Awesome
VSAIT: Unpaired Image Translation via Vector Symbolic Architectures
Justin Theiss, Jay Leverett, Daeil Kim, Aayush Prakash<br> In ECCV 2022 (Oral).
Source GTA5 | GTA5 Translated with VSAIT |
---|---|
Installation
Clone this repo:
git clone https://github.com/facebookresearch/vsait.git
cd vsait/
Install dependencies via pip:
pip install -r requirements.txt
Dataset Preparation
For any two image datasets with png/jpg images, download source and target data (or create symlinks) to ./data/source/
and ./data/target/
with train
and val
subfolders for each domain.
For gta2cityscapes, GTA5 dataset images
folder should be split into training and validation folders to be stored in ./data/source/train/
and ./data/source/val/
, respectively. Similarly, the Cityscapes dataset folders /leftImg8bit/train/
and /leftImg8bit/val/
should be stored in ./data/target/train/
and ./data/target/val/
, respectively.
Training
Launch training with defaults in configs:
python train.py --name="vsait"
This will use the default configs in ./configs/
and save checkpoints and translated images in ./checkpoints/vsait/
.
Evaluation
Translate images in ./data/source/val/
using a specific checkpoint:
python test.py --name="vsait_adapt" --checkpoint="./checkpoints/vsait/version_0/checkpoints/epoch={i}-step={j}.ckpt"
Images from the above example would be saved in ./checkpoints/vsait_adapt/images/
.
License
VSAIT is released under the CC-BY-NC 4.0 License.