This repository provides a complete training and inference pipeline for an image-to-painting translation method. The approach generates vivid and realistic painting artworks by predicting a sequence of physically meaningful stroke parameters. It uses a differentiable neural renderer that imitates vector rendering, framing stroke prediction as a parameter-search process that maximizes similarity between input and rendered output. The method can be jointly optimized with neural style transfer to transfer visual style from reference images.