VFig

VFig is an open vision-language workflow for converting flat figure images into SVG instead of leaving you with a screenshot you have to redraw by hand. That matters when you want to clean up a slide, reuse a chart in a report, or pull one diagram out of a paper without rebuilding every label and shape yourself. A good first example is a flowchart or annotated chart from an internal deck. You upload the image, let the model produce SVG, then open the output in a vector editor and see how much of the structure survived cleanly enough to reuse.

Start with the AllenAI Hugging Face Space and use one diagram that has obvious structure, such as a flowchart, bar chart, or labeled scientific figure. On the first run, look for three things: whether the layout stays intact, whether text placement is still usable, and whether the result is editable enough to fix quickly instead of recreating it from scratch. If the demo is promising, the backing model card shows a direct local `transformers` workflow, but you should treat that as a real GPU path rather than a casual laptop test.

Complex figures can still need cleanup after generation, especially when they mix dense annotations, small text, or crowded layouts. The real value is reducing redraw work, not assuming every SVG comes out production-ready.

• Convert charts and diagrams from slides into editable vector assets.
• Reuse figures from reports or papers without manually redrawing every element.
• Clean up rough exported diagrams before dropping them into docs or presentations.
• Test whether image-to-SVG conversion is good enough for your internal design workflow.

Try the demo

View model page