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Update pretrain model.
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1. Add training log and pretrain
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anxiangsir committed Mar 12, 2021
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55 changes: 23 additions & 32 deletions recognition/arcface_torch/README.md
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Expand Up @@ -9,6 +9,10 @@ torch >= 1.6.0
```

## Train on a single node
If you want to use 8 GPU to train, you should set `--nproc_per_node=8` and set `CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 `
If you want to use 4 GPU to train, you should set `--nproc_per_node=4` and set `CUDA_VISIBLE_DEVICES=0,1,2,3`
If you want to use 1 GPU to train, you should set `--nproc_per_node=1` ...

```shell
export OMP_NUM_THREADS=4
export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
Expand Down Expand Up @@ -42,39 +46,26 @@ CUDA_VISIBLE_DEVICES=0,1 python eval_ijbc.py \
More details see [eval.md](docs/eval.md) in docs.


## Model Zoo
### MS1MV3
| Datasets | backbone | IJBC(1e-05) | IJBC(1e-04) |agedb30|cfp_fp|lfw |
| :---: | :--- | :--- | :--- |:--- |:--- |:--- |
| MS1MV3-Arcface | r18 | 92.08 | 94.68 |97.65 |97.63 |99.73|
| MS1MV3-Arcface | r34 | | | | | |
| MS1MV3-Arcface | r50 | 94.79 | 96.43 |98.28 |98.89 |99.85|
| MS1MV3-Arcface | r50-amp | 94.72 | 96.41 |98.30 |99.06 |99.85|
| MS1MV3-Arcface | r100 | 95.22 | 96.87 |98.45 |99.19 |99.85|

### Glint360k
| Datasets | backbone | IJBC(1e-05) | IJBC(1e-04) |agedb30|cfp_fp|lfw |
| :---: | :--- | :--- | :--- |:--- |:--- |:--- |
| Glint360k-Cosface | r100 | 96.19 | 97.39 |98.52 |99.26 |99.83|
## Model Zoo

More details see [eval.md](docs/modelzoo.md) in docs.
The models are available for non-commercial research purposes only.

All Model Can be found in here.
[Baidu Yun Pan](https://pan.baidu.com/s/1CL-l4zWqsI1oDuEEYVhj-g): e8pw

### MS1MV3
| Datasets | log | backbone | IJBC(1e-05) | IJBC(1e-04) |agedb30|cfp_fp|lfw |
| :---: | :--- | :--- | :--- | :--- |:--- |:--- |:--- |
| MS1MV3-Arcface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/ms1mv3_arcface_r18/training.log) | r18 | 92.08 | 94.68 | 97.65 | 97.63 | 99.73 |
| MS1MV3-Arcface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/ms1mv3_arcface_r34/training.log) | r34 | 94.13 | 95.98 | 98.05 | 98.60 | 99.80 |
| MS1MV3-Arcface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/ms1mv3_arcface_r50/training.log) | r50 | 94.79 | 96.43 | 98.28 | 98.89 | 99.85 |
| MS1MV3-Arcface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/ms1mv3_arcface_r50_fp16/training.log) | r50-fp16 | 94.72 | 96.41 | 98.30 | 99.06 | 99.85 |
| MS1MV3-Arcface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/ms1mv3_arcface_r100/training.log) | r100 | 95.22 | 96.87 | 98.45 | 99.19 | 99.85 |

### Glint360k
| Datasets | log |backbone | IJBC(1e-05) | IJBC(1e-04) |agedb30|cfp_fp|lfw |
| :---: | :--- |:--- | :--- | :--- |:--- |:--- |:--- |
| Glint360k-Cosface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/glint360k_cosface_r100/training.log) |r100 | 96.19 | 97.39 | 98.52 | 99.26 | 99.83 |
| Glint360k-Cosface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/glint360k_cosface_r100_fp16_0.1/training.log)|r100-fp16-sample-0.1 | 95.95 | 97.35 | 98.57 | 99.30 | 99.85 |

## Citation
```
@inproceedings{deng2019arcface,
title={Arcface: Additive angular margin loss for deep face recognition},
author={Deng, Jiankang and Guo, Jia and Xue, Niannan and Zafeiriou, Stefanos},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
pages={4690--4699},
year={2019}
}
@inproceedings{an2020partical_fc,
title={Partial FC: Training 10 Million Identities on a Single Machine},
author={An, Xiang and Zhu, Xuhan and Xiao, Yang and Wu, Lan and Zhang, Ming and Gao, Yuan and Qin, Bin and
Zhang, Debing and Fu Ying},
booktitle={Arxiv 2010.05222},
year={2020}
}
```
More details see [eval.md](docs/modelzoo.md) in docs.
1 change: 0 additions & 1 deletion recognition/arcface_torch/backbones/iresnet.py
Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,6 @@ def conv1x1(in_planes, out_planes, stride=1):

class IBasicBlock(nn.Module):
expansion = 1

def __init__(self, inplanes, planes, stride=1, downsample=None,
groups=1, base_width=64, dilation=1):
super(IBasicBlock, self).__init__()
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