Advanced Deep Learning with Keras

Chapter 7
Figure 7.1.10: Color (from Figure 7.1.9) to the grayscale conversion of CycleGAN
The reader can run the image translation by using the pretrained models for
CycleGAN with PatchGAN:
python3 cyclegan-7.1.1.py --cifar10_g_source=cyclegan_cifar10-g_source.h5
--cifar10_g_target=cyclegan_cifar10-g_target.h5
CycleGAN on MNIST and SVHN datasets
We're now going to tackle a more challenging problem. Suppose we use MNIST
digits in grayscale as our source data, and we want to borrow style from SVHN [1]
which is our target data. The sample data in each domain are shown in Figure 7.1.11.
We can reuse all the build and train functions for CycleGAN that were discussed in
the previous section to perform style transfer. The only difference is we have to add
routines for loading MNIST and SVHN data. SVHN dataset can be found at http://
ufldl.stanford.edu/housenumbers/.
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