update README

open-mmlab · Dec 9, 2022 · c7fcf5a · c7fcf5a
1 parent 918d1ac
commit c7fcf5a
Showing 1 changed file with 3 additions and 3 deletions.
diff --git a/configs/recognition/timesformer/README.md b/configs/recognition/timesformer/README.md
@@ -22,9 +22,9 @@ We present a convolution-free approach to video classification built exclusively
 
 | frame sampling strategy | resolution | gpus |        backbone         |   pretrain   | top1 acc | top5 acc | testing protocol | FLOPs | params |             config             |             ckpt             |             log             |
 | :---------------------: | :--------: | :--: | :---------------------: | :----------: | :------: | :------: | :--------------: | :---: | :----: | :----------------------------: | :--------------------------: | :-------------------------: |
-|         8x32x1          |  224x224   |  8   |   TimeSformer (divST)   | ImageNet-21K |  77.69   |  93.45   | 1 clips x 3 crop | 196G  |  122M  | [config](/configs/recognition/timesformer/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb.py) | [ckpt](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb_20220815-a4d0d01f.pth) | [log](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb.log) |
-|         8x32x1          |  224x224   |  8   |  TimeSformer (jointST)  | ImageNet-21K |  76.95   |  93.28   | 1 clips x 3 crop | 180G  | 86.11M | [config](/configs/recognition/timesformer/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb.py) | [ckpt](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb_20220815-8022d1c0.pth) | [log](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb.log) |
-|         8x32x1          |  224x224   |  8   | TimeSformer (spaceOnly) | ImageNet-21K |  76.93   |  92.88   | 1 clips x 3 crop | 141G  | 86.11M | [config](/configs/recognition/timesformer/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb.py) | [ckpt](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb_20220815-78f05367.pth) | [log](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb.log) |
+|         8x32x1          |  224x224   |  8   |   TimeSformer (divST)   | ImageNet-21K |  77.69   |  93.45   | 1 clip x 3 crop  | 196G  |  122M  | [config](/configs/recognition/timesformer/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb.py) | [ckpt](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb_20220815-a4d0d01f.pth) | [log](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_divST_8xb8-8x32x1-15e_kinetics400-rgb.log) |
+|         8x32x1          |  224x224   |  8   |  TimeSformer (jointST)  | ImageNet-21K |  76.95   |  93.28   | 1 clip x 3 crop  | 180G  | 86.11M | [config](/configs/recognition/timesformer/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb.py) | [ckpt](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb_20220815-8022d1c0.pth) | [log](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_jointST_8xb8-8x32x1-15e_kinetics400-rgb.log) |
+|         8x32x1          |  224x224   |  8   | TimeSformer (spaceOnly) | ImageNet-21K |  76.93   |  92.88   | 1 clip x 3 crop  | 141G  | 86.11M | [config](/configs/recognition/timesformer/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb.py) | [ckpt](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb_20220815-78f05367.pth) | [log](https://download.openmmlab.com/mmaction/v1.0/recognition/timesformer/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb/timesformer_spaceOnly_8xb8-8x32x1-15e_kinetics400-rgb.log) |
 
 1. The **gpus** indicates the number of gpus we used to get the checkpoint. If you want to use a different number of gpus or videos per gpu, the best way is to set `--auto-scale-lr` when calling `tools/train.py`, this parameter will auto-scale the learning rate according to the actual batch size and the original batch size.
 2. We keep the test setting with the [original repo](https://github.com/facebookresearch/TimeSformer) (three crop x 1 clip).