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DOC: update view_as_blocks and gabors_from_lena example using comments from @stevanv (PR #138)

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Nicolas Pinto
2012-02-14 19:45:38 -05:00
parent 68f8c68c3f
commit 5e9ad08b80
2 changed files with 33 additions and 33 deletions
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doc/examples/plot_view_as_blocks.py
+15 -12
View File
@@ -3,25 +3,28 @@
Block views on images/arrays
============================
This example illustrates the use of `view_as_blocks` from `skimage.util.shape`.
Block views can be incredibly useful when one wants to perform local operations
on non-overlapping image patches.
This example illustrates the use of `view_as_blocks` from
`skimage.util.shape`. Block views can be incredibly useful when one
wants to perform local operations on non-overlapping image patches.
We use `lena` from `scipy.misc` and virtually 'slice' it into square blocks.
Then, on each block, we either pool the mean, the max or the median value of
that block. The results are displayed altogether, along with a 'classic'
`bicubic` rescaling of the original `lena` image.
We use `lena` from `skimage.data` and virtually 'slice' it into square
blocks. Then, on each block, we either pool the mean, the max or the
median value of that block. The results are displayed altogether, along
with a 'classic' `bicubic` rescaling of the original `lena` image.
"""
import numpy as np
from scipy.misc import lena, imresize
from scipy.misc import imresize
from matplotlib import pyplot as plt
import matplotlib.cm as cm
from skimage import data
from skimage import color
from skimage.util.shape import view_as_blocks
# -- get `lena` from scipy in grayscale
l = lena()
# -- get `lena` from skimage.data in grayscale
l = color.rgb2gray(data.lena()) / 255.
# -- size of blocks
block_shape = (4, 4)
@@ -43,7 +46,7 @@ median_view = np.median(flatten_view, axis=2)
plt.figure(figsize=(10, 10))
plt.subplot(221)
plt.title("Original rescaled\n in bicubic mode");
plt.title("Original rescaled\n in bicubic mode")
l_resized = imresize(l, view.shape[:2], interp='bicubic')
plt.imshow(l_resized, cmap=cm.Greys_r)
@@ -52,7 +55,7 @@ plt.title("Block view with\n local mean pooling")
plt.imshow(mean_view, cmap=cm.Greys_r)
plt.subplot(223)
plt.title("Block view with\n local max pooling");
plt.title("Block view with\n local max pooling")
plt.imshow(max_view, cmap=cm.Greys_r)
plt.subplot(224)