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Using simple NumPy operations for manipulating images#
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.
![plot camera numpy](../../_images/sphx_glr_plot_camera_numpy_001.png)
import 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')
plt.axis('off')
plt.show()
Total running time of the script: (0 minutes 0.097 seconds)