Eyyub / Tensorflow Cyclegan
Lightweight CycleGAN tensorflow implementation π¦ <-> π
Stars: β 35
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python
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tensorflow-cyclegan
A lightweight CycleGAN tensorflow implementation.
If you plan to use a CycleGAN model for real-world purposes, you should use the Torch CycleGAN implementation.
Some examples
lion2leopard (cherry-picked)
More lion2leopard (each classes contain only 100 instances!)
horse2zebra
horse2zebra failure
zebra2horse
wtf
More zebra2horse
apple2orange
See more in readme_imgs/
Build horse2zebra
- Download
horse2zebra.zipfrom CycleGAN datasets - Unzip it here
. - Run
python build_dataset.py horse2zebra/trainA horse2zebra/trainB trainA trainB - (make sure
dataset_trainA.npy&dataset_trainB.npyare created) - Then, run
python example.py - (If you want to stop and restart your training later you can do:
python example.py restore <last_iter_number>)
Requiremennts
- Python 3.5
- Tensorflow
- Matplotlib
- Pillow
- (Only tested on Windows so far)
Very useful info
- Training took me ~1day (GTX 1060 3g)
- Each 100 steps the script adds an image in the
images/folder - Each 1000 steps the model is saved in
models - CycleGAN seems to be init-sensitive, if the generators only inverse colors: kill & re-try training
Todo
- [x] Image Pool
- [ ] Add learning reate linear decay
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