sklearn.datasets.fetch_olivetti_faces
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sklearn.datasets.fetch_olivetti_faces(data_home=None, shuffle=False, random_state=0, download_if_missing=True)
[source]
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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 User Guide.
Parameters: |
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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:
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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