python train_encoder.py

[genforce]

python train_encoder.py

[ShenYujun]

When training the encoder, we do not need progressive training. So, you should only specify one file for the dataset (i.e., the one with the highest resolution) instead of a directory of datasets from all resolutions.

[leoffx]

It would be nice if this was added to the README. Also adding information about using the dataset_tool.py could be useful for people who never used StyleGAN before.

[ShenYujun]

Good suggestion! We will update the README soon. Thanks!

[bigorange-1]

Thanks for your great job. Recently, i am reading your code. However, i am struggling in a problem. Why not fix the discriminator “D” while training the encoder “E”？ Because, from what I understand, I found, that the generator “G” is fixed. But why, the subsequent discriminator “D” can be updated? Can you help me ?

[zhujiapeng]

Because the image output from the G is dynamically changing i.e., from the initial reconstruction to good reconstruction. Hence, the D needs to be updated.

[bigorange-1]

So, we can still see the training process of D and E as adversarial trainingg, is it right?

[zhujiapeng]

Yes.

[bigorange-1]

Thank you very much.

[bigorange-1]

Hello, I have another question. In perceptual_model.py，i saw that you used VGG16. However, i can't find any training about it. Don’t we need to fine-tune it when we use it? Will directly using the officially provided pre-trained weights have an impact on our results? Or maybe I'm wrong. Missing some key information in your code？Could you tell me? Thank you.