Tensorflow (mainly Keras) implements of GANs with Jupyter Notebook.
Use simple Keras codes to help you get insights behind different GANs. The whole process would show on Jupyter Notebooks, which means that you don't have to actually run those codes to get output results or network architectures.
My env: tensorflow-gpu 2.0.0a0
- DCGAN (64*5*5 conv->128*5*5conv)
| name | usage |
|---|---|
| *.ipynb | implements of GANs |
| pretrained_model/* | checkpoint files |
| image/* | generator's output image |
Keras-GAN from eriklindernoren, although he used Keras api, the combine-train mode still seems tricky
the gan zoo
