CosFace_pytorch
CosFace_pytorch copied to clipboard
If trained with MS-Celeb-1M or VggFace2 dataset ,how much can the test result be improved?
I don't know because I have never done such an experiment. You can try it with a simple modification.
I have trained on the msceleb cleaned by insightface, and have achieved 99.6~99.7 accuracy in LFW with resnet50.
I have trained on the msceleb cleaned by insightface, and have achieved 99.6~99.7 accuracy in LFW with resnet50.
Can you please share the model weights?
Can you also share the model on One Drive ?
I have trained on the msceleb cleaned by insightface, and have achieved 99.6~99.7 accuracy in LFW with resnet50. @gdshen i use the msceleb cleaned by insightface 、 LResnetE50-IR + cosFace ,but the entropy loss is 10.9 and didn't decline, 93%~94% accuracy in LFW , have u ever met this problem
Trained on VggFace2 with Sphere20. Achieved 99.55% on LFW. (Note: Input is 112X112)
-
Baidu Disk 链接: https://pan.baidu.com/s/16kWW4Gq6TdPRn2rA2ickkQ 提取码: pya3
-
Google Drive https://drive.google.com/file/d/19RAVxfvw15tavjpcktBBxFygxxTFM7Z1/view?usp=sharing
please MuggleWang when I test your model (net_sphere20_data_vggface2_acc_9955.pth), I obtained an error:
RuntimeError: Error(s) in loading state_dict for sphere: size mismatch for fc.weight: copying a param with shape torch.Size([512, 25088]) from checkpoint, the shape in current model is torch.Size([512, 21504]).
Thanks in advance
@HeshamMM Check your input size (112x112
), and accordingly the last fully connected layer in the model file layer.py
should be self.fc = nn.Linear(512 * 7 * 7, 512)
. And if input size is 112x96
, it should be self.fc = nn.Linear(512 * 7 * 6, 512)
. Further, in the inference(test) stage, match them with the model *.pth
.
Deeply thanks Dr. MuggleWang.