# SlowFast ## 简介 ```BibTeX @inproceedings{feichtenhofer2019slowfast, title={Slowfast networks for video recognition}, author={Feichtenhofer, Christoph and Fan, Haoqi and Malik, Jitendra and He, Kaiming}, booktitle={Proceedings of the IEEE international conference on computer vision}, pages={6202--6211}, year={2019} } ``` ## 模型库 ### Kinetics-400 | 配置文件 | 分辨率 | GPU 数量 | 主干网络 | 预训练 | top1 准确率 | top5 准确率 | 推理时间 (video/s) | GPU 显存占用 (M) | ckpt | log | json | | :-------------------------------------------------------------------------------------------------------------------------------------- | :-----: | :------: | :------------------: | :----: | :---------: | :---------: | :----------------------: | :--------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | [slowfast_r50_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowfast/slowfast_r50_4x16x1_256e_kinetics400_rgb.py) | 短边256 | 8x4 | ResNet50 | None | 74.75 | 91.73 | x | 6203 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_256p_4x16x1_256e_kinetics400_rgb/slowfast_r50_256p_4x16x1_256e_kinetics400_rgb_20200728-145f1097.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_256p_4x16x1_256e_kinetics400_rgb/20200731_151706.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_256p_4x16x1_256e_kinetics400_rgb/20200731_151706.log.json) | | [slowfast_r50_video_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowfast/slowfast_r50_video_4x16x1_256e_kinetics400_rgb.py) | 短边256 | 8 | ResNet50 | None | 73.95 | 91.50 | x | 6203 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_video_4x16x1_256e_kinetics400_rgb/slowfast_r50_video_4x16x1_256e_kinetics400_rgb_20200826-f85b90c5.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_video_4x16x1_256e_kinetics400_rgb/20200812_160237.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_video_4x16x1_256e_kinetics400_rgb/20200812_160237.log.json) | | [slowfast_r50_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowfast/slowfast_r50_4x16x1_256e_kinetics400_rgb.py) | 短边320 | 8x2 | ResNet50 | None | 76.0 | 92.54 | 1.6 ((32+4)x10x3 frames) | 6203 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_4x16x1_256e_kinetics400_rgb/slowfast_r50_4x16x1_256e_kinetics400_rgb_20210722-04e43ed4.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_4x16x1_256e_kinetics400_rgb/slowfast_r50_4x16x1_20210722.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_4x16x1_256e_kinetics400_rgb/slowfast_r50_4x16x1_20210722.log.json) | | [slowfast_prebn_r50_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowfast/slowfast_prebn_r50_4x16x1_256e_kinetics400_rgb.py) | 短边320 | 8x2 | ResNet50 | None | 76.34 | 92.67 | x | 6203 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_prebn_r50_4x16x1_256e_kinetics400_rgb/slowfast_prebn_r50_4x16x1_256e_kinetics400_rgb_20210722-bb725050.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_prebn_r50_4x16x1_256e_kinetics400_rgb/slowfast_prebn_r50_4x16x1_20210722.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_prebn_r50_4x16x1_256e_kinetics400_rgb/slowfast_prebn_r50_4x16x1_20210722.log.json) | | [slowfast_r50_8x8x1_256e_kinetics400_rgb](/configs/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb.py) | 短边320 | 8x3 | ResNet50 | None | 76.94 | 92.8 | 1.3 ((32+8)x10x3 frames) | 9062 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb/slowfast_r50_8x8x1_256e_kinetics400_rgb_20200716-73547d2b.