Merge pull request #1459 from vighneshbirodkar/seam_carving

FEAT: Seam Carving

doc/examples/plot_seam_carving.py

@@ -0,0 +1,95 @@
+"""
+============
+Seam Carving
+============
+
+This example demonstrates how images can be resized using seam carving [1]_.
+Resizing to a new aspect ratio distorts image contents. Seam carving attempts
+to resize *without* distortion, by removing regions of an image which are less
+important. 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 data, draw
+from skimage import transform, util
+import numpy as np
+from skimage import filters, color
+from matplotlib import pyplot as plt
+
+
+hl_color = np.array([0, 1, 0])
+
+img = data.rocket()
+img = util.img_as_float(img)
+eimg = filters.sobel(color.rgb2gray(img))
+
+plt.title('Original Image')
+plt.imshow(img)
+
+"""
+.. image:: PLOT2RST.current_figure
+"""
+
+resized = transform.resize(img, (img.shape[0], img.shape[1] - 200))
+plt.figure()
+plt.title('Resized Image')
+plt.imshow(resized)
+
+
+"""
+.. image:: PLOT2RST.current_figure
+"""
+
+out = transform.seam_carve(img, eimg, 'vertical', 200)
+plt.figure()
+plt.title('Resized using Seam-Carving')
+plt.imshow(out)
+
+"""
+.. image:: PLOT2RST.current_figure
+
+As you can see, resizing as distorted the rocket and the objects around,
+whereas seam carving has reszied by removing the empty spaces in between.
+
+Object Removal
+--------------
+
+Seam Carving can also be used to remove atrifacts from images. To do that, we
+have to ensure that pixels to be removes get less importance. In the following
+code I approximately mark the rocket with a mask, and then decrease the
+importance of those pixels
+
+"""
+
+masked_img = img.copy()
+
+poly = [(404, 281), (404, 360), (359, 364), (338, 337), (145, 337), (120, 322),
+        (145, 304), (340, 306), (362, 284)]
+pr = np.array([p[0] for p in poly])
+pc = np.array([p[1] for p in poly])
+rr, cc = draw.polygon(pr, pc)
+
+masked_img[rr, cc, :] = masked_img[rr, cc, :]*0.5 + hl_color*.5
+plt.figure()
+plt.title('Object Marked')
+
+plt.imshow(masked_img)
+"""
+.. image:: PLOT2RST.current_figure
+"""
+
+eimg[rr, cc] -= 1000
+
+plt.figure()
+plt.title('Object Removed')
+out = transform.seam_carve(img, eimg, 'vertical', 90)
+resized = transform.resize(img, out.shape)
+plt.imshow(out)
+plt.show()
+"""
+.. image:: PLOT2RST.current_figure
+"""