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scikit-image/doc/examples/segmentation/plot_ncut.py
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Python

"""
==============
Normalized Cut
==============
This example constructs a Region Adjacency Graph (RAG) and recursively performs
a Normalized Cut on it.
References
----------
.. [1] Shi, J.; Malik, J., "Normalized cuts and image segmentation",
Pattern Analysis and Machine Intelligence,
IEEE Transactions on, vol. 22, no. 8, pp. 888-905, August 2000.
"""
from skimage import data, io, segmentation, color
from skimage.future import graph
from matplotlib import pyplot as plt
img = data.coffee()
labels1 = segmentation.slic(img, compactness=30, n_segments=400)
out1 = color.label2rgb(labels1, img, kind='avg')
g = graph.rag_mean_color(img, labels1, mode='similarity')
labels2 = graph.cut_normalized(labels1, g)
out2 = color.label2rgb(labels2, img, kind='avg')
plt.figure()
io.imshow(out1)
plt.figure()
io.imshow(out2)
io.show()