class java.lang.Object








total
public long total()

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).


See Also:
org.opencv.core.Mat.total





type
public int type()

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.


See Also:
org.opencv.core.Mat.type





width
public int width()








zeros
public static Mat zeros(int rows,
                        int cols,
                        int type)

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.
 


 // C++ code:

 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.
See Also:
org.opencv.core.Mat.zeros





zeros
public static Mat zeros(Size size,
                        int type)

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.
 


 // C++ code:

 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:
size - Alternative to the matrix size specification Size(cols,
 rows).
type - Created matrix type.
See Also:
org.opencv.core.Mat.zeros














  
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org.opencv.core Class Mat

nativeObj

Mat

Mat

Mat

Mat

Mat

Mat

Mat

Mat

Mat

adjustROI

assignTo

assignTo

channels

checkVector

checkVector

checkVector

clone

col

colRange

colRange

cols

convertTo

convertTo

convertTo

copyTo

copyTo

create

create

cross

dataAddr

depth

diag

diag

diag

dims

dot

dump

elemSize

elemSize1

empty

eye

eye

get

get

get

get

get

get

getNativeObjAddr

height

inv

inv

isContinuous

isSubmatrix

locateROI

mul

mul

ones

ones

push_back

put

put

put

put

put

release

reshape

reshape

row

rowRange

rowRange

rows

setTo

setTo

setTo

setTo

size

step1

org.opencv.core
Class Mat