blur.rst

augmenters.blur

GaussianBlur

Augmenter to blur images using gaussian kernels.

API link: :class:`~imgaug.augmenters.blur.GaussianBlur`

Example. Blur each image with a gaussian kernel with a sigma of 3.0:

import imgaug.augmenters as iaa
aug = iaa.GaussianBlur(sigma=(0.0, 3.0))

AverageBlur

Blur an image by computing simple means over neighbourhoods.

API link: :class:`~imgaug.augmenters.blur.AverageBlur`

Example. Blur each image using a mean over neihbourhoods that have a random size between 2x2 and 11x11:

import imgaug.augmenters as iaa
aug = iaa.AverageBlur(k=(2, 11))

Example. Blur each image using a mean over neihbourhoods that have random sizes, which can vary between 5 and 11 in height and 1 and 3 in width:

aug = iaa.AverageBlur(k=((5, 11), (1, 3)))

MedianBlur

Blur an image by computing median values over neighbourhoods.

API link: :class:`~imgaug.augmenters.blur.MedianBlur`

Example. Blur each image using a median over neihbourhoods that have a random size between 3x3 and 11x11:

import imgaug.augmenters as iaa
aug = iaa.MedianBlur(k=(3, 11))

BilateralBlur

Blur/Denoise an image using a bilateral filter.

Bilateral filters blur homogenous and textured areas, while trying to preserve edges.

API link: :class:`~imgaug.augmenters.blur.BilateralBlur`

Example. Blur all images using a bilateral filter with a max distance sampled uniformly from the interval [3, 10] and wide ranges for sigma_color and sigma_space:

import imgaug.augmenters as iaa
aug = iaa.BilateralBlur(
    d=(3, 10), sigma_color=(10, 250), sigma_space=(10, 250))

MotionBlur

Blur images in a way that fakes camera or object movements.

API link: :class:`~imgaug.augmenters.blur.MotionBlur`

Example. Apply motion blur with a kernel size of 15x15 pixels to images:

import imgaug.augmenters as iaa
aug = iaa.MotionBlur(k=15)

Example. Apply motion blur with a kernel size of 15x15 pixels and a blur angle of either -45 or 45 degrees (randomly picked per image):

aug = iaa.MotionBlur(k=15, angle=[-45, 45])