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Automating the production of generative images via scripts and predefined constraints without a UI.
Distinct from Image Generation: Focuses on head-less, scripted production based on constraints, unlike the general UI-driven image generation parent.
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iGAN is a framework for producing synthetic images using generative adversarial networks. It provides a web-based interface for interactively creating and editing imagery across categories such as landscapes, architecture, and fashion using pre-trained models. The system enables precise control over visual output through latent space exploration, interpolation, and projection. Users can guide the generative process using an interactive editor featuring sketching, coloring, and warping brushes to refine specific regions or shapes in real-time. The project supports both automated scripted gene
Supports producing multiple images based on specific color and edge maps through automated scripts.