This script illustrates how to use basic NumPy operations, such as slicing, masking and fancy indexing, in order to modify the pixel values of an image.
Sourceimport numpy as np
from skimage import data
import matplotlib.pyplot as plt
camera = data.camera()
camera[:10] = 0
mask = camera < 87
camera[mask] = 255
inds_x = np.arange(len(camera))
inds_y = (4 * inds_x) % len(camera)
camera[inds_x, inds_y] = 0
l_x, l_y = camera.shape[0], camera.shape[1]
X, Y = np.ogrid[:l_x, :l_y]
outer_disk_mask = (X - l_x / 2)**2 + (Y - l_y / 2)**2 > (l_x / 2)**2
camera[outer_disk_mask] = 0
plt.figure(figsize=(4, 4))
plt.imshow(camera, cmap='gray', interpolation='nearest')
plt.axis('off')
plt.show()
Total running time of the script: ( 0 minutes 0.135 seconds)