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Overlay an image segmentation with Numpy and Matplotlib
To overlay an image segmentation with numpy, we can take the following Steps −
Make a masked array of 10×10 dimension.
Update the masked array with 1 for some region.
Make image data using numpy.
Mask an array where a condition is met, to get the masked data.
Create a new figure or activate an existing figure using figure() mrthod.
Use imshow() method to display data as an image, i.e., on a 2D regular raster.
To display the figure, use show() method.
Example
from matplotlib import pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True mask = np.zeros((10, 10)) mask[3:-3, 3:-3] = 1 im = mask + np.random.randn(10, 10) * 0.01 masked = np.ma.masked_where(mask == 0, mask) plt.figure() plt.subplot(1, 2, 1) plt.imshow(im, 'gray', interpolation='none') plt.subplot(1, 2, 2) plt.imshow(im, 'gray', interpolation='none') plt.imshow(masked, 'jet', interpolation='none', alpha=0.7) plt.show()
Output
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