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java.lang.Object org.opencv.core.Mat
public class Mat
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:
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.
// 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).
Mat.clone()
method can be used to get a full (deep) copy of the array when you need it.
// 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.
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);
// 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);
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);
// C++ code:
// create a 3x3 double-precision identity matrix
Mat M = (Mat_
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
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
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
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_
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()
.
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 row span. |
Mat |
colRange(Range r)
Creates a matrix header for the specified row 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. |
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 |
---|
public final long nativeObj
Constructor Detail |
---|
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.
public Mat(int rows, int cols, int type)
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.
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_MAX_CN
channels) matrices.public Mat(int rows, int cols, int type, Scalar s)
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.
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_MAX_CN
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)
.public Mat(long addr)
public Mat(Mat m, Range rowRange)
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.
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.public Mat(Mat m, Range rowRange, Range colRange)
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.
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.public Mat(Mat m, Rect roi)
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.
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.public Mat(Size size, int type)
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.
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_MAX_CN
channels) matrices.public Mat(Size size, int type, Scalar s)
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.
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_MAX_CN
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)
.Method Detail |
---|
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.
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.Imgproc.copyMakeBorder(org.opencv.core.Mat, org.opencv.core.Mat, int, int, int, int, int, org.opencv.core.Scalar)
public void assignTo(Mat m)
Provides a functional form of convertTo
.
This is an internally used method called by the "MatrixExpressions" engine.
m
- Destination array.public void assignTo(Mat m, int type)
Provides a functional form of convertTo
.
This is an internally used method called by the "MatrixExpressions" engine.
m
- Destination array.type
- Desired destination array depth (or -1 if it should be the same
as the source type).public int channels()
Returns the number of matrix channels.
The method returns the number of matrix channels.
public int checkVector(int elemChannels)
public int checkVector(int elemChannels, int depth)
public int checkVector(int elemChannels, int depth, boolean requireContinuous)
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.
clone
in class java.lang.Object
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.
x
- A 0-based column index.public Mat colRange(int startcol, int endcol)
Creates a matrix header for the specified row 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.
startcol
- An inclusive 0-based start index of the column span.endcol
- An exclusive 0-based ending index of the column span.public Mat colRange(Range r)
Creates a matrix header for the specified row 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.
r
- "Range" structure containing both the start and the end indices.public int cols()
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)
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.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)
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.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)
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.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.
m
- Destination matrix. If it does not have a proper size or type before
the operation, it is reallocated.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);
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.
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.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:
total()*elemSize()
bytes.
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.
rows
- New number of rows.cols
- New number of columns.type
- New matrix type.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:
total()*elemSize()
bytes.
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.
size
- Alternative new matrix size specification: Size(cols,
rows)
type
- New matrix type.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.
m
- Another cross-product operand.public long dataAddr()
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
)
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.
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.
d
- Single-column matrix that forms a diagonal matrix or index of the
diagonal, with the following values:
d=1
means the diagonal is set immediately below the main one.
d=1
means the diagonal is set immediately above the main one.
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.
d
- Single-column matrix that forms a diagonal matrix or index of the
diagonal, with the following values:
d=1
means the diagonal is set immediately below the main one.
d=1
means the diagonal is set immediately above the main one.
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.
m
- another dot-product operand.public java.lang.String dump()
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.
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.
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
.
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;
rows
- Number of rows.cols
- Number of columns.type
- Created matrix type.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;
size
- Alternative matrix size specification as Size(cols,
rows)
.type
- Created matrix type.public double[] get(int row, int col)
public int get(int row, int col, byte[] data)
public int get(int row, int col, double[] data)
public int get(int row, int col, float[] data)
public int get(int row, int col, int[] data)
public int get(int row, int col, short[] data)
public long getNativeObjAddr()
public int height()
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.
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.
method
- Matrix inversion method. Possible values are the following:
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
inv_scale = 1.f/alpha_scale;
CV_Assert(src1.type() == src2.type() &&
src1.type() == CV_MAKETYPE(DataType
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
const T* ptr2 = src2.ptr
T* dptr = dst.ptr
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
dptr[j+1] = saturate_cast
dptr[j+2] = saturate_cast
dptr[j+3] = saturate_cast
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.
public boolean isSubmatrix()
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.
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.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)
m
- Another array of the same type and the same size as
*this
, or a matrix expression.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)
m
- Another array of the same type and the same size as
*this
, or a matrix expression.scale
- Optional scale factor.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.
rows
- Number of rows.cols
- Number of columns.type
- Created matrix type.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.
size
- Alternative to the matrix size specification Size(cols,
rows)
.type
- Created matrix type.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.
m
- Added line(s).public int put(int row, int col, byte[] data)
public int put(int row, int col, double... data)
public int put(int row, int col, float[] data)
public int put(int row, int col, int[] data)
public int put(int row, int col, short[] data)
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.
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:
rows*cols*channels()
must
stay the same after the transformation.
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
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
cn
- New number of channels. If the parameter is 0, the number of
channels remains the same.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:
rows*cols*channels()
must
stay the same after the transformation.
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
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
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.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));
y
- A 0-based row index.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.
startrow
- An inclusive 0-based start index of the row span.endrow
- An exclusive 0-based ending index of the row span.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.
r
- "Range" structure containing both the start and the end indices.public int rows()
public Mat setTo(Mat value)
Sets all or some of the array elements to the specified value.
value
- Assigned scalar converted to the actual array type.public Mat setTo(Mat value, Mat mask)
Sets all or some of the array elements to the specified value.
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.public Mat setTo(Scalar s)
public Mat setTo(Scalar value, Mat mask)
Sets all or some of the array elements to the specified value.
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.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).
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.
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.
i
- a ipublic 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.
rowStart
- a rowStartrowEnd
- a rowEndcolStart
- a colStartcolEnd
- a colEndpublic 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.
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()
.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.
roi
- Extracted submatrix specified as a rectangle.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)
public java.lang.String toString()
toString
in class java.lang.Object
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).
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.
public int width()
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.
rows
- Number of rows.cols
- Number of columns.type
- Created matrix type.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.
size
- Alternative to the matrix size specification Size(cols,
rows)
.type
- Created matrix type.
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