idinvert
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python train_encoder.py
When i am trying to training the encoder, I got the error as below:
tensorflow.python.framework.errors_impl.FailedPreconditionError: datasets/custom-dataset; Is a directory [[{{node IteratorGetNext}}]]
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.
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.
Good suggestion! We will update the README soon. Thanks!
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 ?
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.
So, we can still see the training process of D and E as adversarial trainingg, is it right?
Yes.
Thank you very much.
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.