PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks. (by eriklindernoren)
CoGAN
By mingyuliutw
PyTorch-GAN | CoGAN | |
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7 | 1 | |
15,732 | 284 | |
- | - | |
0.0 | 0.0 | |
4 days ago | over 6 years ago | |
Python | Jupyter Notebook | |
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.
PyTorch-GAN
Posts with mentions or reviews of PyTorch-GAN.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-07.
- How to run large GAN models on colab with Celeb dataset
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Cleansing Image for Cataloging(see description)
there are many image to image translation models you can choose from. A good starting point would be PyTorch-GAN. I guess you're able to pick one by experimenting yourself. Good luck in your interesting work, and report back once you're done.
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[P] Pythae: Unifying Generative AutoEncoders in Python - What's new ?
By the way, if you are interested in GANs, this repository may help you: https://github.com/eriklindernoren/PyTorch-GAN.
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Help learning GAN architecture
If you are familiar with pytorch, I highly recommand to take a look at https://github.com/eriklindernoren/PyTorch-GAN as they have papers and implementations
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[D] What is current SOTA in Image to Image Translation?
I also happen to know of a old (but it checks out) mass-port-to-pytorch github: https://github.com/eriklindernoren/PyTorch-GAN . That one is handy for more seeing what kind of models are out there, but they're probably not SOTA.
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[P] Voice Conversion VAE-Cycle-GAN on Melspectrograms
Hi just an update to whom ever faces a similar issue. I've fixed it.The key change was redefining the encoder loss - where kld is defined without logvar (only mu) and the reconstruction loss is defined with L1 rather than MSE. This was a helpful resource on the matter https://github.com/eriklindernoren/PyTorch-GAN/blob/master/implementations/unit/unit.py
- I created a GAN to generate Minecraft skins - http://perceptrons.tk:8501/
CoGAN
Posts with mentions or reviews of CoGAN.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-15.
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[P] Voice Conversion VAE-Cycle-GAN on Melspectrograms
You also set biases to false? At least in CoGAN there are biases. https://github.com/mingyuliutw/CoGAN/blob/master/cogan/models/celeba/celeba.train.ptt
What are some alternatives?
When comparing PyTorch-GAN and CoGAN you can also consider the following projects:
tt-vae-gan - Timbre transfer with variational autoencoding and cycle-consistent adversarial networks. Able to transfer the timbre of an audio source to that of another.
contrastive-unpaired-translation - Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)