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Update README.md
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anxiangsir committed Mar 19, 2021
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17 changes: 12 additions & 5 deletions recognition/arcface_torch/README.md
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Expand Up @@ -81,21 +81,28 @@ All Model Can be found in here.
### 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 |
| MS1MV3-Arcface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/ms1mv3_arcface_r18_fp16/training.log) | r18-fp16 | 92.07 | 94.66 | 97.77 | 97.73 | 99.77 |
| MS1MV3-Arcface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/ms1mv3_arcface_r34_fp16/training.log) | r34-fp16 | 94.10 | 95.90 | 98.10 | 98.67 | 99.80 |
| MS1MV3-Arcface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/ms1mv3_arcface_r50_fp16/training.log) | r50-fp16 | 94.79 | 96.46 | 98.35 | 98.96 | 99.83 |
| MS1MV3-Arcface |[log](https://raw.githubusercontent.com/anxiangsir/insightface_arcface_log/master/ms1mv3_arcface_r100_fp16/training.log) | r100-fp16 | 95.31 | 96.81 | 98.48 | 99.06 | 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 |
| Glint360k-Cosface | - | - | - | - | - | - | - |
| Glint360k-Cosface | - | - | - | - | - | - | - |
| Glint360k-Cosface | - | - | - | - | - | - | - |




More details see [eval.md](docs/modelzoo.md) in docs.


## Test
We test on PyTorch versions 1.6.0, 1.7.1, and 1.8.0. Please create an issue if you are having trouble.

## Citation
```
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2 changes: 1 addition & 1 deletion recognition/arcface_torch/backbones/__init__.py
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@@ -1 +1 @@
from .iresnet import iresnet18, iresnet34, iresnet50, iresnet100
from .iresnet import iresnet18, iresnet34, iresnet50, iresnet100, iresnet200
8 changes: 7 additions & 1 deletion recognition/arcface_torch/backbones/iresnet.py
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@@ -1,7 +1,7 @@
import torch
from torch import nn

__all__ = ['iresnet18', 'iresnet34', 'iresnet50', 'iresnet100']
__all__ = ['iresnet18', 'iresnet34', 'iresnet50', 'iresnet100', 'iresnet200']


def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
Expand Down Expand Up @@ -179,3 +179,9 @@ def iresnet50(pretrained=False, progress=True, **kwargs):
def iresnet100(pretrained=False, progress=True, **kwargs):
return _iresnet('iresnet100', IBasicBlock, [3, 13, 30, 3], pretrained,
progress, **kwargs)


def iresnet200(pretrained=False, progress=True, **kwargs):
return _iresnet('iresnet200', IBasicBlock, [6, 26, 60, 6], pretrained,
progress, **kwargs)

1 change: 0 additions & 1 deletion recognition/arcface_torch/train.py
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Expand Up @@ -97,7 +97,6 @@ def main(args):
global_step += 1
features = F.normalize(backbone(img))
x_grad, loss_v = module_partial_fc.forward_backward(label, features, opt_pfc)

if cfg.fp16:
features.backward(grad_scaler.scale(x_grad))
grad_scaler.unscale_(opt_backbone)
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