DiscoGAN
Official PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks.
Prerequisites
- Python 2.7
- PyTorch
- Numpy/Scipy/Pandas
- Progressbar
- OpenCV
Training DiscoGAN
CelebA
Download CelebA dataset using
$ python ./datasets/download.py celebA
(Currently, the link for downloading CelebA dataset is not available).
To train gender conversion,
$ python ./discogan/image_translation.py --task_name='celebA' --style_A='Male'
To train hair color conversion
$ python ./discogan/image_translation.py --task_name='celebA' --style_A='Blond_Hair' --style_B='Black_Hair' --constraint='Male'
Handbags / Shoes
Download Edges2Handbags dataset using
$ python ./datasets/download.py edges2handbags
Download Edges2Shoes dataset using
$ python ./datasets/download.py edges2shoes
To train Edges2Handbags,
$ python ./discogan/image_translation.py --task_name='edges2handbags'
To train Edges2Shoes,
$ python ./discogan/image_translation.py --task_name='edges2shoes'
To train Handbags2Shoes,
$ python ./discogan/image_translation.py --task_name='Handbags2Shoes' --starting_rate=0.5
Facescrub
Download Facescrub dataset using
$ python ./datasets/download.py facescrub
To train gender conversion,
$ python ./discogan/image_translation.py --task_name='facescrub'
Car, Face
Download 3D car dataset used in Deep Visual Analogy-Making, and 3D face dataset into ./datasets folder and extract them.
To train Car2Car translation,
$ python ./discogan/angle_pairing.py --task_name='car2car'
To train Car2Face translation,
$ python ./discogan/angle_pairing.py --task_name='car2face'
Run script.sh in order to train a model using other datasaet, after uncommenting corresponding line.
Results
All example results show x_A, x_AB, x_ABA and x_B, x_BA, x_BAB
Example results of hair color conversion
Example results of gender conversion (CelebA)
Example results of Edges2Handbags
Example results of Handbags2Shoes
Example results of gender conversion (Facescrub)
Example results of Car2Face
