Find the bounding box of an object

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

../../../_images/plot_find_object_1.png

Python ソースコード: plot_find_object.py

import numpy as np

from scipy import ndimage

import matplotlib.pyplot as plt



np.random.seed(1)

n = 10

l = 256

im = np.zeros((l, l))

points = l*np.random.random((2, n**2))

im[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1

im = ndimage.gaussian_filter(im, sigma=l/(4.*n))



mask = im > im.mean()



label_im, nb_labels = ndimage.label(mask)



# Find the largest connect component

sizes = 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 connect component, extract it's bounding box

slice_x, slice_y = 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()

Total running time of the example: 0.06 seconds ( 0 minutes 0.06 seconds)