Repository for CLIP-supervised GAN-based Image Editing.
cliplsd.py contrains all training code for the project.
The notebooks folder contains all experiment notebooks.
A streamlit app is provided to view the trained directions depending on the chosen parameters.
streamlit run 1D_visualization.py
Using this app you can view the edits made by the directions found by the model.
For more information check out the report pdf.
This project builds on top of Optimizing Latent Space Directions For GAN-based Local Image Editing