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# SlowOnly

## 简介

<!-- [ALGORITHM] -->

```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                                                                                                     |
| :-------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------: | :------: | :------: | :------: | :---------: | :---------: | :----------------: | :--------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_r50_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb.py)                                           | 短边 256 |   8x4    | ResNet50 |   None   |    72.76    |    90.51    |         x          |       3168       |                 [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_256p_4x16x1_256e_kinetics400_rgb/slowonly_r50_256p_4x16x1_256e_kinetics400_rgb_20200820-bea7701f.pth)                 |                                   [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_256p_4x16x1_256e_kinetics400_rgb/20200817_001411.log)                                    |                                 [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_256p_4x16x1_256e_kinetics400_rgb/20200817_001411.log.json)                                  |
| [slowonly_r50_video_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_r50_video_4x16x1_256e_kinetics400_rgb.py)                               | 短边 320 |   8x2    | ResNet50 |   None   |    72.90    |    90.82    |         x          |       8472       |           [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_video_320p_4x16x1_256e_kinetics400_rgb/slowonly_r50_video_320p_4x16x1_256e_kinetics400_rgb_20201014-c9cdc656.pth)           |          [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_video_320p_4x16x1_256e_kinetics400_rgb/slowonly_r50_video_320p_4x16x1_256e_kinetics400_rgb_20201014.log)          |          [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_video_320p_4x16x1_256e_kinetics400_rgb/slowonly_r50_video_320p_4x16x1_256e_kinetics400_rgb_20201014.json)          |
| [slowonly_r50_8x8x1_256e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_r50_8x8x1_256e_kinetics400_rgb.py)                                             | 短边 256 |   8x4    | ResNet50 |   None   |    74.42    |    91.49    |         x          |       5820       |                  [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_256p_8x8x1_256e_kinetics400_rgb/slowonly_r50_256p_8x8x1_256e_kinetics400_rgb_20200820-75851a7d.pth)                  |                                    [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_256p_8x8x1_256e_kinetics400_rgb/20200817_003320.log)                                    |                                  [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_256p_8x8x1_256e_kinetics400_rgb/20200817_003320.log.json)                                  |
| [slowonly_r50_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb.py)                                           | 短边 320 |   8x2    | ResNet50 |   None   |    73.02    |    90.77    | 4.0 (40x3 frames)  |       3168       |                      [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb/slowonly_r50_4x16x1_256e_kinetics400_rgb_20200704-a69556c6.pth)                      |                                          [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb/so_4x16.log)                                          |                             [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb/slowonly_r50_4x16_73.02_90.77.log.json)                             |
| [slowonly_r50_8x8x1_256e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_r50_8x8x1_256e_kinetics400_rgb.py)                                             | 短边 320 |   8x3    | ResNet50 |   None   |    74.93    |    91.92    | 2.3 (80x3 frames)  |       5820       |                       [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_8x8x1_256e_kinetics400_rgb/slowonly_r50_8x8x1_256e_kinetics400_rgb_20200703-a79c555a.pth)                       |                                           [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_8x8x1_256e_kinetics400_rgb/so_8x8.log)                                           |                              [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_8x8x1_256e_kinetics400_rgb/slowonly_r50_8x8_74.93_91.92.log.json)                              |
