Added example and test

doc/examples/plot_seam_carving.py

@@ -1,19 +1,38 @@
+"""
+============
+Seam Carving
+============
+
+This example demonstrates how images can be resized using seam carving [1]_.
+Resizing often distorts contents in the image. Seam carving tries to resize
+images while trying to keep important content intact. In this example we are
+using the Sobel filter to signify the importance of each pixel.
+
+.. [1] Shai Avidan and Ariel Shamir
+       "Seam Carving for Content-Aware Image Resizing"
+       http://www.cs.jhu.edu/~misha/ReadingSeminar/Papers/Avidan07.pdf
+
+"""
 from skimage import io, data
 from skimage import transform
 from skimage import color, filters
 from matplotlib import pyplot as plt
 
-def custom_sobel(img):
-    if img.ndim == 3:
-        img = color.rgb2gray(img)
-
-    return filters.sobel(img)
 
 img = data.coins()
-out  = transform.seam_carve(img, 'vertical', 80, energy_func = custom_sobel)
-out  = transform.seam_carve(out, 'horizontal', 70, energy_func = custom_sobel)
+out  = transform.seam_carve(img, 'vertical', 80, energy_func = filters.sobel)
+out  = transform.seam_carve(out, 'horizontal', 70, energy_func = filters.sobel)
+resized = transform.resize(img, out.shape)
+
+plt.title('Original Image')
+io.imshow(img, plugin='matplotlib')
 
-io.imshow(out)
 plt.figure()
-io.imshow(img)
+plt.title('Resized Image Image')
+io.imshow(resized, plugin='matplotlib')
+
+plt.figure()
+plt.title('Resized Image Image')
+io.imshow(out, plugin='matplotlib')
+
 io.show()