stylegan2-pytorch
Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch (by rosinality)
anycost-gan
[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing (by mit-han-lab)
stylegan2-pytorch | anycost-gan | |
---|---|---|
3 | 1 | |
2,665 | 769 | |
- | 0.3% | |
0.0 | 2.5 | |
6 months ago | 7 months ago | |
Python | Python | |
MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
stylegan2-pytorch
Posts with mentions or reviews of stylegan2-pytorch.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-10-04.
- Converting a .pkl file to a .pt for StyleGan2 Model
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I'm stumped with installing PyTorch.
Originally I wanted to run https://github.com/JCBrouwer/maua-stylegan2. I was trying to run the convert_weight.py but it resulted in shape mismatch errors in torch torch.Size([1, 512, 4, 4]) vs torch.Size([1]), so I tried the version here https://github.com/rosinality/stylegan2-pytorch/blob/master/convert_weight.py and the result was the same.
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[D] Node Collapse with StyleGAN2 - ada
Used this implementation (https://github.com/rosinality/stylegan2-pytorch) to better understand the code. IMO it is written way more clearly than the official implementation. You should spend a lot of time reviewing the code until you understand what each line is doing. It isn't helpful that their aren't very many comments, but you should be able to recognize different architectures and calculations from the paper. Understanding the details is key. Don't let your eyes glaze over any part of it.
anycost-gan
Posts with mentions or reviews of anycost-gan.
We have used some of these posts to build our list of alternatives
and similar projects.
What are some alternatives?
When comparing stylegan2-pytorch and anycost-gan you can also consider the following projects:
PaddleGAN - PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.
lightweight-gan - Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two