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"""
==============
Normalized Cut
==============
This example constructs a Region Adjacency Graph (RAG) and recursively performs
a Normalized Cut on it [1]_.
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, segmentation, color
from skimage import graph
from matplotlib import pyplot as plt
img = data.coffee()
labels1 = segmentation.slic(img, compactness=30, n_segments=400, start_label=1)
out1 = color.label2rgb(labels1, img, kind='avg', bg_label=0)
g = graph.rag_mean_color(img, labels1, mode='similarity')
labels2 = graph.cut_normalized(labels1, g)
out2 = color.label2rgb(labels2, img, kind='avg', bg_label=0)
fig, ax = plt.subplots(nrows=2, sharex=True, sharey=True, figsize=(6, 8))
ax[0].imshow(out1)
ax[1].imshow(out2)
for a in ax:
a.axis('off')
plt.tight_layout()
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