Functions
Scalar	cv::cuda::absSum (InputArray src, InputArray mask=noArray())
	Returns the sum of absolute values for matrix elements. More...

void	cv::cuda::calcAbsSum (InputArray src, OutputArray dst, InputArray mask=noArray(), Stream &stream=Stream::Null())

void	cv::cuda::calcNorm (InputArray src, OutputArray dst, int normType, InputArray mask=noArray(), Stream &stream=Stream::Null())

void	cv::cuda::calcNormDiff (InputArray src1, InputArray src2, OutputArray dst, int normType=NORM_L2, Stream &stream=Stream::Null())

void	cv::cuda::calcSqrSum (InputArray src, OutputArray dst, InputArray mask=noArray(), Stream &stream=Stream::Null())

void	cv::cuda::calcSum (InputArray src, OutputArray dst, InputArray mask=noArray(), Stream &stream=Stream::Null())

int	cv::cuda::countNonZero (InputArray src)
	Counts non-zero matrix elements. More...

void	cv::cuda::countNonZero (InputArray src, OutputArray dst, Stream &stream=Stream::Null())

void	cv::cuda::findMinMax (InputArray src, OutputArray dst, InputArray mask=noArray(), Stream &stream=Stream::Null())

void	cv::cuda::findMinMaxLoc (InputArray src, OutputArray minMaxVals, OutputArray loc, InputArray mask=noArray(), Stream &stream=Stream::Null())

void	cv::cuda::integral (InputArray src, OutputArray sum, Stream &stream=Stream::Null())
	Computes an integral image. More...

void	cv::cuda::meanStdDev (InputArray mtx, Scalar &mean, Scalar &stddev)
	Computes a mean value and a standard deviation of matrix elements. More...

void	cv::cuda::meanStdDev (InputArray mtx, OutputArray dst, Stream &stream=Stream::Null())

void	cv::cuda::minMax (InputArray src, double minVal, double maxVal, InputArray mask=noArray())
	Finds global minimum and maximum matrix elements and returns their values. More...

void	cv::cuda::minMaxLoc (InputArray src, double minVal, double maxVal, Point minLoc, Point maxLoc, InputArray mask=noArray())
	Finds global minimum and maximum matrix elements and returns their values with locations. More...

double	cv::cuda::norm (InputArray src1, int normType, InputArray mask=noArray())
	Returns the norm of a matrix (or difference of two matrices). More...

double	cv::cuda::norm (InputArray src1, InputArray src2, int normType=NORM_L2)
	Returns the difference of two matrices. More...

void	cv::cuda::normalize (InputArray src, OutputArray dst, double alpha, double beta, int norm_type, int dtype, InputArray mask=noArray(), Stream &stream=Stream::Null())
	Normalizes the norm or value range of an array. More...

void	cv::cuda::rectStdDev (InputArray src, InputArray sqr, OutputArray dst, Rect rect, Stream &stream=Stream::Null())
	Computes a standard deviation of integral images. More...

void	cv::cuda::reduce (InputArray mtx, OutputArray vec, int dim, int reduceOp, int dtype=-1, Stream &stream=Stream::Null())
	Reduces a matrix to a vector. More...

void	cv::cuda::sqrIntegral (InputArray src, OutputArray sqsum, Stream &stream=Stream::Null())
	Computes a squared integral image. More...

Scalar	cv::cuda::sqrSum (InputArray src, InputArray mask=noArray())
	Returns the squared sum of matrix elements. More...

Scalar	cv::cuda::sum (InputArray src, InputArray mask=noArray())
	Returns the sum of matrix elements. More...

Detailed Description

Function Documentation

§ absSum()

Scalar cv::cuda::absSum	(	InputArray	src,
		InputArray	mask = `noArray()`
	)

#include <opencv2/cudaarithm.hpp>

Returns the sum of absolute values for matrix elements.

Parameters

src	Source image of any depth except for CV_64F .
mask	optional operation mask; it must have the same size as src1 and CV_8UC1 type.

§ calcAbsSum()

void cv::cuda::calcAbsSum	(	InputArray	src,
		OutputArray	dst,
		InputArray	mask = `noArray()`,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ calcNorm()

void cv::cuda::calcNorm	(	InputArray	src,
		OutputArray	dst,
		int	normType,
		InputArray	mask = `noArray()`,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ calcNormDiff()

void cv::cuda::calcNormDiff	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		int	normType = `NORM_L2`,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ calcSqrSum()

void cv::cuda::calcSqrSum	(	InputArray	src,
		OutputArray	dst,
		InputArray	mask = `noArray()`,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ calcSum()

void cv::cuda::calcSum	(	InputArray	src,
		OutputArray	dst,
		InputArray	mask = `noArray()`,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ countNonZero() [1/2]

int cv::cuda::countNonZero ( InputArray src )

#include <opencv2/cudaarithm.hpp>

Counts non-zero matrix elements.

