Classes
class	cv::cuda::Convolution
	Base class for convolution (or cross-correlation) operator. : More...

Functions
Ptr< Convolution >	cv::cuda::createConvolution (Size user_block_size=Size())
	Creates implementation for cuda::Convolution . More...

void	cv::cuda::dft (InputArray src, OutputArray dst, Size dft_size, int flags=0, Stream &stream=Stream::Null())
	Performs a forward or inverse discrete Fourier transform (1D or 2D) of the floating point matrix. More...

void	cv::cuda::gemm (InputArray src1, InputArray src2, double alpha, InputArray src3, double beta, OutputArray dst, int flags=0, Stream &stream=Stream::Null())
	Performs generalized matrix multiplication. More...

void	cv::cuda::mulAndScaleSpectrums (InputArray src1, InputArray src2, OutputArray dst, int flags, float scale, bool conjB=false, Stream &stream=Stream::Null())
	Performs a per-element multiplication of two Fourier spectrums and scales the result. More...

void	cv::cuda::mulSpectrums (InputArray src1, InputArray src2, OutputArray dst, int flags, bool conjB=false, Stream &stream=Stream::Null())
	Performs a per-element multiplication of two Fourier spectrums. More...

Detailed Description

Function Documentation

Ptr<Convolution> cv::cuda::createConvolution ( Size user_block_size = Size() )

Creates implementation for cuda::Convolution .

Parameters

user_block_size Block size. If you leave default value Size(0,0) then automatic estimation of block size will be used (which is optimized for speed). By varying user_block_size you can reduce memory requirements at the cost of speed.

void cv::cuda::dft	(	InputArray	src,
		OutputArray	dst,
		Size	dft_size,
		int	flags = `0`,
		Stream &	stream = `Stream::Null()`
	)

Performs a forward or inverse discrete Fourier transform (1D or 2D) of the floating point matrix.

Parameters

src	Source matrix (real or complex).
dst	Destination matrix (real or complex).
dft_size	Size of a discrete Fourier transform.
flags	Optional flags: DFT_ROWS transforms each individual row of the source matrix. DFT_SCALE scales the result: divide it by the number of elements in the transform (obtained from dft_size ). DFT_INVERSE inverts DFT. Use for complex-complex cases (real-complex and complex-real cases are always forward and inverse, respectively). DFT_REAL_OUTPUT specifies the output as real. The source matrix is the result of real-complex transform, so the destination matrix must be real.
stream	Stream for the asynchronous version.

Use to handle real matrices ( CV32FC1 ) and complex matrices in the interleaved format ( CV32FC2 ).

The source matrix should be continuous, otherwise reallocation and data copying is performed. The function chooses an operation mode depending on the flags, size, and channel count of the source matrix:

If the source matrix is complex and the output is not specified as real, the destination matrix is complex and has the dft_size size and CV_32FC2 type. The destination matrix contains a full result of the DFT (forward or inverse).
If the source matrix is complex and the output is specified as real, the function assumes that its input is the result of the forward transform (see the next item). The destination matrix has the dft_size size and CV_32FC1 type. It contains the result of the inverse DFT.
If the source matrix is real (its type is CV_32FC1 ), forward DFT is performed. The result of the DFT is packed into complex ( CV_32FC2 ) matrix. So, the width of the destination matrix is dft_size.width / 2 + 1 . But if the source is a single column, the height is reduced instead of the width.

See also: dft

void cv::cuda::gemm	(	InputArray	src1,
		InputArray	src2,
		double	alpha,
		InputArray	src3,
		double	beta,
		OutputArray	dst,
		int	flags = `0`,
		Stream &	stream = `Stream::Null()`
	)

Performs generalized matrix multiplication.

Parameters

src1	First multiplied input matrix that should have CV_32FC1 , CV_64FC1 , CV_32FC2 , or CV_64FC2 type.
src2	Second multiplied input matrix of the same type as src1 .
alpha	Weight of the matrix product.
src3	Third optional delta matrix added to the matrix product. It should have the same type as src1 and src2 .
beta	Weight of src3 .
dst	Destination matrix. It has the proper size and the same type as input matrices.
flags	Operation flags: GEMM_1_T transpose src1 GEMM_2_T transpose src2 GEMM_3_T transpose src3
stream	Stream for the asynchronous version.

The function performs generalized matrix multiplication similar to the gemm functions in BLAS level

For example, gemm(src1, src2, alpha, src3, beta, dst, GEMM_1_T + GEMM_3_T) corresponds to

\[\texttt{dst} = \texttt{alpha} \cdot \texttt{src1} ^T \cdot \texttt{src2} + \texttt{beta} \cdot \texttt{src3} ^T\]

Note: Transposition operation doesn't support CV_64FC2 input type.

See also: gemm

void cv::cuda::mulAndScaleSpectrums	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		int	flags,
		float	scale,
		bool	conjB = `false`,
		Stream &	stream = `Stream::Null()`
	)

Performs a per-element multiplication of two Fourier spectrums and scales the result.

Parameters

src1	First spectrum.
src2	Second spectrum with the same size and type as a .
dst	Destination spectrum.
flags	Mock parameter used for CPU/CUDA interfaces similarity, simply add a `0` value.
scale	Scale constant.
conjB	Optional flag to specify if the second spectrum needs to be conjugated before the multiplication.
stream	Stream for the asynchronous version.

Only full (not packed) CV_32FC2 complex spectrums in the interleaved format are supported for now.

See also: mulSpectrums

void cv::cuda::mulSpectrums	(	InputArray	src1,
		InputArray	src2,
		OutputArray	dst,
		int	flags,
		bool	conjB = `false`,
		Stream &	stream = `Stream::Null()`
	)

Performs a per-element multiplication of two Fourier spectrums.

Parameters

src1	First spectrum.
src2	Second spectrum with the same size and type as a .
dst	Destination spectrum.
flags	Mock parameter used for CPU/CUDA interfaces similarity.
conjB	Optional flag to specify if the second spectrum needs to be conjugated before the multiplication.
stream	Stream for the asynchronous version.

Only full (not packed) CV_32FC2 complex spectrums in the interleaved format are supported for now.

See also: mulSpectrums

Classes

Functions

Detailed Description

Function Documentation