| [slowonly_imagenet_pretrained_r50_4x16x1_150e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_imagenet_pretrained_r50_4x16x1_150e_kinetics400_rgb.py)   | 短边 320 |   8x2    | ResNet50 | ImageNet |    73.39    |    91.12    |         x          |       3168       |  [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_4x16x1_150e_kinetics400_rgb/slowonly_imagenet_pretrained_r50_4x16x1_150e_kinetics400_rgb_20200912-1e8fc736.pth)  | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_4x16x1_150e_kinetics400_rgb/slowonly_imagenet_pretrained_r50_4x16x1_150e_kinetics400_rgb_20200912.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_4x16x1_150e_kinetics400_rgb/slowonly_imagenet_pretrained_r50_4x16x1_150e_kinetics400_rgb_20200912.json) |
| [slowonly_imagenet_pretrained_r50_8x8x1_150e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x8x1_150e_kinetics400_rgb.py)     | 短边 320 |   8x4    | ResNet50 | ImageNet |    75.55    |    92.04    |         x          |       5820       |   [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x8x1_150e_kinetics400_rgb/slowonly_imagenet_pretrained_r50_8x8x1_150e_kinetics400_rgb_20200912-3f9ce182.pth)   |  [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x8x1_150e_kinetics400_rgb/slowonly_imagenet_pretrained_r50_8x8x1_150e_kinetics400_rgb_20200912.log)  |  [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x8x1_150e_kinetics400_rgb/slowonly_imagenet_pretrained_r50_8x8x1_150e_kinetics400_rgb_20200912.json)  |
| [slowonly_nl_embedded_gaussian_r50_4x16x1_150e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_nl_embedded_gaussian_r50_4x16x1_150e_kinetics400_rgb.py) | 短边 320 |   8x2    | ResNet50 | ImageNet |    74.54    |    91.73    |         x          |       4435       | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_nl_embedded_gaussian_r50_4x16x1_150e_kinetics400_rgb/slowonly_nl_embedded_gaussian_r50_4x16x1_150e_kinetics400_rgb_20210308-0d6e5a69.pth) |                           [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_nl_embedded_gaussian_r50_4x16x1_150e_kinetics400_rgb/20210305_152630.log)                            |                         [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_nl_embedded_gaussian_r50_4x16x1_150e_kinetics400_rgb/20210305_152630.log.json)                          |
| [slowonly_nl_embedded_gaussian_r50_8x8x1_150e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_nl_embedded_gaussian_r50_8x8x1_150e_kinetics400_rgb.py)   | 短边 320 |   8x4    | ResNet50 | ImageNet |    76.07    |    92.42    |         x          |       8895       |  [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_nl_embedded_gaussian_r50_8x8x1_150e_kinetics400_rgb/slowonly_nl_embedded_gaussian_r50_8x8x1_150e_kinetics400_rgb_20210308-e8dd9e82.pth)  |                            [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_nl_embedded_gaussian_r50_8x8x1_150e_kinetics400_rgb/20210308_212250.log)                            |                          [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_nl_embedded_gaussian_r50_8x8x1_150e_kinetics400_rgb/20210308_212250.log.json)                          |
| [slowonly_r50_4x16x1_256e_kinetics400_flow](/configs/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_flow.py)                                         | 短边 320 |   8x2    | ResNet50 | ImageNet |    61.79    |    83.62    |         x          |       8450       |                     [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_flow/slowonly_r50_4x16x1_256e_kinetics400_flow_20200704-decb8568.pth)                     |                   [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_flow/slowonly_r50_4x16x1_256e_kinetics400_flow_61.8_83.6.log)                    |                 [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_flow/slowonly_r50_4x16x1_256e_kinetics400_flow_61.8_83.6.log.json)                  |
| [slowonly_r50_8x8x1_196e_kinetics400_flow](/configs/recognition/slowonly/slowonly_r50_8x8x1_256e_kinetics400_flow.py)                                           | 短边 320 |   8x4    | ResNet50 | ImageNet |    65.76    |    86.25    |         x          |       8455       |                      [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_8x8x1_256e_kinetics400_flow/slowonly_r50_8x8x1_256e_kinetics400_flow_20200704-6b384243.pth)                      |                    [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_8x8x1_256e_kinetics400_flow/slowonly_r50_8x8x1_196e_kinetics400_flow_65.8_86.3.log)                     |                  [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_8x8x1_256e_kinetics400_flow/slowonly_r50_8x8x1_196e_kinetics400_flow_65.8_86.3.log.json)                   |

### Kinetics-400 数据基准测试

在数据基准测试中，比较两种不同的数据预处理方法 (1) 视频分辨率为 340x256, (2) 视频分辨率为短边 320px, (3) 视频分辨率为短边 256px.

