Comments (8)
Karras implemented projecting to latent space right there in the original repo yo. Don't think it can be improved any more. He's using tiled (1, 512) dlatent though, I suppose as a preemptive measure against censorship activists. Made a couple of changes to project to (18, 512) space: https://github.com/oneiroid/stylegan2
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In the meantime, I've done two things: ported this repo to StyleGAN2 (link), at least up to the point where the tutorial notebook runs; and, in my own port of Puzer's encoder (link), added a project_images.py
equivalent to encode_images.py
.
My impression is that there is a lot of cool stuff in here that would be great to have in StyleGAN2. On the other hand, from a "user" - as opposed to "researcher" - perspective, a two-line change to the projector, plus a bit of glue around it, seems kind of hard to beat.
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@ofirkris I've thought about this - this would be better done as a fork of StyleGAN2. Anyone would be welcome to do this in a new repo, currently I'm taking a break from active development over the holidays.
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Karras implemented projecting to latent space right there in the original repo yo. Don't think it can be improved any more. He's using tiled (1, 512) dlatent though, I suppose as a preemptive measure against censorship activists. Made a couple of changes to project to (18, 512) space: https://github.com/oneiroid/stylegan2
@oneiroid: Uh, you're totally right!
Optimization video: https://youtu.be/DqOXWb1fvHk
This looks pretty good to me!
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Hi @woctezuma, I positively wouldn't mind explaining :))
Using (1, 512) dlatents you will never get good projection for any face that was not present in the training dataset.
Using (18, 512) dlats you can project any face. And then you can apply facial attributes directions - emotions, age, gender.
Even celebrity faces! And them celebrities got their faces copyrighted and sold for good money.
So there could've been deepfakes-style hysteria and calls to forbid everything starting from GANs down to internet and propagation of light reflected off their precioussssssss privately owned faces.
Karras and Nvidia do not need such sick activity around them. I hope I made myself clear. I'm a bit distressed recently by all the sick things happening, tried my best :)
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@oneiroid Did you run python align_images.py
before python encode_images.py
?
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Karras implemented projecting to latent space right there in the original repo yo. Don't think it can be improved any more. He's using tiled (1, 512) dlatent though, I suppose as a preemptive measure against censorship activists. Made a couple of changes to project to (18, 512) space: https://github.com/oneiroid/stylegan2
Hello @oneiroid, would you mind explaining what you meant as "preemptive measure against censorship activists"? I am trying to understand this (18, 512) change (rolux/stylegan2encoder#21), and so far, my understanding is that the visual fidelity is better but the semantic fidelity (for interpolation, etc.) is not. I assume that is the reason why Nvidia's implementation uses (1, 512). I would be curious about your other explanation.
Edit: I have found these related issues (#1, #2), including one created by you.
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Thank you for clarifying. It helps me in my understanding of this change!
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Related Issues (20)
- Error running encode_images.py on Colab HOT 2
- Error while running encode_images.py #41
- google drive exceeded encode_images.py
- Two bugs found HOT 2
- AttributeError: module 'tensorflow' has no attribute 'Dimension' HOT 2
- Face Alignment results in exception error
- Compatibility with pretrained stylegan2 model? HOT 7
- train encoder directly HOT 1
- requirements.txt empty and compatibility issues HOT 1
- assert img.shape == self.shape Assertion Error HOT 6
- How to interpolate a one region of two faces? HOT 1
- Why can't we find the vector Z and have to use W ? HOT 2
- runing StyleGAN_Encoder sehape error HOT 2
- Weird error, how do I fix it???'
- Why requirments.txt is empty HOT 1
- Getting error while run the 'encode_images.py' file
- 'latent_training_data' is no longer available HOT 1
- PreTrained Model HOT 1
- tf compatibility issue
- _pickle.UnpicklingError: invalid load key, '<'. HOT 2
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