ximinng/PyTorch-SVGRender
A PyTorch library for generating SVG vector graphics using diffusion models and score distillation sampling with differentiable rendering.
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PyTorch-SVGRender provides differentiable rendering methods for SVG generation using neural networks. It supports text-to-SVG and image-to-SVG conversion through techniques including score distillation sampling (SDS) and diffusion models. The library integrates differentiable vector graphics rasterization (DiffVG) and enables editing and synthesis of vector sketches and graphics.
Frequently asked
- What is ximinng/PyTorch-SVGRender?
- A PyTorch library for generating SVG vector graphics using diffusion models and score distillation sampling with differentiable rendering.
- Is PyTorch-SVGRender open source?
- Yes — ximinng/PyTorch-SVGRender is open source, released under the MPL-2.0 license.
- What language is PyTorch-SVGRender written in?
- ximinng/PyTorch-SVGRender is primarily written in Python.
- How popular is PyTorch-SVGRender?
- ximinng/PyTorch-SVGRender has 491 stars on GitHub.
- Where can I find PyTorch-SVGRender?
- ximinng/PyTorch-SVGRender is on GitHub at https://github.com/ximinng/PyTorch-SVGRender.