Comments (3)
Sorry, I made a mistake in the code when printing the progress information
Line 192 in 7a1c560
The information should be printed as
f"[{ii:03d}/{len(files):03d}]"
rather than the original
f"[{ii * args.batch:03d}/{len(files):03d}]"
So your progress at [448/283] should be [112/283]
I think your Simpsons style is too abstract and different from real human faces, and it is not well aligned (the eye positions of your two style images differ a lot from each other and from the FFHQ faces).
These two points make the destylization fail.
Our method is to simulate the fine-tuning behavior of StyleGAN, and style transfer by fine-tuning StyleGAN relies on the close semantic correspondences between the source domain and the target domain, which is true for real faces and cartoon faces. However, in your case, the domain gap is so large that I'm afraid even fine-tuning StyleGAN cannot work, let alone our method.
I think you can check the performance of your finetune StyleGAN on your Simpsons styles and see whether it works. If it does not work, I guess our method might not be able to make it, either.
from dualstylegan.
Heads up, this piece of code was never fixed. So anyone wondering around December 2022 you need to change the code manually.
from dualstylegan.
this code printing the progress info has been fixed
from dualstylegan.
Related Issues (20)
- Why " W+ " encoder giving fully different style transformation ? HOT 23
- How to use this code in mac OS and building in IOS Device ? HOT 1
- 卡通化的人物可以保留人物的真实感吗? HOT 1
- Why dose the destylization process work? HOT 3
- 灌篮高手风格模型 HOT 1
- """Add --wplus in style_transfer.py to use original w+ pSp encoder rather than z+.""" integrate in demo of Hf spaces HOT 3
- Toon images HOT 2
- integrate stable diffusion pretrained models
- How is this picture drawn? HOT 1
- Memory issue while toonifying the image using "VToonify" but not while style transfering the image using "DualStyleGAN" why ?
- AttributeError: module 'model.stylegan' has no attribute 'lpips' HOT 1
- RuntimeError: mat1 dim 1 must match mat2 dim 0 HOT 1
- RuntimeError: input must be contiguous HOT 2
- pre-train ConditionalDiscriminator HOT 1
- 生成图片的脖子有痕迹 HOT 1
- Error occured when pretraining dualstylegan HOT 2
- Train with w-plus pSp encoder. HOT 2
- the gpu memory usage of finetuning dualstylegan on 8 gpus HOT 2
- Apart from Human images
- Freeze/crash in web demo on reconstruct_face()
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from dualstylegan.