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Machine Learning for OpenCV
book

Machine Learning for OpenCV

by Michael Beyeler, Michael Beyeler (USD)
July 2017
Intermediate to advanced
382 pages
9h 13m
English
Packt Publishing
Content preview from Machine Learning for OpenCV

Loading the dataset

Like many other classic datasets, the Olivetti face dataset can be loaded using scikit-learn:

In [1]: from sklearn.datasets import fetch_olivetti_faces...     dataset = fetch_olivetti_faces()In [2]: X = dataset.data...     y = dataset.target

Although the original images consisted of 92 x 112 pixel images, the version available through scikit-learn contains images downscaled to 64 x 64 pixels.

To get a sense of the dataset, we can plot some example images. Let's pick eight indices from the dataset in a random order:

In [3]: import numpy as np...     np.random.seed(21)...     idx_rand = np.random.randint(len(X), size=8)

We can plot these example images using Matplotlib, but we need to make sure we reshape the column vectors to 64 x ...

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Publisher Resources

ISBN: 9781783980284