Vame-py

Fixes

- OS aware dependencies installation, specially important for pytorch

Features

- Initialize project and run pipeline without videos ([Issue 129](https://github.com/EthoML/VAME/issues/129))
- Allow adding videos later on in the project ([Issue 129](https://github.com/EthoML/VAME/issues/129))
- Run on Google colab tags in documentation pages ([Issue 144](https://github.com/EthoML/VAME/issues/144))

Fixes

- Egocentric alignment outputs with incorrect column order ([Issue 96](https://github.com/EthoML/VAME/issues/96))
- Slow align egocentrical data ([Issue 113](https://github.com/EthoML/VAME/issues/113))
- Standardized config argument across all functions

Features

- User friendly way to select reference points for alignment ([Issue 89](https://github.com/EthoML/VAME/issues/89))
- Adopt movement Xarray data format ([Issue 111](https://github.com/EthoML/VAME/issues/111))
- Relocate IQR cleaning into preprocessing ([Issue 22](https://github.com/EthoML/VAME/issues/22))
- Created preprocessing module ([Issue 119](https://github.com/EthoML/VAME/issues/119))
- Separate module for visualization of results ([Issue 127](https://github.com/EthoML/VAME/issues/127))
- Further improvements to Pipeline

Fixes

- Removed auto adding date from poject names (105)
- Renamed `parametrization` to `segmentation_algorithm` (106)
- Renamed `file` to `session` (107)
- Removed old doctrings at top of files (108)
- Build compatibility with SLEAP (39)
- Build compatibility with LightningPose (115)
- `num_features` should be extracted from DLC data (100)
- Create VAME Project Class (42)

Features
- Improve handling of user input (cli) when `all_data==no`
- `vame.report()` saves figures to `<project_path>/reports/` folder
- Created `VAMEPipeline` class that makes it straightforward to run an entire pipeline, and also to pick it up from where it last stopped
- Use https://github.com/neuroinformatics-unit/movement as main data ingestion interface