DualGAN: unsupervised dual learning for image-to-image translation
please cite the paper, if the codes has been used for your research.
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Python (2.7 or later)
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numpy
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scipy
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NVIDIA GPU + CUDA 8.0 + CuDNN v5.1
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TensorFlow 1.0 or later
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unzip
- clone this repo:
git clone https://github.com/duxingren14/DualGAN.git
cd DualGAN
- download datasets (e.g., sketch-photo), run:
bash ./datasets/download_dataset.sh sketch-photo
- train the model:
python main.py --phase train --dataset_name sketch-photo --image_size 256 --epoch 45 --lambda_A 20.0 --lambda_B 20.0 --A_channels 1 --B_channels 1
- test the model:
python main.py --phase test --dataset_name sketch-photo --image_size 256 --epoch 45 --lambda_A 20.0 --lambda_B 20.0 --A_channels 1 --B_channels 1
Similarly, run experiments on facades dataset with the following commands:
bash ./datasets/download_dataset.sh facades
python main.py --phase train --dataset_name facades --image_size 256 --epoch 45 --lambda_A 20.0 --lambda_B 20.0 --A_channels 3 --B_channels 3
python main.py --phase test --dataset_name facades --image_size 256 --epoch 45 --lambda_A 20.0 --lambda_B 20.0 --A_channels 3 --B_channels 3
some datasets can also be downloaded manually from the website. Please cite their papers if you use the data.
facades: http://cmp.felk.cvut.cz/~tylecr1/facade/
sketch: http://mmlab.ie.cuhk.edu.hk/archive/cufsf/
maps: http://www.cs.mun.ca/~yz7241/dataset/maps.zip
oil-chinese: http://www.cs.mun.ca/~yz7241/, jump to http://www.cs.mun.ca/~yz7241/dataset/
day-night: http://www.cs.mun.ca/~yz7241/dataset/
Codes are built on the top of pix2pix-tensorflow and DCGAN-tensorflow. Thanks for their precedent contributions!
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