Changes
Audio:
- New augmentations: `loop`
- Efficiency improvements: made `high_pass_filter` & `low_pass_filter` ~97% faster by using `torchaudio`
Image:
- New augmentations: `skew`
- Added bbox computation helper `spatial_bbox_helper` to make it easier to add new image augmentations & automatically compute the bounding box transformations (e.g. see how we used this for `skew` [here](https://github.com/facebookresearch/AugLy/blob/main/augly/image/functional.py#L2430))
- Efficiency improvements: made `resize` ~35% faster by defaulting to bilinear interpolation
Text:
- Allow multi-word typo replacement
- Efficiency improvements: made `contractions`, `replace_similar_chars`, `replace_similar_unicode_chars`, `replace_upside_down` ~40-60% faster using algorithmic improvements
Video:
- Efficiency improvements: made 30 of the video augmentations faster using [`vidgear`](https://github.com/abhiTronix/vidgear) (a new dependency we added in this release) to execute `ffmpeg` commands using higher compression rates (e.g. `hflip` 75% faster, `loop` 85% faster, `remove_audio` 96% faster, `pixelization` 71% faster)
Overall:
- Modified internal imports to be Python 3.6-compatible
- Added error messages to unit tests for easier debugging
- If you want to see a full report benchmarking the runtimes of all AugLy augmentations versus other libraries, keep an eye out for the AugLy paper, which will be up on Arxiv in January!