2.6.8.13. Find the bounding box of an object

This example shows how to extract the bounding box of the largest object

import numpy as np
import scipy as sp
import matplotlib.pyplot as plt

rng = np.random.default_rng(27446968)
n = 10
l = 256
im = np.zeros((l, l))
points = l * rng.random((2, n**2))
im[(points[0]).astype(int), (points[1]).astype(int)] = 1
im = sp.ndimage.gaussian_filter(im, sigma=l / (4.0 * n))

mask = im > im.mean()

label_im, nb_labels = sp.ndimage.label(mask)

# Find the largest connected component
sizes = sp.ndimage.sum(mask, label_im, range(nb_labels + 1))
mask_size = sizes < 1000
remove_pixel = mask_size[label_im]
label_im[remove_pixel] = 0
labels = np.unique(label_im)
label_im = np.searchsorted(labels, label_im)

# Now that we have only one connected component, extract it's bounding box
slice_x, slice_y = sp.ndimage.find_objects(label_im == 4)[0]
roi = im[slice_x, slice_y]

plt.figure(figsize=(4, 2))
plt.axes([0, 0, 1, 1])
plt.imshow(roi)
plt.axis("off")

plt.show()