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--- |
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task_categories: |
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- image-classification |
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- unconditional-image-generation |
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pretty_name: Easy MNIST |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Easy MNIST |
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MNIST processed into three easy to use formats. Each .zip file contains a labels_and_paths.csv file and a data directory. |
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|
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## mnist_png.zip |
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MNIST in the png format. |
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``` |
|
label path |
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0 5 data/0.png |
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1 0 data/1.png |
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2 4 data/2.png |
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3 1 data/3.png |
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4 9 data/4.png |
|
... ... ... |
|
69995 2 data/69995.png |
|
69996 3 data/69996.png |
|
69997 4 data/69997.png |
|
69998 5 data/69998.png |
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69999 6 data/69999.png |
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``` |
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|
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## mnist_numpy.zip |
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MNIST in the npy format. |
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``` |
|
label path |
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0 5 data/0.npy |
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1 0 data/1.npy |
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2 4 data/2.npy |
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3 1 data/3.npy |
|
4 9 data/4.npy |
|
... ... ... |
|
69995 2 data/69995.npy |
|
69996 3 data/69996.npy |
|
69997 4 data/69997.npy |
|
69998 5 data/69998.npy |
|
69999 6 data/69999.npy |
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``` |
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|
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## mnist_numpy_flat.zip |
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MNIST in the npy format, flattened to 784 dimensional vectors. |
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``` |
|
label path |
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0 5 data/0.npy |
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1 0 data/1.npy |
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2 4 data/2.npy |
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3 1 data/3.npy |
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4 9 data/4.npy |
|
... ... ... |
|
69995 2 data/69995.npy |
|
69996 3 data/69996.npy |
|
69997 4 data/69997.npy |
|
69998 5 data/69998.npy |
|
69999 6 data/69999.npy |
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``` |
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|
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## Acknowledgements |
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- Yann LeCun, Courant Institute, NYU |
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- Corinna Cortes, Google Labs, New York |
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- Christopher J.C. Burges, Microsoft Research, Redmond |
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|
