Comments (3)
Hey @laolongboy,
Personally, I have tried 64 at most while the locality regularization is active. Of course you can invert even more identities if you want.
You can use PTI on those 2 identities together and receive only one StyleGAN. Which will incorporate both identities. To do so you need to use the MultiIDCoach by passing True to the use_multi_id_training variable in the run_pti script.
You should receive results as if you have used PTI on each of them separately, but with only one StyleGAN
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Thanks, I will try and update the results.
What's more, do we need to reseek the InterfaceGan's attrbute boundarys? or we can directly use the boundarys detected in the original stylegan space?
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The best part of the PTI process is that you can directly use the boundaries detected in the original StyleGAN space. Not only InterfaceGAN, but also GANSpace and StyleCLIP, and much more. The PTI process together with the regularization affects only the identity attribute in a very local environment.
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Related Issues (20)
- every image need 127M checkpoint
- The more smile, the more black HOT 5
- How did you find the directions? HOT 1
- Unexpected size of W features in generated_images = self.G.synthesis(w, noise_mode='const', force_fp32=True) HOT 2
- opt multi image one time? HOT 1
- The input parameters of the Generator HOT 1
- checkpoint HOT 3
- SG and SG2 issue HOT 2
- GPU error HOT 1
- Effect of lpips type HOT 1
- run_pit: assert target.shape == (G.img_channels, G.img_resolution, G.img_resolution) HOT 3
- [question] What kind of pre-processing would a model that doesn't generate faces require? HOT 1
- Custom Images - Run on full images HOT 3
- How can i get "car images " w_pivot?
- Applying PTI to other non style-GAN generators
- Failed to run 512x512 images
- How to improve the invert image to be more similar to the input image? HOT 1
- May I ask how the pt file for editing attributes was obtained?
- insetGan+PTI?
- Can I run it on Windows?
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