[Feature] Support Semi-supervised Oriented Object Detection: SOOD (CVPR 2023)

[Haru-zt]

Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers.

Motivation

Support Semi-supervised Oriented Object Detection: SOOD (CVPR 2023).
SOOD is based on mmrotate 0.x, but not work in mmrotate 1.x

Modification

1. SOOD configs files (including data augmentation)
2. Semi-base
3. SOOD code
4. OT loss used in SOOD
5. Mean Teacher Hook supports Burn-in strategy
6. provide README.md to split train set and start training

BC-breaking (Optional)

No

Use cases (Optional)

please refer to sood/README.md

Checklist

1. Pre-commit or other linting tools are used to fix the potential lint issues. Yes
2. The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
3. The documentation has been modified accordingly, like docstring or example tutorials. Yes

[CLAassistant]

All committers have signed the CLA.