Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

What is the project about?

The project introduces "Drag Your GAN," a method for interactively manipulating images generated by Generative Adversarial Networks (GANs). Users can "drag" points on an image to precisely control the pose, shape, expression, and layout of generated or real images.

What problem does it solve?

Existing GAN image editing methods often lack precise and flexible control over image features. DragGAN provides a user-friendly and interactive way to manipulate images at a pixel level, overcoming limitations of previous approaches that rely on coarse controls or pre-defined attributes. It allows for fine-grained control that was previously difficult or impossible to achieve.

What are the features of the project?

Interactive Point-based Manipulation: Users select handle points and target points on an image, and the system moves the handle points towards the targets.
Precise Control: Allows for fine-grained control over object pose, shape, expression, and layout.
Real and Generated Images: Works on both GAN-generated images and real images (after GAN inversion).
Motion Supervision: A new point tracking approach that leverages the GAN's features to keep track of handle points during manipulation.
Point Tracking: Leverages the GAN's features to keep track of handle points.
GUI: Provides a graphical user interface for easy interaction.
Gradio Demo: Offers a web-based demo for accessibility.
Docker Support: Containerized version for easy deployment.

What are the technologies used in the project?

PyTorch: The primary deep learning framework.
StyleGAN2/StyleGAN3: The underlying GAN architecture.
CUDA: (Optional) For GPU acceleration.
Gradio: For creating the web-based demo.
Docker: For containerization.
conda: For environment management.

What are the benefits of the project?

User-Friendly: The "dragging" interface is intuitive and easy to use.
Precise and Flexible: Offers a level of control not found in many other GAN editing tools.
Interactive: Provides real-time feedback during manipulation.
Versatile: Applicable to a wide range of image editing tasks.
Open Source: The code is available for research and non-commercial use.

What are the use cases of the project?

Image Editing: Modifying existing images (e.g., changing the pose of a person, the shape of an object, or the expression of a face).
Content Creation: Generating new images with specific characteristics.
Animation: Creating simple animations by sequentially dragging points.
Interactive Design: Prototyping and exploring different visual designs.
Research: A platform for further research in GAN-based image manipulation.