Mmaction2

**Highlights**
- Support [OmniSource](https://arxiv.org/abs/2003.13042)
- Support C3D
- Support video recognition with audio modality
- Support HVU
- Support X3D

**New Features**
- Support AVA dataset preparation ([266](https://github.com/open-mmlab/mmaction2/pull/266))
- Support the training of video recognition dataset with multiple tag categories ([235](https://github.com/open-mmlab/mmaction2/pull/235))
- Support joint training with multiple training datasets of multiple formats, including images, untrimmed videos, etc. ([242](https://github.com/open-mmlab/mmaction2/pull/242))
- Support to specify a start epoch to conduct evaluation ([216](https://github.com/open-mmlab/mmaction2/pull/216))
- Implement X3D models, support testing with model weights converted from SlowFast ([288](https://github.com/open-mmlab/mmaction2/pull/288))

**Improvements**
- Set default values of 'average_clips' in each config file so that there is no need to set it explicitly during testing in most cases ([232](https://github.com/open-mmlab/mmaction2/pull/232))
- Extend HVU datatools to generate individual file list for each tag category ([258](https://github.com/open-mmlab/mmaction2/pull/258))
- Support data preparation for Kinetics-600 and Kinetics-700 ([254](https://github.com/open-mmlab/mmaction2/pull/254))
- Add `cfg-options` in arguments to override some settings in the used config for convenience ([212](https://github.com/open-mmlab/mmaction2/pull/212))
- Rename the old evaluating protocol `mean_average_precision` as `mmit_mean_average_precision` since it is only used on MMIT and is not the `mAP` we usually talk about. Add `mean_average_precision`, which is the real `mAP` ([235](https://github.com/open-mmlab/mmaction2/pull/235))
- Add accurate setting (Three crop * 2 clip) and report corresponding performance for TSM model ([241](https://github.com/open-mmlab/mmaction2/pull/241))
- Add citations in each preparing_dataset.md in `tools/data/dataset` ([289](https://github.com/open-mmlab/mmaction2/pull/289))
- Update the performance of audio-visual fusion on Kinetics-400 ([281](https://github.com/open-mmlab/mmaction2/pull/281))
- Support data preparation of OmniSource web datasets, including GoogleImage, InsImage, InsVideo and KineticsRawVideo ([294](https://github.com/open-mmlab/mmaction2/pull/294))
- Use `metric_options` dict to provide metric args in `evaluate` ([286](https://github.com/open-mmlab/mmaction2/pull/286))

**Bug Fixes**
- Register `FrameSelector` in `PIPELINES` ([268](https://github.com/open-mmlab/mmaction2/pull/268))
- Fix the potential bug for default value in dataset_setting ([245](https://github.com/open-mmlab/mmaction2/pull/245))
- Fix the data preparation bug for `something-something` dataset ([278](https://github.com/open-mmlab/mmaction2/pull/278))
- Fix the invalid config url in slowonly README data benchmark ([249](https://github.com/open-mmlab/mmaction2/pull/249))
- Validate that the performance of models trained with videos have no significant difference comparing to the performance of models trained with rawframes ([256](https://github.com/open-mmlab/mmaction2/pull/256))
- Correct the `img_norm_cfg` used by TSN-3seg-R50 UCF-101 model, improve the Top-1 accuracy by 3% ([273](https://github.com/open-mmlab/mmaction2/pull/273))

**ModelZoo**
- Add Baselines for Kinetics-600 and Kinetics-700, including TSN-R50-8seg and SlowOnly-R50-8x8 ([259](https://github.com/open-mmlab/mmaction2/pull/259))
- Add OmniSource benchmark on MiniKineitcs ([296](https://github.com/open-mmlab/mmaction2/pull/296))
- Add Baselines for HVU, including TSN-R18-8seg on 6 tag categories of HVU ([287](https://github.com/open-mmlab/mmaction2/pull/287))
- Add X3D models ported from [SlowFast](https://github.com/facebookresearch/SlowFast/) ([#288](https://github.com/open-mmlab/mmaction2/pull/288))

**Highlights**
- Support TPN
- Support JHMDB, UCF101-24, HVU dataset preparation
- support onnx model conversion

**New Features**
- Support the data pre-processing pipeline for the HVU Dataset ([277](https://github.com/open-mmlab/mmaction2/pull/227/))
- Support real-time action recognition from web camera ([171](https://github.com/open-mmlab/mmaction2/pull/171))
- Support onnx ([160](https://github.com/open-mmlab/mmaction2/pull/160))
- Support UCF101-24 preparation ([219](https://github.com/open-mmlab/mmaction2/pull/219))
- Support evaluating mAP for ActivityNet with [CUHK17_activitynet_pred](http://activity-net.org/challenges/2017/evaluation.html) ([#176](https://github.com/open-mmlab/mmaction2/pull/176))
- Add the data pipeline for ActivityNet, including downloading videos, extracting RGB and Flow frames, finetuning TSN and extracting feature ([190](https://github.com/open-mmlab/mmaction2/pull/190))
- Support JHMDB preparation ([220](https://github.com/open-mmlab/mmaction2/pull/220))

**ModelZoo**
- Add finetuning setting for SlowOnly ([173](https://github.com/open-mmlab/mmaction2/pull/173))
- Add TSN and SlowOnly models trained with [OmniSource](https://arxiv.org/abs/2003.13042), which achieve 75.7% Top-1 with TSN-R50-3seg and 80.4% Top-1 with SlowOnly-R101-8x8 ([#215](https://github.com/open-mmlab/mmaction2/pull/215))

