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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, etc.
Features
- The library is Python-based and requires at least Python 3.6, as we use dataclasses
- AugLy is a Python 3.6+ library
- We provide various media assets to use with some of our augmentations
- AugLy is MIT licensed
- A new data augmentation library to help build more robust AI models
- AugLy is a novel open source data augmentation library that combines multiple modalities
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