Overview
Stencil-AI explores two different ways to generate print-ready stencils:
- text-to-image generation using Stable Diffusion and fine-tuned sketch-style checkpoints
- deterministic image conversion using classical computer vision
Design
The most interesting part of the repo is that it does not force a single method. It explicitly compares:
- AI generation for open-ended prompt-driven output
- CV pipelines for fast deterministic conversion of existing images
- a hybrid workflow where AI generates and CV refines
Research / Product Angle
The repo also documents the difference between standard Stable Diffusion prompt engineering and fine-tuned checkpoints trained on sketch-style data. That makes it stronger than a simple demo because it compares model behavior instead of only showcasing generated outputs.
Why It Matters
Stencil-AI sits in a useful middle ground between creative tooling and technical experimentation. It demonstrates model selection, fine-tuning tradeoffs, and workflow design rather than just single-image generation.