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rSSKJr  SSKJr  SSKJrJrJrJr  SS	KJrJr  SS
KJrJr  \" SSSS9r\" \\S/S/S/S/S/\" \SSSS9/\" \SSSS9/S.SS9SSSSSSSS.S j5       rg)a  Modified Olivetti faces dataset.

The original database was available from (now defunct)

    https://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html

The version retrieved here comes in MATLAB format from the personal
web page of Sam Roweis:

    https://cs.nyu.edu/~roweis/
    )IntegralReal)PathLikeremove)existsN)loadmat)get_data_home)RemoteFileMetadata_fetch_remote_pkl_filepath
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  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 :ref:`User Guide <olivetti_faces_dataset>`.

Parameters
----------
data_home : str or path-like, 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 : bool, default=False
    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 :term:`Glossary <random_state>`.

download_if_missing : bool, default=True
    If False, raise an OSError if the data is not locally available
    instead of trying to download the data from the source site.

return_X_y : bool, default=False
    If True, returns `(data, target)` instead of a `Bunch` object. See
    below for more information about the `data` and `target` object.

    .. versionadded:: 0.22

n_retries : int, default=3
    Number of retries when HTTP errors are encountered.

    .. versionadded:: 1.5

delay : float, default=1.0
    Number of seconds between retries.

    .. versionadded:: 1.5

Returns
-------
data : :class:`~sklearn.utils.Bunch`
    Dictionary-like object, with the following attributes.

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

(data, target) : tuple if `return_X_y=True`
    Tuple with the `data` and `target` objects described above.

    .. versionadded:: 0.22

Examples
--------
>>> from sklearn.datasets import fetch_olivetti_faces
>>> olivetti_faces = fetch_olivetti_faces()
>>> olivetti_faces.data.shape
(400, 4096)
>>> olivetti_faces.target.shape
(400,)
>>> olivetti_faces.images.shape
(400, 64, 64)
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   zolivetti_faces.rst)dataimagestargetDESCR)r	   r   r   OSErrorprintFACESr   r   r   r   Tcopyjoblibdumploadnpfloat32minmaxreshape	transposearrayranger   permutationlenr   r   )r   r   r   r   r   r    r!   filepathmat_pathmfiler'   ir1   orderfaces_vectorizedfdescrs                   b/var/www/html/dynamic-report/venv/lib/python3.13/site-packages/sklearn/datasets/_olivetti_faces.pyfetch_olivetti_facesrM   +   s|   P 	2IY7H("MNNEIIyQR 9
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