`sklearn.datasets`.fetch_olivetti_faces¶

sklearn.datasets.fetch_olivetti_faces(data_home=None, shuffle=False, random_state=0, download_if_missing=True)[source]¶

Load the Olivetti faces data-set from AT&T (classification).

Download it if necessary.

Read more in the User Guide.

Parameters:

data_home : optional, default: None: Specify another download and cache folder for the datasets. By default all scikit-learn data is stored in ‘~/scikit_learn_data’ subfolders.
shuffle : boolean, optional: If True the order of the dataset is shuffled to avoid having images of the same person grouped.
random_state : int, RandomState instance or None (default=0): Determines random number generation for dataset shuffling. Pass an int for reproducible output across multiple function calls. See Glossary.
download_if_missing : optional, True by default: If False, raise a IOError if the data is not locally available instead of trying to download the data from the source site.

Returns:

An object with the following attributes:
data : numpy array of shape (400, 4096): Each row corresponds to a ravelled face image of original size 64 x 64 pixels.
images : numpy array of shape (400, 64, 64): Each row is a face image corresponding to one of the 40 subjects of the dataset.
target : numpy array of shape (400, ): Labels associated to each face image. Those labels are ranging from 0-39 and correspond to the Subject IDs.
DESCR : string: Description of the modified Olivetti Faces Dataset.

Examples using `sklearn.datasets.fetch_olivetti_faces`¶