sklearn.datasets.fetch_olivetti_faces

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

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

Download it if necessary.

Classes 40
Samples total 400
Dimensionality 4096
Features real, between 0 and 1

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.