cifar10

Description:

The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.

Homepage: https://www.cs.toronto.edu/~kriz/cifar.html
Source code: tfds.image_classification.Cifar10
Versions:
- 3.0.2 (default): No release notes.
Download size: 162.17 MiB
Dataset size: 132.40 MiB
Auto-cached (documentation): Yes
Splits:

Split	Examples
`'test'`	10,000
`'train'`	50,000

Features:

FeaturesDict({
    'id': Text(shape=(), dtype=tf.string),
    'image': Image(shape=(32, 32, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=10),
})

Supervised keys (See as_supervised doc): ('image', 'label')
Citation:

@TECHREPORT{Krizhevsky09learningmultiple,
    author = {Alex Krizhevsky},
    title = {Learning multiple layers of features from tiny images},
    institution = {},
    year = {2009}
}

Visualization (tfds.show_examples):

Visualization