2018-03-14 08:16:14 -07:00
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# mnists
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downloads and prepares various mnist-compatible datasets.
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2018-03-14 08:53:25 -07:00
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files are downloaded to `~/.mnist`
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and checked for integrity by SHA-256 hashes.
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2018-03-14 08:16:14 -07:00
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2018-03-14 09:19:07 -07:00
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**dependencies:** python 3.6 (or later), numpy.
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2018-03-14 08:16:14 -07:00
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2018-03-14 09:19:07 -07:00
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**install:** `pip install --upgrade --upgrade-strategy only-if-needed 'https://github.com/notwa/mnists/tarball/master#egg=mnists'`
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2018-03-14 08:16:14 -07:00
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2018-03-14 08:53:25 -07:00
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I've added `--upgrade-strategy` to the command-line
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2018-03-14 08:16:14 -07:00
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so you don't accidentally "upgrade" numpy to
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a version not compiled specifically for your system.
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## usage
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```python
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import mnists
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dataset = "emnist_balanced"
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train_images, train_labels, test_images, test_labels = mnists.prepare(dataset)
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```
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2018-03-14 08:53:25 -07:00
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the default images shape is (n, 1, 28, 28).
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2018-03-14 08:16:14 -07:00
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pass `flatten=True` to `mnists.prepare` to get (n, 784).
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## datasets
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in alphabetical order:
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### [emnist][emnist]
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* `emnist_balanced`
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* `emnist_byclass`
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* `emnist_bymerge`
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* `emnist_digits`
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* `emnist_letters`
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* `emnist_mnist`
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### [fashion-mnist][fashion-mnist]
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* `fashion_mnist`
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### [mnist][mnist]
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* `mnist`
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[emnist]: //www.nist.gov/itl/iad/image-group/emnist-dataset
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[fashion-mnist]: //github.com/zalandoresearch/fashion-mnist
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[mnist]: http://yann.lecun.com/exdb/mnist/
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