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Efficiently Composable Data Augmentation on the GPU with Jax

Home Page: https://augmax.readthedocs.io/en/latest/

License: Apache License 2.0

Python 100.00%
gpu pre-processing jax

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leonhardfeiner

augmax's Issues

Git tags for releases?

Would it be possible to get git tags for releases? I can see that the latest version is 0.2.2 according to pypi, but in order to build from source I'm not sure which commit that corresponds to. Having releases tagged helps when packaging augmax for other package managers, eg. nixpkgs.

Semantics of `RandomCrop`

I have a few questions that AFAIU are not covered in the documentation,

  • What happens if the requested width/height are larger than the input image?
  • If the requested width/height is less than the input image, will the returned image lie outside the strict borders of the input? If so, what sort of padding is done?
  • If the requested width/height are exactly equal to the input image, does it reduce to the identity function?

I also consulted the albumentations API docs, but they didn't have much more information. So just putting these questions out into the ether...

Example Syntax Error

Small issue, front page of GitHub, on
Augmenting an entire batch of images on the GPU page,

sub_rngs = jax.random.split(rng, images.shape[0])
transformed_images = jax.jit(jax.vmap(transform))(sub_rng, images)

The last sub_rng should be changed to sub_rngs .
Thanks!

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