Parameters

src	Single-channel source image.

The function does not work with CV_64F images on GPUs with the compute capability < 1.3.

See also: countNonZero

§ countNonZero() [2/2]

void cv::cuda::countNonZero	(	InputArray	src,
		OutputArray	dst,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ findMinMax()

void cv::cuda::findMinMax	(	InputArray	src,
		OutputArray	dst,
		InputArray	mask = `noArray()`,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ findMinMaxLoc()

void cv::cuda::findMinMaxLoc	(	InputArray	src,
		OutputArray	minMaxVals,
		OutputArray	loc,
		InputArray	mask = `noArray()`,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ integral()

void cv::cuda::integral	(	InputArray	src,
		OutputArray	sum,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

Computes an integral image.

Parameters

src	Source image. Only CV_8UC1 images are supported for now.
sum	Integral image containing 32-bit unsigned integer values packed into CV_32SC1 .
stream	Stream for the asynchronous version.

See also: integral

§ meanStdDev() [1/2]

void cv::cuda::meanStdDev	(	InputArray	mtx,
		Scalar &	mean,
		Scalar &	stddev
	)

#include <opencv2/cudaarithm.hpp>

Computes a mean value and a standard deviation of matrix elements.

Parameters

mtx	Source matrix. CV_8UC1 matrices are supported for now.
mean	Mean value.
stddev	Standard deviation value.

See also: meanStdDev

§ meanStdDev() [2/2]

void cv::cuda::meanStdDev	(	InputArray	mtx,
		OutputArray	dst,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

§ minMax()

void cv::cuda::minMax	(	InputArray	src,
		double *	minVal,
		double *	maxVal,
		InputArray	mask = `noArray()`
	)

#include <opencv2/cudaarithm.hpp>

Finds global minimum and maximum matrix elements and returns their values.

Parameters

src	Single-channel source image.
minVal	Pointer to the returned minimum value. Use NULL if not required.
maxVal	Pointer to the returned maximum value. Use NULL if not required.
mask	Optional mask to select a sub-matrix.

The function does not work with CV_64F images on GPUs with the compute capability < 1.3.

See also: minMaxLoc

§ minMaxLoc()

void cv::cuda::minMaxLoc	(	InputArray	src,
		double *	minVal,
		double *	maxVal,
		Point *	minLoc,
		Point *	maxLoc,
		InputArray	mask = `noArray()`
	)

#include <opencv2/cudaarithm.hpp>

Finds global minimum and maximum matrix elements and returns their values with locations.

Parameters

src	Single-channel source image.
minVal	Pointer to the returned minimum value. Use NULL if not required.
maxVal	Pointer to the returned maximum value. Use NULL if not required.
minLoc	Pointer to the returned minimum location. Use NULL if not required.
maxLoc	Pointer to the returned maximum location. Use NULL if not required.
mask	Optional mask to select a sub-matrix.

The function does not work with CV_64F images on GPU with the compute capability < 1.3.

See also: minMaxLoc

§ norm() [1/2]

double cv::cuda::norm	(	InputArray	src1,
		int	normType,
		InputArray	mask = `noArray()`
	)

#include <opencv2/cudaarithm.hpp>

Returns the norm of a matrix (or difference of two matrices).

Parameters

src1	Source matrix. Any matrices except 64F are supported.
normType	Norm type. NORM_L1 , NORM_L2 , and NORM_INF are supported for now.
mask	optional operation mask; it must have the same size as src1 and CV_8UC1 type.

See also: norm

§ norm() [2/2]

double cv::cuda::norm	(	InputArray	src1,
		InputArray	src2,
		int	normType = `NORM_L2`
	)

#include <opencv2/cudaarithm.hpp>

Returns the difference of two matrices.

Parameters

src1	Source matrix. Any matrices except 64F are supported.
src2	Second source matrix (if any) with the same size and type as src1.
normType	Norm type. NORM_L1 , NORM_L2 , and NORM_INF are supported for now.

