Modeling Crochet Patterns with a Force-directed Graph Layout
Bibliographic record
Abstract
Designing crochet patterns is a difficult, time-consuming task. Typically, an initial pattern is created and crocheted; after seeing how the object comes out, the pattern is modified and some amount of stitches are undone and remade, through some number of iterations. This process involves a lot of guesswork and the manual labor of physically crocheting. In this paper, we present a way of creating a 3D representation of a crochet pattern using a written pattern as input: we translate the written pattern into a graph and obtain a force-directed graph layout. The result is a 3D model that looks like the hand-crocheted pattern in shape and size, with the advantage that the designer does not need to physically crochet the pattern and can make adjustments based on the digital model. Our intended audience includes both professional designers as well as beginners, helping designers visualize their crochet pattern before investing the time and effort to physically make it. While our application is oriented towards amigurumi, it could be extended to work with clothing or other similar styles of crochet.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".