| 配置文件                                                                                                                                                                                 |  分辨率  | GPU 数量 | 主干网络 | 输入 | 预训练 | top1 准确率 | top5 准确率 |      测试方案      |                                                                                                                      ckpt                                                                                                                       |                                                                                                                  log                                                                                                                  |                                                                                                                  json                                                                                                                   |
| :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------: | :------: | :------: | :--: | :----: | :---------: | :---------: | :----------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_r50_randomresizedcrop_340x256_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowonly/data_benchmark/slowonly_r50_randomresizedcrop_340x256_4x16x1_256e_kinetics400_rgb.py) | 340x256  |   8x2    | ResNet50 | 4x16 |  None  |    71.61    |    90.05    | 10 clips x 3 crops | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/data_benchmark/slowonly_r50_randomresizedcrop_340x256_4x16x1_256e_kinetics400_rgb/slowonly_r50_randomresizedcrop_340x256_4x16x1_256e_kinetics400_rgb_20200803-dadca1a3.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/data_benchmark/slowonly_r50_randomresizedcrop_340x256_4x16x1_256e_kinetics400_rgb/slowonly_r50_randomresizedcrop_340x256_4x16x1_256e_kinetics400_rgb_20200803.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/data_benchmark/slowonly_r50_randomresizedcrop_340x256_4x16x1_256e_kinetics400_rgb/slowonly_r50_randomresizedcrop_340x256_4x16x1_256e_kinetics400_rgb_20200803.json) |
| [slowonly_r50_randomresizedcrop_320p_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowonly/data_benchmark/slowonly_r50_randomresizedcrop_320p_4x16x1_256e_kinetics400_rgb.py)       | 短边 320 |   8x2    | ResNet50 | 4x16 |  None  |    73.02    |    90.77    | 10 clips x 3 crops |                                  [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb/slowonly_r50_4x16x1_256e_kinetics400_rgb_20200704-a69556c6.pth)                                   |                                                       [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb/so_4x16.log)                                                        |                                          [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb/slowonly_r50_4x16_73.02_90.77.log.json)                                           |
| [slowonly_r50_randomresizedcrop_256p_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowonly/data_benchmark/slowonly_r50_randomresizedcrop_256p_4x16x1_256e_kinetics400_rgb.py)       | 短边 256 |   8x4    | ResNet50 | 4x16 |  None  |    72.76    |    90.51    | 10 clips x 3 crops |                             [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_256p_4x16x1_256e_kinetics400_rgb/slowonly_r50_256p_4x16x1_256e_kinetics400_rgb_20200820-bea7701f.pth)                              |                                                 [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_256p_4x16x1_256e_kinetics400_rgb/20200817_001411.log)                                                 |                                               [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_256p_4x16x1_256e_kinetics400_rgb/20200817_001411.log.json)                                               |

### Kinetics-400 OmniSource Experiments

|                                                       配置文件                                                        |  分辨率  | 主干网络  | 预训练 |   w. OmniSource    | top1 准确率 | top5 准确率 |                                                                                     ckpt                                                                                     |                                                           log                                                            |                                                                         json                                                                         |
| :-------------------------------------------------------------------------------------------------------------------: | :------: | :-------: | :----: | :----------------: | :---------: | :---------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_r50_4x16x1_256e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb.py) | 短边 320 | ResNet50  |  None  |        :x:         |    73.0     |    90.8     | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb/slowonly_r50_4x16x1_256e_kinetics400_rgb_20200704-a69556c6.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb/so_4x16.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb/slowonly_r50_4x16_73.02_90.77.log.json) |
|                                                           x                                                           |    x     | ResNet50  |  None  | :heavy_check_mark: |    76.8     |    92.5     |                   [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/omni/slowonly_r50_omni_4x16x1_kinetics400_rgb_20200926-51b1f7ea.pth)                   |                                                            x                                                             |                                                                          x                                                                           |
| [slowonly_r101_8x8x1_196e_kinetics400_rgb](/configs/recognition/slowonly/slowonly_r101_8x8x1_196e_kinetics400_rgb.py) |    x     | ResNet101 |  None  |        :x:         |    76.5     |    92.7     |               [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/omni/slowonly_r101_without_omni_8x8x1_kinetics400_rgb_20200926-0c730aef.pth)               |                                                            x                                                             |                                                                          x                                                                           |
|                                                           x                                                           |    x     | ResNet101 |  None  | :heavy_check_mark: |    80.4     |    94.4     |                   [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/omni/slowonly_r101_omni_8x8x1_kinetics400_rgb_20200926-b5dbb701.pth)                   |                                                            x                                                             |                                                                          x                                                                           |

