Code for WACV 2024 paper SpectralCLIP: Preventing Artifacts in Text-Guided Style Transfer from a Spectral Perspective.
24 Oct 2023: SpectralCLIP is accepted by WACV 2024
03 Nov 2023: We release the code of SpectralCLIP
To use SpectralCLIP for style transfer, we implement the method based on CLIPstyler.
$ conda create -n SpectralCLIP python=3.6
$ conda install --yes -c pytorch pytorch=1.7.1 torchvision cudatoolkit=11.0
$ pip install ftfy regex tqdm
$ pip install git+https://github.com/openai/CLIP.git
$ pip install torch-dct
python train_SpectralCLIP.py --band c2 --text "Giorgio Morandi"
To change the filtering band combination, modify the --band argument.
Here are the filtering band combinations we found effective for different styles:
| Filter | Style |
|---|---|
| c1 | Lowbrow, Outsider art, Visionary art, Rosy-color oil painting |
| c2 | Pop art, Cartoon, Giorgio Morandi, Harlem Renaissance, Neon art, Contemporary art |
| c3 | Fauvism, Digital art |