Documentation, example for km_segmentation

doc/examples/plot_km_segmentation.py

@@ -0,0 +1,36 @@
+"""
+"""
+print __doc__
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from skimage.data import lena
+from skimage.segmentation import km_segmentation
+from skimage.util import img_as_float
+
+img = img_as_float(lena()).copy("C")
+segments = km_segmentation(img, ratio=2.0, n_segments=200)
+
+print("number of segments: %d" % len(np.unique(segments)))
+
+plt.subplot(131, title="original")
+plt.imshow(img, interpolation='nearest')
+plt.axis("off")
+
+plt.subplot(132, title="superpixels")
+# shuffle the labels for better visualization
+plt.imshow(segments, interpolation='nearest', cmap=plt.cm.prism)
+plt.axis("off")
+
+plt.subplot(133, title="mean color")
+colors = [np.bincount(segments.ravel(), img[:, :, c].ravel()) for c in
+        xrange(img.shape[2])]
+counts = np.bincount(segments.ravel())
+colors = np.vstack(colors) / counts
+plt.imshow(colors.T[segments], interpolation='nearest')
+plt.axis("off")
+
+plt.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9,
+                    bottom=0.02, left=0.02, right=0.98)
+plt.show()