DragGAN
Interactive point-based image manipulation using generative adversarial networks.
About DragGAN
DragGAN is an unofficial open-source implementation of the 'Drag Your GAN' technique, enabling users to manipulate generated or real images by dragging control points directly on the image canvas.
It provides a Gradio-based web interface for interactive use and supports local deployment across Windows, macOS, and Linux. The implementation includes all necessary code and pre-trained models, with instructions for both Colab (GPU-recommended) and local execution.
The tool targets researchers and developers interested in intuitive, geometry-aware editing of GAN-generated content — not end-user photo editing software, but a functional, accessible prototype of the original DragGAN method.
Key Features
- Interactive point-based image manipulation via drag-and-drop control points
- Gradio-based web interface for browser-based interaction
- Support for custom image upload and editing
- Local deployment support on Windows, macOS, and Linux
- Colab-ready setup with GPU runtime instructions
- Open-source code and pre-trained models included
- Compatible with pip installation (e.g., draggan==1.1.0)
Pros & Cons
Pros
- • Fully open and free to use with no paywall or usage limits
- • Cross-platform and accessible via Colab for zero-setup experimentation
- • Enables hands-on exploration of GAN manifold manipulation for students and researchers
Cons
- • Requires technical familiarity to run locally (Python, dependencies, GPU setup)
- • No official GUI installer or polished desktop application — relies on Gradio or CLI
- • No documentation on model licensing or training data provenance