### Kinetics-600

| 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 |                                                                                          ckpt                                                                                          |                                                                                     log                                                                                      |                                                                                      json                                                                                      |
| :------------------------------------------------------------------------------------------------------------------------------ | :------: | :------: | :------: | :----: | :---------: | :---------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_r50_video_8x8x1_256e_kinetics600_rgb](/configs/recognition/slowonly/slowonly_r50_video_8x8x1_256e_kinetics600_rgb.py) | 短边 256 |   8x4    | ResNet50 |  None  |    77.5     |    93.7     | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_video_8x8x1_256e_kinetics600_rgb/slowonly_r50_video_8x8x1_256e_kinetics600_rgb_20201015-81e5153e.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_video_8x8x1_256e_kinetics600_rgb/slowonly_r50_video_8x8x1_256e_kinetics600_rgb_20201015.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_video_8x8x1_256e_kinetics600_rgb/slowonly_r50_video_8x8x1_256e_kinetics600_rgb_20201015.json) |

### Kinetics-700

| 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 |                                                                                          ckpt                                                                                          |                                                                                     log                                                                                      |                                                                                      json                                                                                      |
| :------------------------------------------------------------------------------------------------------------------------------ | :------: | :------: | :------: | :----: | :---------: | :---------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_r50_video_8x8x1_256e_kinetics700_rgb](/configs/recognition/slowonly/slowonly_r50_video_8x8x1_256e_kinetics700_rgb.py) | 短边 256 |   8x4    | ResNet50 |  None  |    65.0     |    86.1     | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_video_8x8x1_256e_kinetics700_rgb/slowonly_r50_video_8x8x1_256e_kinetics700_rgb_20201015-9250f662.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_video_8x8x1_256e_kinetics700_rgb/slowonly_r50_video_8x8x1_256e_kinetics700_rgb_20201015.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_r50_video_8x8x1_256e_kinetics700_rgb/slowonly_r50_video_8x8x1_256e_kinetics700_rgb_20201015.json) |

### GYM99

| 配置文件                                                                                                                                          |  分辨率  | GPU 数量 | 主干网络 |  预训练  | top1 准确率 | 类别平均准确率 |                                                                                                    ckpt                                                                                                    |                                                                                               log                                                                                                |                                                                                                json                                                                                                |
| :------------------------------------------------------------------------------------------------------------------------------------------------ | :------: | :------: | :------: | :------: | :---------: | :------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_imagenet_pretrained_r50_4x16x1_120e_gym99_rgb](/configs/recognition/slowonly/slowonly_imagenet_pretrained_r50_4x16x1_120e_gym99_rgb.py) | 短边 256 |   8x2    | ResNet50 | ImageNet |    79.3     |      70.2      |  [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_4x16x1_120e_gym99_rgb/slowonly_imagenet_pretrained_r50_4x16x1_120e_gym99_rgb_20201111-a9c34b54.pth)  |  [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_4x16x1_120e_gym99_rgb/slowonly_imagenet_pretrained_r50_4x16x1_120e_gym99_rgb_20201111.log)  |  [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_4x16x1_120e_gym99_rgb/slowonly_imagenet_pretrained_r50_4x16x1_120e_gym99_rgb_20201111.json)  |
| [slowonly_kinetics_pretrained_r50_4x16x1_120e_gym99_flow](/configs/recognition/slowonly/slowonly_k400_pretrained_r50_4x16x1_120e_gym99_flow.py)   | 短边 256 |   8x2    | ResNet50 | Kinetics |    80.3     |      71.0      | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_kinetics_pretrained_r50_4x16x1_120e_gym99_flow/slowonly_kinetics_pretrained_r50_4x16x1_120e_gym99_flow_20201111-66ecdb3c.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_kinetics_pretrained_r50_4x16x1_120e_gym99_flow/slowonly_kinetics_pretrained_r50_4x16x1_120e_gym99_flow_20201111.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_kinetics_pretrained_r50_4x16x1_120e_gym99_flow/slowonly_kinetics_pretrained_r50_4x16x1_120e_gym99_flow_20201111.json) |
| 1: 1 融合                                                                                                                                         |          |          |          |          |    83.7     |      74.8      |                                                                                                                                                                                                            |                                                                                                                                                                                                  |                                                                                                                                                                                                    |

### Jester

| 配置文件                                                                                                                                        | 分辨率 | GPU 数量 | 主干网络 |  预训练  | top1 准确率 |                                                                                             ckpt                                                                                              |                                                                                         log                                                                                         |                                                                                         json                                                                                          |
