Typical GANs are implemented as Tensorflow 2.
I followed the suggestions in the papers, and I slightly changed the model structure or optimizer for simple task.
Tensorflow 2.0
Tensorflow Datasets
Tensorflow-addons
cd GAN_DIR_YOU_WANT
python train.py
Name | Description |
---|---|
utils.py | Loss function, Image storage function, etc. |
model.py | Model Architecture |
train.py | Model learning and Loading datasets |
- GAN
- CGAN
- DCGAN
- LSGAN
- WGAN
- WGAN-GP
- CycleGAN
- StarGAN
- SRGAN
- SAGAN
- ACGAN
- infoGAN
- BEGAN
- BigGAN
- Stacked GAN
- EBGAN