README

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AugLy is a data augmentations library that currently supports four modalities (audio, image, text & video) and over 100 augmentations. Each modality’s augmentations are contained within its own sub-library. These sub-libraries include both function-based and class-based transforms, composition operators, and have the option to provide metadata about the transform applied, including its intensity.

AugLy is a great library to utilize for augmenting your data in model training, or to evaluate the robustness gaps of your model! We designed AugLy to include many specific data augmentations that users perform in real life on internet platforms like Facebook's -- for example making an image into a meme, overlaying text/emojis on images/videos, reposting a screenshot from social media. While AugLy contains more generic data augmentations as well, it will be particularly useful to you if you're working on a problem like copy detection, hate speech detection, or copyright infringement where these "internet user" types of data augmentations are prevalent.

!Visual

To see more examples of augmentations, open the Colab notebooks in the README for each modality! (e.g. image README & Colab)

The library is Python-based and requires at least Python 3.6, as we use dataclasses.

 Authors

Joanna Bitton — Software Engineer at Meta AI

Zoe Papakipos — Software Engineer at Meta AI

 Installation

AugLy is a Python 3.6+ library. It can be installed with:

bash
pip install augly[all]


If you want to only install the dependencies needed for one sub-library e.g. audio, you can install like so:

bash
pip install augly[audio]


Or clone AugLy if you want to be able to run our unit tests, contribute a pull request, etc:
bash
git clone [email protected]:facebookresearch/AugLy.git && cd AugLy
[Optional, but recommended] conda create -n augly && conda activate augly && conda install pip
pip install -e .[all]


Backwards compatibility note: In versions augly<=0.2.1 we did not separate the dependencies by modality. For those versions to install most dependencies you could use pip install augly, and if you want to use the audio or video modalities you would install with pip install augly[av].

In some environments, pip doesn't install python-magic as expected. In that case, you will need to additionally run:
bash
conda install -c conda-forge python-magic


Or if you aren't using conda:
bash
sudo apt-get install python3-magic


 Documentation

Check out our documentation on ReadtheDocs!

For more details about how to use each sub-library, how to run the tests, and links to colab notebooks with runnable examples, please see the READMEs in each respective directory (audio, image, text, & video).

 Assets

We provide various media assets to use with some of our augmentations. These assets include:
1. Emojis (Twemoji) - Copyright 2020 Twitter, Inc and other contributors. Code licensed under the MIT License. Graphics licensed under CC-BY 4.0.
2. Fonts (Noto font