This is the code repository complementing the paper attribute-guided image generation from layout. The pretrained model can be downloaded here: (TODO)
- Python 3.6.8
- SPADE
- numpy==1.16.3
- torch==1.1.0
- torchvision==0.3.0
- PIL==6.0.0
- imageio==2.5.0
- tensorboardX==1.8
- sklearn==0.20.3
- h5py==2.8.0
Visual Genome (VG) Download:
cd data/Dataset/vg
chmod +x download_vg.sh
./download_vg.sh
Preprocessing:
cd data/Dataset/vg
python train_test_split.py # split the dataset
cd ../..
python preprocess_vg.py
To train 64x64 (or 128x128) from scratch, run
python train64.py
The script will check if pretrained models exist.
Training 128x128 model is computationally expensive. You might consider using torch.DataParallel
for training with a larger batch size.
To test 64x64 (or 128x128) model, run
python test64.py
You can modify attributes as you wish in the test64.py (test128.py) script.