The code is based on the style-transfer-pytorch, supporting masked image style transfer.

We also deployed the Optimal Transport Loss, and a masked seamless clone-style transfer method.

Also, support using a user word prompt to mask the given image automatically.

Detailed results can be found here:exp/results.ipynb

The main changes happened here: style_transfer/style_transfer.py

*To enable the mask mode and switch to a different loss function, please follow the comments in the codes.

Detailed results can be found here: SAM _generate_mask/predictor_example.ipynb

User Prompt - "sheep"

User Prompt - "bear"

User Prompt - "chair"

• Style Transfer with Optimal Transport Loss

• Masked Style Transfer and Mask Strategies

• Naive Masekd Style Transfer and Mask Strategies

• MSE-Style Loss, Wasserstein-2 Loss, and Optimal Transport Loss