Comments (1)
Please see the #4. The number of training iteration in one epoch is very large, you can modify dataset or save checkpoint more often.
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Related Issues (20)
- how many images are necessary to have good results? HOT 1
- Which dataset do you use to train your own arcface? HOT 1
- GPU Memory HOT 2
- Training with only CelebHQ dataset HOT 7
- Coefficients of loss HOT 3
- some error with aei_inference.py HOT 3
- multi GPU training HOT 1
- Colab Example-FaceShifter.pth HOT 4
- Should affine be set as False in your ADD layers? HOT 1
- The implementation of ID Loss seems different from the original paper HOT 2
- Have you ever encountered this phenomenon: attr loss down to near 0 and rec loss keeps at 0.01 and doesn't got down? HOT 2
- A question about train step HOT 1
- TypeError: __init__() got an unexpected keyword argument 'early_step_callback' HOT 1
- Can anyone share a pretrained model?
- Can you provide the pre-trained arcface.pth? HOT 2
- The link of pre-trained Arcface model is expired
- DeepFace HOT 1
- identity encoder code not found HOT 7
- where is val set
- CUDA out of memory. HOT 4
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