Cutting a patch around a segment of a segmented image-CodePudding

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?

CodePudding user response：

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()

This results in

Example adapted from here.

EDIT: Furthermore, with region.image you get a mask of your region to set the others to black.