Comments (9)
@Voyz Yes, the code will be public for sure. For now, we still have some work in submission, but a more powerful GAN-related toolkit is coming soon!!
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@Voyz We may release the code in March. Thanks for your interest and patience.
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You can try to extract VGG features from a fixed input image using both stylegan-encoder
and your own pytorch
version to check whether these two tools give same output.
Also, does the loss descend normally during the optimization procedure?
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Original:
Learnt and generated with stylegan-encoder:
The loss does reduce but stabilizes early. The comparison above is with SGD optimizer and learning rate = 1. Other optimizers and lr give similar or worse results.
Maybe this has something to do with differences in optimizer implementations for pytorch and tensorflow/keras and this is just an issue of finding the right hyperparamters to train, but I have had no luck so far.
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The loss value from top and bottom figures are clearly different. Can you test whether VGG models from tensorflow/pytorch version give same response to same image? I suggest taking this test as the first step of debugging.
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We will support the inversion function in the future version soon. Close this issue for now.
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Hi @ShenYujun - is there any indication as to when the inversion function will be made public? We await it with anticipation!
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@ShenYujun That's absolutely wonderful news, thanks! Out of interest, would you be able to give an approximate release date?
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@ShenYujun Thank you, appreciate the reply. We truly admire your work, massive kudos for what you've achieved so far! Looking forward to seeing more!
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Related Issues (20)
- AttributeError: module 'tensorflow' has no attribute 'get_variable' HOT 2
- Access to training modules
- how do I test on my own set of images? Whenever I try testing it opens up sample images..Any help will be appreciated, HOT 2
- How can we generate the 256 resolution images for style GAN on celebahq instead of 1024?
- Can I use my own face for Semantic Face Editing HOT 1
- changing dataset HOT 4
- Integrate expression boundaries
- What is the rationale behind sampling from the normal distribution for the W latent code, which is not a normal distribution at all?
- Training with custom dataset HOT 3
- vgg16_zhang_perceptual.pkl _pickle.UnpicklingError: invalid load key, '-'.
- Pretrained Model on pggan
- how can i run an inference using CPU?
- how to get latent codes from jpg/png images? HOT 1
- question about the proof
- Can you provide me with ppgan_ celebahq.pth file as pre-training model HOT 1
- It can realize the attributes of other kinds of objects, not the search of face attributes, such as the conversion of landscape images into snow, rain, mountains, etc.
- Issue regarding method linear_interpolate in file utils/manipulator.py
- How to train a classifier to get attribute scores HOT 2
- does it provide the function of generating an eyeglass on my own face photo?
- About editing HOT 2
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