sklearn.datasets.fetch_olivetti_faces — scikit-learn 0.20.4 documentation (original) (raw)
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.
| 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. |