chainer implementation of pix2pix https://phillipi.github.io/pix2pix/

The Japanese readme can be found here.

1. pip install -r requirements.txt
2. Download the facade dataset (base set) http://cmp.felk.cvut.cz/~tylecr1/facade/
3. python train_facade.py -g [GPU ID, e.g. 0] -i [dataset root directory] --out [output directory] --snapshot_interval 10000
4. Wait a few hours...

• --out stores snapshots of the model and example images at an interval defined by --snapshot_interval
• If the model size is large, you can reduce --snapshot_interval to save resources.

• Gather image pairs (e.g. label + photo). Several hundred pairs are required for good results.
• Create a copy of facade_dataset.py for your dataset. The function get_example should be written so that it returns the i-th image pair a tuple of numpy arrays i.e. (input, output).
• It maybe necessary to update the loss function in updater.py.
• Likewise, make a copy of facade_visualizer.py and modify to visualize the dataset.
• In train_facade.py change in_ch and out_ch to the correct input and output channels for your data.