See also: norm

§ normalize()

void cv::cuda::normalize	(	InputArray	src,
		OutputArray	dst,
		double	alpha,
		double	beta,
		int	norm_type,
		int	dtype,
		InputArray	mask = `noArray()`,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

Normalizes the norm or value range of an array.

Parameters

src	Input array.
dst	Output array of the same size as src .
alpha	Norm value to normalize to or the lower range boundary in case of the range normalization.
beta	Upper range boundary in case of the range normalization; it is not used for the norm normalization.
norm_type	Normalization type ( NORM_MINMAX , NORM_L2 , NORM_L1 or NORM_INF ).
dtype	When negative, the output array has the same type as src; otherwise, it has the same number of channels as src and the depth =CV_MAT_DEPTH(dtype).
mask	Optional operation mask.
stream	Stream for the asynchronous version.

See also: normalize

§ rectStdDev()

void cv::cuda::rectStdDev	(	InputArray	src,
		InputArray	sqr,
		OutputArray	dst,
		Rect	rect,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

Computes a standard deviation of integral images.

Parameters

src	Source image. Only the CV_32SC1 type is supported.
sqr	Squared source image. Only the CV_32FC1 type is supported.
dst	Destination image with the same type and size as src .
rect	Rectangular window.
stream	Stream for the asynchronous version.

§ reduce()

void cv::cuda::reduce	(	InputArray	mtx,
		OutputArray	vec,
		int	dim,
		int	reduceOp,
		int	dtype = `-1`,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

Reduces a matrix to a vector.

Parameters

mtx	Source 2D matrix.
vec	Destination vector. Its size and type is defined by dim and dtype parameters.
dim	Dimension index along which the matrix is reduced. 0 means that the matrix is reduced to a single row. 1 means that the matrix is reduced to a single column.
reduceOp	Reduction operation that could be one of the following: CV_REDUCE_SUM The output is the sum of all rows/columns of the matrix. CV_REDUCE_AVG The output is the mean vector of all rows/columns of the matrix. CV_REDUCE_MAX The output is the maximum (column/row-wise) of all rows/columns of the matrix. CV_REDUCE_MIN The output is the minimum (column/row-wise) of all rows/columns of the matrix.
dtype	When it is negative, the destination vector will have the same type as the source matrix. Otherwise, its type will be CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), mtx.channels()) .
stream	Stream for the asynchronous version.

The function reduce reduces the matrix to a vector by treating the matrix rows/columns as a set of 1D vectors and performing the specified operation on the vectors until a single row/column is obtained. For example, the function can be used to compute horizontal and vertical projections of a raster image. In case of CV_REDUCE_SUM and CV_REDUCE_AVG , the output may have a larger element bit-depth to preserve accuracy. And multi-channel arrays are also supported in these two reduction modes.

See also: reduce

§ sqrIntegral()

void cv::cuda::sqrIntegral	(	InputArray	src,
		OutputArray	sqsum,
		Stream &	stream = `Stream::Null()`
	)

#include <opencv2/cudaarithm.hpp>

Computes a squared integral image.

Parameters

src	Source image. Only CV_8UC1 images are supported for now.
sqsum	Squared integral image containing 64-bit unsigned integer values packed into CV_64FC1 .
stream	Stream for the asynchronous version.

§ sqrSum()

Scalar cv::cuda::sqrSum	(	InputArray	src,
		InputArray	mask = `noArray()`
	)

#include <opencv2/cudaarithm.hpp>

Returns the squared sum of matrix elements.

Parameters

src	Source image of any depth except for CV_64F .
mask	optional operation mask; it must have the same size as src1 and CV_8UC1 type.

§ sum()

Scalar cv::cuda::sum	(	InputArray	src,
		InputArray	mask = `noArray()`
	)

#include <opencv2/cudaarithm.hpp>

Returns the sum of matrix elements.

Parameters

src	Source image of any depth except for CV_64F .
mask	optional operation mask; it must have the same size as src1 and CV_8UC1 type.

See also: sum

Functions

Detailed Description

Function Documentation

§ absSum()

§ calcAbsSum()

§ calcNorm()

§ calcNormDiff()

§ calcSqrSum()

§ calcSum()

§ countNonZero() [1/2]

§ countNonZero() [2/2]

§ findMinMax()

§ findMinMaxLoc()

§ integral()

§ meanStdDev() [1/2]

§ meanStdDev() [2/2]

§ minMax()

§ minMaxLoc()

§ norm() [1/2]

§ norm() [2/2]

§ normalize()

§ rectStdDev()

§ reduce()

§ sqrIntegral()

§ sqrSum()

§ sum()