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb/20200716_192653.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb/20200716_192653.log.json) | | [slowfast_r50_8x8x1_256e_kinetics400_rgb_steplr](/configs/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb.py) | 短边320 | 8x4 | ResNet50 | None | 76.34 | 92.61 | 1.3 ((32+8)x10x3 frames) | 9062 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb_steplr/slowfast_r50_8x8x1_256e_kinetics400_rgb_steplr-43988bac.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb_steplr/slowfast_r50_8x8x1_256e_kinetics400_rgb_steplr.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb_steplr/slowfast_r50_8x8x1_256e_kinetics400_rgb_steplr.json) | | [slowfast_multigrid_r50_8x8x1_358e_kinetics400_rgb](/configs/recognition/slowfast/slowfast_multigrid_r50_8x8x1_358e_kinetics400_rgb.py) | 短边320 | 8x2 | ResNet50 | None | 76.07 | 92.21 | x | 9062 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_multigrid_r50_8x8x1_358e_kinetics400_rgb/slowfast_multigrid_r50_8x8x1_358e_kinetics400_rgb-f82bd304.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_multigrid_r50_8x8x1_358e_kinetics400_rgb/slowfast_multigrid_r50_8x8x1_358e_kinetics400_rgb.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_multigrid_r50_8x8x1_358e_kinetics400_rgb/slowfast_multigrid_r50_8x8x1_358e_kinetics400_rgb.json) | | [slowfast_prebn_r50_8x8x1_256e_kinetics400_rgb_steplr](/configs/recognition/slowfast/slowfast_prebn_r50_8x8x1_256e_kinetics400_rgb.py) | 短边320 | 8x4 | ResNet50 | None | 76.58 | 92.85 | 1.3 ((32+8)x10x3 frames) | 9062 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_prebn_r50_8x8x1_256e_kinetics400_rgb_steplr/slowfast_prebn_r50_8x8x1_256e_kinetics400_rgb_steplr-28474e54.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_prebn_r50_8x8x1_256e_kinetics400_rgb_steplr/slowfast_prebn_r50_8x8x1_256e_kinetics400_rgb_steplr.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_prebn_r50_8x8x1_256e_kinetics400_rgb_steplr/slowfast_prebn_r50_8x8x1_256e_kinetics400_rgb_steplr.json) | | [slowfast_r101_r50_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowfast/slowfast_r101_r50_4x16x1_256e_kinetics400_rgb.py) | 短边256 | 8x1 | ResNet101 + ResNet50 | None | 76.69 | 93.07 | | 16628 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r101_4x16x1_256e_kinetics400_rgb/slowfast_r101_4x16x1_256e_kinetics400_rgb_20210218-d8b58813.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r101_4x16x1_256e_kinetics400_rgb/20210118_133528.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r101_4x16x1_256e_kinetics400_rgb/20210118_133528.log.json) | | [slowfast_r101_8x8x1_256e_kinetics400_rgb](/configs/recognition/slowfast/slowfast_r101_8x8x1_256e_kinetics400_rgb.py) | 短边256 | 8x4 | ResNet101 | None | 77.90 | 93.51 | | 25994 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r101_8x8x1_256e_kinetics400_rgb/slowfast_r101_8x8x1_256e_kinetics400_rgb_20210218-0dd54025.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r101_8x8x1_256e_kinetics400_rgb/20210218_121513.