The project uses synthetic data generation to train deep learning models for tattoo removal in images. It overlays APDrawing dataset pairs with tattoo designs to create training data, leveraging ControlNet for image-to-image translation. The pipeline processes portrait and full-body images, using Stable Diffusion as the underlying generative model to produce retouched output without tattoos.