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Save training images to folder
training-data
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Run training script
python train.py --epochs=100 --batch-size=32 \
--sample-interval=50 --load-saved=True --method=wgangp
The code wgan and wgangp are taken and modified from Keras-GAN.
Why not fork?
It's a great repo to fork and start with, but there are too many GAN implementations that we are not going to use. So we copied the code we need and modified them for our training sets.utils is taken and modified from Pokemon_GAM.