Machine Learning for OpenCV 4 - Second Edition

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 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 64-pixel ...