Install

python

!git clone https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix

python

import os
os.chdir('pytorch-CycleGAN-and-pix2pix/')

python

!pip install -r requirements.txt

Datasets

Download one of the official datasets with:

bash ./datasets/download_pix2pix_dataset.sh [cityscapes, night2day, edges2handbags, edges2shoes, facades, maps]

Or use your own dataset by creating the appropriate folders and adding in the images. Follow the instructions here.

python

!bash ./datasets/download_pix2pix_dataset.sh facades

Pretrained models

Download one of the official pretrained models with:

bash ./scripts/download_pix2pix_model.sh [edges2shoes, sat2map, map2sat, facades_label2photo, and day2night]

Or add your own pretrained model to ./checkpoints/{NAME}_pretrained/latest_net_G.pt

python

!bash ./scripts/download_pix2pix_model.sh facades_label2photo

Training

python train.py --dataroot ./datasets/facades --name facades_pix2pix --model pix2pix --direction BtoA

Change the --dataroot and --name to your own dataset's path and model's name. Use --gpu_ids 0,1,.. to train on multiple GPUs and --batch_size to change the batch size. Add --direction BtoA if you want to train a model to transfrom from class B to A.

python

!python train.py --dataroot ./datasets/facades --name facades_pix2pix --model pix2pix --direction BtoA --display_id -1

Testing

python test.py --dataroot ./datasets/facades --direction BtoA --model pix2pix --name facades_pix2pix

Change the --dataroot, --name, and --direction to be consistent with your trained model's configuration and how you want to transform images.

from https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix: Note that we specified --direction BtoA as Facades dataset's A to B direction is photos to labels.

If you would like to apply a pre-trained model to a collection of input images (rather than image pairs), please use --model test option. See ./scripts/test_single.sh for how to apply a model to Facade label maps (stored in the directory facades/testB).

See a list of currently available models at ./scripts/download_pix2pix_model.sh

python

!ls checkpoints/

python

!python test.py --dataroot ./datasets/facades --direction BtoA --model pix2pix --name facades_label2photo_pretrained --use_wandb

Visualize

python

import matplotlib.pyplot as plt

img = plt.imread('./results/facades_label2photo_pretrained/test_latest/images/100_fake_B.png')
plt.imshow(img)

python

img = plt.imread('./results/facades_label2photo_pretrained/test_latest/images/100_real_A.png')
plt.imshow(img)

python

img = plt.imread('./results/facades_label2photo_pretrained/test_latest/images/100_real_B.png')
plt.imshow(img)