rich-text-to-image
This project investigates how rich text formatting can enhance control over text-to-image generation. Using attributes such as font size, color, and style improves token weighting and image accuracy. Recent updates include model integration, local style support, and precise color generation. The method leverages region-based diffusion and cross-attention mapping for intricate visual results, highlighted by a JSON input structure and various user interface deployment options, signifying advances in expression and precision.