1 dépôt
Awesome GitHub RepositoriesGenerative Model Debuggers
Tools for probing and visualizing the output space of generative models to identify capabilities and limitations.
Distinct from Generative Models: Candidates focus on data model generators or identity models, not diagnostic tools for analyzing generative model behavior.
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Awesome Generative Model Debuggers GitHub Repositories
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- junyanz/igan
junyanz/iGAN
4,007Voir sur GitHubiGAN 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
Provides a visualization tool for analyzing the capabilities and limitations of a generative model through iterative output testing.
Python
