Style2paints is a deep learning image processor designed for the automated colorization of grayscale line art. It functions as a generative style transfer engine that maps artistic color palettes and textures onto monochrome sketches, allowing users to transform black and white drawings into finished illustrations through neural network inference.
The system distinguishes itself by incorporating user-provided color guidance and style references to influence the final output. It utilizes coordinate-mapped color points and hint-driven optimization to ensure that specific colors are applied precisely to intended regions, while multi-stage refinement processes improve edge alignment and color blending across the canvas.
To support ongoing creative workflows, the application includes text-based state serialization. This capability allows users to export and import their colorization hints and project progress as compact strings, enabling the preservation and sharing of specific coloring configurations between sessions.
