From 22b5f4addf800fe959906978f1d5086faa0ddfcb Mon Sep 17 00:00:00 2001
From: Vighnesh Birodkar <vighneshbirodkar@gmail.com>
Date: Wed, 23 Jul 2014 04:47:17 +0530
Subject: [PATCH] Added example for ncut

---
 doc/examples/plot_ncut.py | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)
 create mode 100644 doc/examples/plot_ncut.py

diff --git a/doc/examples/plot_ncut.py b/doc/examples/plot_ncut.py
new file mode 100644
index 00000000..941ef014
--- /dev/null
+++ b/doc/examples/plot_ncut.py
@@ -0,0 +1,32 @@
+"""
+==============
+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, Aug 2000
+"""
+from skimage import graph, data, io, segmentation, color
+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_n(labels1, g)
+out2 = color.label2rgb(labels2, img, kind='avg')
+
+plt.figure()
+io.imshow(out1)
+plt.figure()
+io.imshow(out2)
+io.show()