Convolves an image with a 2D kernel. More...

Functions
VPIStatus	vpiSubmitConvolution (VPIStream stream, VPIBackend backend, VPIImage input, VPIImage output, const float *kernelData, uint32_t kernelWidth, uint32_t kernelHeight, VPIBoundaryCond boundary)
	Runs a generic 2D convolution over an image. More...

VPIStatus	vpiSubmitSeparableConvolution (VPIStream stream, VPIBackend backend, VPIImage input, VPIImage output, const float kernelXData, uint32_t kernelXSize, const float kernelYData, uint32_t kernelYSize, VPIBoundaryCond boundary)
	Runs a generic 2D convolution operation over an image, optimized for separable kernels. More...

Detailed Description

Convolves an image with a 2D kernel.

vpiSubmitConvolution is used for generic 2D kernels, separable or not. For separable kernels, it's usually more efficient to use vpiSubmitSeparableConvolution.

Function Documentation

VPIStatus vpiSubmitConvolution	(	VPIStream	stream,
		VPIBackend	backend,
		VPIImage	input,
		VPIImage	output,
		const float *	kernelData,
		uint32_t	kernelWidth,
		uint32_t	kernelHeight,
		VPIBoundaryCond	boundary
	)

Runs a generic 2D convolution over an image.

Parameters

[in]	stream	The stream handle where the operation will be queued in.
[in]	backend	The backend that will execute the algorithm.
[in]	input	Input image to be convolved with the kernel.
[out]	output	Output image where the result is written to. Its image format and dimensions must be the same as input.
[in]	kernelWidth,kernelHeight	Kernel dimensions.
[in]	kernelData	Convolution kernel coefficients, in row-major layout.
[in]	boundary	Boundary condition.

VPIStatus vpiSubmitSeparableConvolution	(	VPIStream	stream,
		VPIBackend	backend,
		VPIImage	input,
		VPIImage	output,
		const float *	kernelXData,
		uint32_t	kernelXSize,
		const float *	kernelYData,
		uint32_t	kernelYSize,
		VPIBoundaryCond	boundary
	)

Runs a generic 2D convolution operation over an image, optimized for separable kernels.

Parameters

[in]	stream	The stream handle where the operation will be queued in.
[in]	backend	The backend that will execute the algorithm.
[in]	input	Input image to be convolved with the kernel.
[out]	output	Output image where the result is written to. Its image format and dimensions must be the same as input's.
[in]	kernelXSize,kernelYSize	Kernel dimensions in X and Y directions.
[in]	kernelXData,kernelYData	Convolution kernel coefficients, in both X and Y directions respectively.
[in]	boundary	Boundary condition.