Module: color

pop_bilateral skimage.filters.rank.pop_bilateral(image, selem, out=None, mask=None, shift_x=False, shift_y=False, s0=10

lena skimage.data.lena(*args, **kwargs)

RAG class skimage.future.graph.RAG(label_image=None, connectivity=1, data=None, **attr)

plugin_order skimage.io.plugin_order()

corner_shi_tomasi skimage.feature.corner_shi_tomasi(image, sigma=1)

Module: viewer.widgets Widgets for interacting with ImageViewer. These widgets should be added to a Plugin subclass using its add_widget

reconstruction skimage.morphology.reconstruction(seed, mask, method='dilation', selem=None, offset=None)

PolynomialTransform class skimage.transform.PolynomialTransform(params=None)

How to parallelize loops In image processing, we frequently apply the same algorithm on a large batch of images. In this paragraph, we propose to use