sklearn.datasets.fetch_olivetti_faces(data_home=None, shuffle=False, random_state=0, download_if_missing=True)
[source]
Loader for the Olivetti faces data-set from AT&T.
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. 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. random_state : optional, integer or RandomState object The seed or the random number generator used to shuffle the data. |
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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. |
This dataset consists of 10 pictures each of 40 individuals. The original database was available from (now defunct)
http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.htmlThe version retrieved here comes in MATLAB format from the personal web page of Sam Roweis:
http://www.cs.nyu.edu/~roweis/sklearn.datasets.fetch_olivetti_faces
© 2007–2016 The scikit-learn developers
Licensed under the 3-clause BSD License.
http://scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_olivetti_faces.html