prompt-to-prompt
Discover innovative text-based image editing techniques using Latent and Stable Diffusion models that leverage prompt manipulation for greater creative control. This project features prompt replacement, refinement, and re-weighting methods, allowing modification of attention weights to create customized image outputs. Designed for researchers and developers, it offers detailed notebooks and code implementation, compatible with Pytorch 1.11 and Huggingface diffusers. Understand attention control mechanisms, primary prompt edits, and real image editing via null-text inversion, offering notable advancements in AI-generated imagery for precise and intuitive outcomes.
