Issue
I have an segmented image into superpixels as follows:
from skimage.data import astronaut
img = astronaut()
segments_slic = slic(img, n_segments=250, compactness=10, sigma=1,
start_label=1)
fig = plt.figure(figsize = (16,8));
plt.imshow(mark_boundaries(img, segments_slic))
And got the following image:
I wish to cut a patch around each superpixel. Consider, for example, the patch around the shining part of the helmet colored red:
If I want to take a close (manual) look at the segments using plt.imshow(segments_slic[425:459,346:371])
, I get this patch around the segment:
The pixels with the specific superpixel labe streach on row 425:459
and on columns 346:371
.
Currently, I am doing this: patches = list()
for superpixel in np.unique(segments_slic ):
x_min = np.min(np.where(segments == 15)[0]);
x_max = np.max(np.where(segments == 15)[0]);
y_min = np.min(np.where(segments == 15)[1]);
y_max = np.max(np.where(segments == 15)[1]);
patches.append(I[x_min:x_max,y_min:y_max,:]);
Not sure if it is correct, though it seems to be fine. What is the best way to generate such a patch for each superpixel? Moreover, is it possible to set the pixels in the patch, which do not belong to the superpixel, to black?
Solution
You can use regionprops
and access the patch coordinates via region.bbox
as in
from skimage.data import astronaut
import matplotlib.pyplot as plt
from skimage.segmentation import slic
from skimage.segmentation import mark_boundaries
from skimage.measure import regionprops
import matplotlib.patches as mpatches
img = astronaut()
segments_slic = slic(img, n_segments=250, compactness=10, sigma=1, start_label=1)
fig, ax = plt.subplots(figsize=(16, 8))
ax.imshow(img)
for region in regionprops(segments_slic):
# draw rectangle around segmented coins
minr, minc, maxr, maxc = region.bbox
rect = mpatches.Rectangle((minc, minr), maxc - minc, maxr - minr,
fill=False, edgecolor='red', linewidth=2)
ax.add_patch(rect)
# access patch via img[minr:maxr, minc:maxc]
plt.imshow(mark_boundaries(img, segments_slic))
plt.show()
Example adapted from here.
EDIT: Furthermore, with region.image
you get a mask of your region to set the others to black.
Answered By - gfkri
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