**Improvements**
- Support demo with video url ([165](https://github.com/open-mmlab/mmaction2/pull/165))
- Support multi-batch when testing ([184](https://github.com/open-mmlab/mmaction2/pull/184))
- Add tutorial for adding a new learning rate updater ([181](https://github.com/open-mmlab/mmaction2/pull/181))
- Add config name in meta info ([183](https://github.com/open-mmlab/mmaction2/pull/183))
- Remove git hash in `__version__` ([189](https://github.com/open-mmlab/mmaction2/pull/189))
- Check mmcv version ([189](https://github.com/open-mmlab/mmaction2/pull/189))
- Update url with 'https://download.openmmlab.com' ([#208](https://github.com/open-mmlab/mmaction2/pull/208))
- Update Docker file to support PyTorch 1.6 and update `install.md` ([209](https://github.com/open-mmlab/mmaction2/pull/209))
- Polish readsthedocs display ([217](https://github.com/open-mmlab/mmaction2/pull/217), [#229](https://github.com/open-mmlab/mmaction2/pull/229))

**Bug Fixes**
- Fix the bug when using OpenCV to extract only RGB frames with original shape ([184](https://github.com/open-mmlab/mmaction2/pull/187))
- Fix the bug of sthv2 `num_classes` from 339 to 174 ([174](https://github.com/open-mmlab/mmaction2/pull/174), [#207](https://github.com/open-mmlab/mmaction2/pull/207))

Highlights
- Support TIN, CSN, SSN, NonLocal
- Support FP16 training

New Features
- Support NonLocal module and provide ckpt in TSM and I3D ([41](https://github.com/open-mmlab/mmaction2/pull/41))
- Support SSN ([33](https://github.com/open-mmlab/mmaction2/pull/33), [#37](https://github.com/open-mmlab/mmaction2/pull/37), [#52](https://github.com/open-mmlab/mmaction2/pull/52), [#55](https://github.com/open-mmlab/mmaction2/pull/55))
- Support CSN ([87](https://github.com/open-mmlab/mmaction2/pull/87))
- Support TIN ([53](https://github.com/open-mmlab/mmaction2/pull/53))
- Support HMDB51 dataset preparation ([60](https://github.com/open-mmlab/mmaction2/pull/60))
- Support encoding videos from frames ([84](https://github.com/open-mmlab/mmaction2/pull/84))
- Support FP16 training ([25](https://github.com/open-mmlab/mmaction2/pull/25))
- Enhance demo by supporting rawframe inference ([59](https://github.com/open-mmlab/mmaction2/pull/59)), output video/gif ([#72](https://github.com/open-mmlab/mmaction2/pull/72))

ModelZoo
- Update Slowfast modelzoo ([51](https://github.com/open-mmlab/mmaction2/pull/51))
- Update TSN, TSM video checkpoints ([50](https://github.com/open-mmlab/mmaction2/pull/50))
- Add data benchmark for TSN ([57](https://github.com/open-mmlab/mmaction2/pull/57))
- Add data benchmark for SlowOnly ([77](https://github.com/open-mmlab/mmaction2/pull/77))
- Add BSN/BMN performance results with feature extracted by our codebase ([99](https://github.com/open-mmlab/mmaction2/pull/99))

Improvements
- Polish data preparation codes ([70](https://github.com/open-mmlab/mmaction2/pull/70))
- Improve data preparation scripts ([58](https://github.com/open-mmlab/mmaction2/pull/58))
- Improve unittest coverage and minor fix ([62](https://github.com/open-mmlab/mmaction2/pull/62))
- Support PyTorch 1.6 in CI ([117](https://github.com/open-mmlab/mmaction2/pull/117))
- Support `with_offset` for rawframe dataset ([48](https://github.com/open-mmlab/mmaction2/pull/48))
- Support json annotation files ([119](https://github.com/open-mmlab/mmaction2/pull/119))
- Support `multi-class` in TSMHead ([104](https://github.com/open-mmlab/mmaction2/pull/104))
- Support using `val_step()` to validate data for each `val` workflow ([123](https://github.com/open-mmlab/mmaction2/pull/123))
- Use `xxInit()` method to get `total_frames` and make `total_frames` a required key ([90](https://github.com/open-mmlab/mmaction2/pull/90))
- Add paper introduction in model readme ([140](https://github.com/open-mmlab/mmaction2/pull/140))
- Adjust the directory structure of `tools/` and rename some scripts files ([142](https://github.com/open-mmlab/mmaction2/pull/142))

Bug Fixes
- Fix configs for localization test ([67](https://github.com/open-mmlab/mmaction2/pull/67))
- Fix configs of SlowOnly by fixing lr to 8 gpus ([136](https://github.com/open-mmlab/mmaction2/pull/136))
- Fix the bug in analyze_log ([54](https://github.com/open-mmlab/mmaction2/pull/54))
- Fix the bug of generating HMDB51 class index file ([69](https://github.com/open-mmlab/mmaction2/pull/69))
- Fix the bug of using `load_checkpoint()` in ResNet ([93](https://github.com/open-mmlab/mmaction2/pull/93))
- Fix the bug of `--work-dir` when using slurm training script ([110](https://github.com/open-mmlab/mmaction2/pull/110))
- Correct the sthv1/sthv2 rawframes filelist generate command ([71](https://github.com/open-mmlab/mmaction2/pull/71))
- `CosineAnnealing` typo ([47](https://github.com/open-mmlab/mmaction2/pull/47))

The first release of MMAction2.