bob.ip.Gaussian¶

class bob.ip.Gaussian((object)self[, (int)radius_y=1[, (int)radius_x=1[, (float)sigma_y=1.5811388300841898[, (float)sigma_x=1.5811388300841898[, (BorderType)conv_border=bob.sp._sp.BorderType.Mirror]]]]]) → None :¶

Bases: Boost.Python.instance

This class allows after configuration to perform gaussian smoothing.

Creates a gaussian smoother.

__init__( (object)self, (Gaussian)other) -> None

__init__((object)self[, (int)radius_y=1[, (int)radius_x=1[, (float)sigma_y=1.5811388300841898[, (float)sigma_x=1.5811388300841898[, (BorderType)conv_border=bob.sp._sp.BorderType.Mirror]]]]]) → None :¶

Creates a gaussian smoother.

__init__( (object)self, (Gaussian)other) -> None

Methods

`__init__`((object)self [, (int)radius_y=1 [, …)	Creates a gaussian smoother.
`reset`((Gaussian)self [, (int)radius_y=1 [, …)	Resets the parametrization of the Gaussian

Attributes

`conv_border`	The extrapolation method used by the convolution at the border
`kernel_x`	The values of the x-kernel (read only access)
`kernel_y`	The values of the y-kernel (read only access)
`radius_x`	The radius of the Gaussian along the x-axis (size of the kernel=2*radius+1)
`radius_y`	The radius of the Gaussian along the y-axis (size of the kernel=2*radius+1)
`sigma_x`	The variance of the Gaussian along the x-axis
`sigma_y`	The variance of the Gaussian along the y-axis

__call__((Gaussian)self, (object)src, (object)dst) → None :¶

Smoothes an image (2D/grayscale or color 3D/color). The dst array should have the expected type (numpy.float64) and the same size as the src array.

__call__( (Gaussian)self, (object)src) -> object :: Smoothes an image (2D/grayscale or color 3D/color). The smoothed image is returned as a numpy array.

conv_border¶: The extrapolation method used by the convolution at the border

kernel_x¶: The values of the x-kernel (read only access)

kernel_y¶: The values of the y-kernel (read only access)

radius_x¶: The radius of the Gaussian along the x-axis (size of the kernel=2*radius+1)

radius_y¶: The radius of the Gaussian along the y-axis (size of the kernel=2*radius+1)

reset((Gaussian)self[, (int)radius_y=1[, (int)radius_x=1[, (float)sigma_y=1.5811388300841898[, (float)sigma_x=1.5811388300841898[, (BorderType)conv_border=bob.sp._sp.BorderType.Mirror]]]]]) → None :¶: Resets the parametrization of the Gaussian

sigma_x¶: The variance of the Gaussian along the x-axis

sigma_y¶: The variance of the Gaussian along the y-axis