DragGAN
Discover DragGAN's point-based interaction for easy image editing on generative manifolds. Utilizing GAN capabilities, it provides flexible control and intuitive editing. With straightforward installation on CUDA devices and Apple Silicon, the project is accessible and compatible with Docker and pre-trained models. The GUI supports editing both GAN-generated and real images through GAN inversion. Compatible with PyTorch, it significantly advances image manipulation technology.
