Home

Awesome

RelGAN (ICCV 2019)

imgA

(Official) Keras implementation of RelGAN: Multi-Domain Image-to-Image Translation via Relative Attributes

The paper is accepted to ICCV 2019. We also have the PyTorch version here.

imgB

Preparation

Get Started

Preprocessing

In this step, we export annotations to a numpy file. You will get anno_dic.npy and imgIndex.npy after running the script

-n  :   number of attributes (5, 9, 17)
-o  :   target output file
python3 preprocessing.py [--number=17] [--output=anno_dic.npy]

Training

python3 train.py
    --path=<path to celeba-256>
    --device=<device number>
    [--growth=False]
    [--step=0]
    [--lr=1e-5]
    [--beta1=0.5]
    [--beta2=0.999]
    [--batch_size=4]
    [--sample_size=2]
    [--epochs=400000]
    [--lambda1=10]
    [--lambda2=10]
    [--lambda4=10]
    [--lambda5=10]
    [--lambda_gp=150]
    [--img_size=256]
    [--vec_size=17]     #if you change the number of attributes, change this number

Testing

python3 demo_translation.py --device=<device number>
python3 demo_interpolation.py --device=<device number>