M
About
Purlwise Labs brings artificial intelligence to the world of fiber arts, starting with one of the most common frustrations for knitters: losing count of stitches. Developed by a team that is equal parts knitting enthusiasts and machine learning researchers, the tool uses computer vision trained on over 1,700 work-in-progress photos contributed by volunteer knitters to recognize and count stitches directly from images of needles. The current focus is automated stitch counting, but the team's broader roadmap is ambitious. Planned features include row counting, real-time knitting error identification, crochet stitch counting, pattern progress tracking, personalized pattern and yarn recommendations, and beginner-friendly assistance tools. The goal is to build a suite of AI-powered digital assistants that handle the repetitive, error-prone tasks of crafting — lowering barriers for crafters with manual or visual challenges and making the overall experience more enjoyable. Purlwise Labs is in active development with a web-based demo available to try. It is particularly well-suited for hobbyist and serious knitters, crocheters, and fiber arts enthusiasts who want technology to complement their craft without replacing the hands-on joy of making. The project also highlights the growing intersection of niche creative communities and practical machine learning applications.
Key Features
- Automatic Stitch Counting: Uses computer vision to count stitches on knitting needles from a photo, eliminating the need for manual counting.
- Community-Trained AI Model: The underlying model was trained on over 1,700 work-in-progress knitting photos contributed by volunteer crafters, making it highly relevant to real-world knitting scenarios.
- Planned Error Identification: Future updates aim to detect common knitting mistakes in real time, helping crafters catch errors before they become hard to fix.
- Pattern & Yarn Recommendations: Upcoming features will offer personalized pattern and yarn suggestions based on a crafter's skill level and project history.
- Accessibility-Focused Design: Designed to lower barriers for crafters with manual or visual challenges by automating repetitive and precision-dependent tasks.
Use Cases
- A knitter working on a complex lace pattern uses Purlwise Labs to verify their stitch count after each row without interrupting their flow.
- A crafter with low vision uses the AI stitch counter to compensate for difficulty visually tracking stitches on the needle.
- A beginner knitter uses the tool to check that they haven't accidentally increased or decreased stitches while learning a new technique.
- An experienced knitter uses the planned error detection feature to catch dropped stitches or accidental yarn-overs early in a project.
- A yarn shop owner recommends Purlwise Labs to customers as a digital companion tool to pair with patterns and yarn purchases.
Pros
- Solves a Real Crafting Pain Point: Stitch counting is one of the most common and frustrating tasks for knitters — automating it addresses a genuine, everyday need.
- Built by Domain Experts: The team combines actual knitting expertise with machine learning research, resulting in a tool that understands the craft context, not just the technology.
- Broad Roadmap: Plans for row counting, error detection, crochet support, and pattern tracking suggest a platform with long-term value for the fiber arts community.
Cons
- Still in Early Development: The full app is not yet launched, and most advanced features (row counting, error detection, pattern tracking) are not yet available.
- Very Niche Use Case: The tool is specifically tailored to knitting and fiber arts, limiting its appeal outside that community.
Frequently Asked Questions
What does Purlwise Labs do?
Purlwise Labs uses artificial intelligence and computer vision to automatically count stitches on knitting needles from a photo, saving knitters from losing their place during a project.
Is Purlwise Labs free to use?
Yes, there is a free 'Try it!' demo available on the website. The team is also collecting emails to notify users when the full app launches.
How was the AI model trained?
The model was trained on over 1,700 work-in-progress (WIP) knitting photos contributed by volunteer knitters from the crafting community.
Does it work for crochet as well as knitting?
Crochet stitch counting is on the roadmap but is not yet available. The current focus is on counting stitches on knitting needles.
What features are planned for the future?
The team is working on row counting, knitting error identification, crochet counting, pattern progress tracking, yarn and pattern recommendations, and beginner assistance tools.