| :---------------------------------------------------------------------------------------------------------------------------------------------- | :----: | :------: | :------: | :------: | :---------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_imagenet_pretrained_r50_8x8x1_64e_jester_rgb](/configs/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x8x1_64e_jester_rgb.py) | 高 100 |    8     | ResNet50 | ImageNet |    97.2     | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x8x1_64e_jester_rgb/slowonly_imagenet_pretrained_r50_8x8x1_64e_jester_rgb-b56a5389.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x8x1_64e_jester_rgb/slowonly_imagenet_pretrained_r50_8x8x1_64e_jester_rgb.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x8x1_64e_jester_rgb/slowonly_imagenet_pretrained_r50_8x8x1_64e_jester_rgb.json) |

### HMDB51

| 配置文件                                                                                                                                        | GPU 数量 | 主干网络 |   预训练    | top1 准确率 | top5 准确率 | GPU 显存占用 (M) |                                                                                                  ckpt                                                                                                  |                                                                      log                                                                      |                                                                        json                                                                         |
| :---------------------------------------------------------------------------------------------------------------------------------------------- | :------: | :------: | :---------: | :---------: | :---------: | :--------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_imagenet_pretrained_r50_8x4x1_64e_hmdb51_rgb](/configs/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_hmdb51_rgb.py) |    8     | ResNet50 |  ImageNet   |    37.52    |    71.50    |       5812       | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_hmdb51_rgb/slowonly_imagenet_pretrained_r50_8x4x1_64e_hmdb51_rgb_20210630-16faeb6a.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_hmdb51_rgb/20210605_185256.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_hmdb51_rgb/20210605_185256.log.json) |
| [slowonly_k400_pretrained_r50_8x4x1_40e_hmdb51_rgb](/configs/recognition/slowonly/slowonly_k400_pretrained_r50_8x4x1_40e_hmdb51_rgb.py)         |    8     | ResNet50 | Kinetics400 |    65.95    |    91.05    |       5812       |     [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_k400_pretrained_r50_8x4x1_40e_hmdb51_rgb/slowonly_k400_pretrained_r50_8x4x1_40e_hmdb51_rgb_20210630-cee5f725.pth)     |   [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_k400_pretrained_r50_8x4x1_40e_hmdb51_rgb/20210606_010153.log)   |   [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_k400_pretrained_r50_8x4x1_40e_hmdb51_rgb/20210606_010153.log.json)   |

### UCF101

| 配置文件                                                                                                                                        | GPU 数量 | 主干网络 |   预训练    | top1 准确率 | top5 准确率 | GPU 显存占用 (M) |                                                                                                  ckpt                                                                                                  |                                                                      log                                                                      |                                                                        json                                                                         |
| :---------------------------------------------------------------------------------------------------------------------------------------------- | :------: | :------: | :---------: | :---------: | :---------: | :--------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_imagenet_pretrained_r50_8x4x1_64e_ucf101_rgb](/configs/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_ucf101_rgb.py) |    8     | ResNet50 |  ImageNet   |    71.35    |    89.35    |       5812       | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_ucf101_rgb/slowonly_imagenet_pretrained_r50_8x4x1_64e_ucf101_rgb_20210630-181e1661.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_ucf101_rgb/20210605_213503.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_ucf101_rgb/20210605_213503.log.json) |
| [slowonly_k400_pretrained_r50_8x4x1_40e_ucf101_rgb](/configs/recognition/slowonly/slowonly_k400_pretrained_r50_8x4x1_40e_ucf101_rgb.py)         |    8     | ResNet50 | Kinetics400 |    92.78    |    99.42    |       5812       |     [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_k400_pretrained_r50_8x4x1_40e_ucf101_rgb/slowonly_k400_pretrained_r50_8x4x1_40e_ucf101_rgb_20210630-ee8c850f.pth)     |   [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_k400_pretrained_r50_8x4x1_40e_ucf101_rgb/20210606_010231.log)   |   [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_k400_pretrained_r50_8x4x1_40e_ucf101_rgb/20210606_010231.log.json)   |

### Something-Something V1

| 配置文件                                                                                                                                      | GPU 数量 | 主干网络 |  预训练  | top1 准确率 | top5 准确率 | GPU 显存占用 (M) |                                                                                                 ckpt                                                                                                 |                                                                                        log                                                                                        |                                                                                        json                                                                                         |
| :-------------------------------------------------------------------------------------------------------------------------------------------- | :------: | :------: | :------: | :---------: | :---------: | :--------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [slowonly_imagenet_pretrained_r50_8x4x1_64e_sthv1_rgb](/configs/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_sthv1_rgb.py) |    8     | ResNet50 | ImageNet |    47.76    |    77.49    |       7759       | [ckpt](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_sthv1_rgb/slowonly_imagenet_pretrained_r50_8x4x1_64e_sthv1_rgb_20211202-d034ff12.pth) | [log](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_sthv1_rgb/slowonly_imagenet_pretrained_r50_8x4x1_64e_sthv1_rgb.log) | [json](https://download.openmmlab.com/mmaction/recognition/slowonly/slowonly_imagenet_pretrained_r50_8x4x1_64e_sthv1_rgb/slowonly_imagenet_pretrained_r50_8x4x1_64e_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 SlowOnly 模型在 Kinetics400 数据集上的训练。

```shell
python tools/train.py configs/recognition/slowonly/slowonly_r50_4x16x1_256e_kinetics400_rgb.py \
    --work-dir work_dirs/slowonly_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 Kinetics400 数据集上测试 SlowOnly 模型，并将结果导出为一个 json 文件。

```shell
python tools/test.py configs/recognition/slowonly/slowonly_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。