emnist

• Visualization: Explore in Know Your Data north_east

• Description:

The EMNIST dataset is a set of handwritten character digits derived from the NIST Special Database 19 and converted to a 28x28 pixel image format and dataset structure that directly matches the MNIST dataset.

• Homepage: https://www.nist.gov/itl/products-and-services/emnist-dataset

• Source code: tfds.image_classification.EMNIST

• Versions:

  • 3.0.0 (default): New split API (https://tensorflow.org/datasets/splits)

• Download size: 535.73 MiB

• Dataset size: Unknown size

• Auto-cached (documentation): Unknown

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

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe): Missing.

• Citation:

@article{cohen_afshar_tapson_schaik_2017,
    title={EMNIST: Extending MNIST to handwritten letters},
    DOI={10.1109/ijcnn.2017.7966217},
    journal={2017 International Joint Conference on Neural Networks (IJCNN)},
    author={Cohen, Gregory and Afshar, Saeed and Tapson, Jonathan and Schaik, Andre Van},
    year={2017}
}

emnist/byclass (default config)

• Config description: EMNIST ByClass

• Splits:

Split	Examples
'test'	116,323
'train'	697,932

• Feature structure:

FeaturesDict({
    'image': Image(shape=(28, 28, 1), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=62),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
image	Image	(28, 28, 1)	tf.uint8
label	ClassLabel		tf.int64

emnist/bymerge

• Config description: EMNIST ByMerge

• Splits:

Split	Examples
'test'	116,323
'train'	697,932

• Feature structure:

FeaturesDict({
    'image': Image(shape=(28, 28, 1), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=47),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
image	Image	(28, 28, 1)	tf.uint8
label	ClassLabel		tf.int64

emnist/balanced

• Config description: EMNIST Balanced

• Splits:

Split	Examples
'test'	18,800
'train'	112,800

• Feature structure:

FeaturesDict({
    'image': Image(shape=(28, 28, 1), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=47),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
image	Image	(28, 28, 1)	tf.uint8
label	ClassLabel		tf.int64

emnist/letters

• Config description: EMNIST Letters

• Splits:

Split	Examples
'test'	14,800
'train'	88,800

• Feature structure:

FeaturesDict({
    'image': Image(shape=(28, 28, 1), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=37),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
image	Image	(28, 28, 1)	tf.uint8
label	ClassLabel		tf.int64

emnist/digits

• Config description: EMNIST Digits

• Splits:

Split	Examples
'test'	40,000
'train'	240,000

• Feature structure:

FeaturesDict({
    'image': Image(shape=(28, 28, 1), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=10),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
image	Image	(28, 28, 1)	tf.uint8
label	ClassLabel		tf.int64

emnist/mnist

• Config description: EMNIST MNIST

• Splits:

Split	Examples
'test'	10,000
'train'	60,000

• Feature structure:

FeaturesDict({
    'image': Image(shape=(28, 28, 1), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=10),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
image	Image	(28, 28, 1)	tf.uint8
label	ClassLabel		tf.int64