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r101_8x8x1_256e_kinetics400_rgb/20210218_121513.log.json) | | [slowfast_r152_r50_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowfast/slowfast_r152_r50_4x16x1_256e_kinetics400_rgb.py) | 短边256 | 8x1 | ResNet152 + ResNet50 | None | 77.13 | 93.20 | | 10077 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r152_4x16x1_256e_kinetics400_rgb/slowfast_r152_4x16x1_256e_kinetics400_rgb_20210122-bdeb6b87.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r152_4x16x1_256e_kinetics400_rgb/20210122_131321.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r152_4x16x1_256e_kinetics400_rgb/20210122_131321.log.json) | ### Something-Something V1 | 配置文件 | 分辨率 | GPU 数量 | 主干网络 | 预训练 | top1 准确率 | top5 准确率 | 推理时间 (video/s) | GPU 显存占用 (M) | ckpt | log | json | | :------------------------------------------------------------------------------------------------------ | :----: | :------: | :------: | :---------: | :---------: | :---------: | :----------------: | :--------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------: | | [slowfast_r50_16x8x1_22e_sthv1_rgb](/configs/recognition/slowfast/slowfast_r50_16x8x1_22e_sthv1_rgb.py) | 高 100 | 8 | ResNet50 | Kinetics400 | 49.67 | 79.00 | x | 9293 | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_16x8x1_22e_sthv1_rgb/slowfast_r50_16x8x1_22e_sthv1_rgb_20211202-aaaf9279.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_16x8x1_22e_sthv1_rgb/slowfast_r50_16x8x1_22e_sthv1_rgb.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_16x8x1_22e_sthv1_rgb/slowfast_r50_16x8x1_22e_sthv1_rgb.json) | 注： 1. 这里的 **GPU 数量** 指的是得到模型权重文件对应的 GPU 个数。默认地，MMAction2 所提供的配置文件对应使用 8 块 GPU 进行训练的情况。 依据 [线性缩放规则](https://arxiv.org/abs/1706.02677)，当用户使用不同数量的 GPU 或者每块 GPU 处理不同视频个数时，需要根据批大小等比例地调节学习率。 如，lr=0.01 对应 4 GPUs x 2 video/gpu，以及 lr=0.08 对应 16 GPUs x 4 video/gpu。 2. 这里的 **推理时间** 是根据 [基准测试脚本](/tools/analysis/benchmark.py) 获得的，采用测试时的采帧策略，且只考虑模型的推理时间， 并不包括 IO 时间以及预处理时间。对于每个配置，MMAction2 使用 1 块 GPU 并设置批大小（每块 GPU 处理的视频个数）为 1 来计算推理时间。 3. 我们使用的 Kinetics400 验证集包含 19796 个视频，用户可以从 [验证集视频](https://mycuhk-my.sharepoint.com/:u:/g/personal/1155136485_link_cuhk_edu_hk/EbXw2WX94J1Hunyt3MWNDJUBz-nHvQYhO9pvKqm6g39PMA?e=a9QldB) 下载这些视频。同时也提供了对应的 [数据列表](https://download.openmmlab.com/mmaction/dataset/k400_val/kinetics_val_list.txt) （每行格式为：视频 ID，视频帧数目，类别序号）以及 [标签映射](https://download.openmmlab.com/mmaction/dataset/k400_val/kinetics_class2ind.txt) （类别序号到类别名称）。 对于数据集准备的细节，用户可参考 [数据集准备文档](/docs/zh_cn/data_preparation.md) 中的 Kinetics400 部分。 ## 如何训练 用户可以使用以下指令进行模型训练。 ```shell python tools/train.py ${CONFIG_FILE} [optional arguments] ``` 例如：以一个确定性的训练方式，辅以定期的验证过程进行 SlowFast 模型在 Kinetics400 数据集上的训练。 ```shell python tools/train.py configs/recognition/slowfast/slowfast_r50_4x16x1_256e_kinetics400_rgb.py \ --work-dir work_dirs/slowfast_r50_4x16x1_256e_kinetics400_rgb \ --validate --seed 0 --deterministic ``` 更多训练细节，可参考 [基础教程](/docs/zh_cn/getting_started.md#训练配置) 中的 **训练配置** 部分。 ## 如何测试 用户可以使用以下指令进行模型测试。 ```shell python tools/test.py ${CONFIG_FILE} ${CHECKPOINT_FILE} [optional arguments] ``` 例如：在 SlowFast 数据集上测试 CSN 模型，并将结果导出为一个 json 文件。 ```shell python tools/test.py configs/recognition/slowfast/slowfast_r50_4x16x1_256e_kinetics400_rgb.py \ checkpoints/SOME_CHECKPOINT.pth --eval top_k_accuracy mean_class_accuracy \ --out result.json --average-clips=prob ``` 更多测试细节，可参考 [基础教程](/docs/zh_cn/getting_started.md#测试某个数据集) 中的 **测试某个数据集** 部分。