tf.keras.datasets.cifar100.load_data
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Loads CIFAR100 dataset.
tf.keras.datasets.cifar100.load_data(
label_mode='fine'
)
This is a dataset of 50,000 32x32 color training images and
10,000 test images, labeled over 100 fine-grained classes that are
grouped into 20 coarse-grained classes. See more info at the
CIFAR homepage.
Arguments |
|---|
label_mode
|
one of "fine", "coarse". If it is "fine" the category labels
are the fine-grained labels, if it is "coarse" the output labels are the
coarse-grained superclasses.
|
Returns |
|---|
Tuple of Numpy arrays: (x_train, y_train), (x_test, y_test).
x_train, x_test: uint8 arrays of RGB image data with shape
(num_samples, 3, 32, 32) if tf.keras.backend.image_data_format() is
'channels_first', or (num_samples, 32, 32, 3) if the data format
is 'channels_last'.
y_train, y_test: uint8 arrays of category labels with shape
(num_samples, 1).
|
Raises |
|---|
ValueError
|
in case of invalid label_mode.
|
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Last updated 2020-10-01 UTC.
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TensorFlow 1 version
View source on GitHub