Decompose: Implement real auto-digitize engine — Phase 2: Region Classification #7
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Mark/Kimi_Agent_Brother_10_Digitizing_App#7
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⚠️ Re-scoped — blocked on #11
~/Projects/easystitch/src/embroidery_converter/classifier.py~/Projects/easystitch/src/svg_annotation/element_classifier.pyDonor note
EasyStitch's classifier operates on SVG semantic metadata
(element class, stroke/fill attributes), not on raster pixel data.
ThreadCraft's fabric is vector primitives on a Fabric.js canvas, so
the same shape of rule applies: a TypeScript port of the rule set
is the right approach. Do not call the EasyStitch service for this —
classification runs over canvas state and must be synchronous so
the Editor's right-panel can preview changes live.
Port the heuristics directly. The EasyStitch file is the spec; the
tests there (
tests/test_main.py, the test files indata/withexpected
auto_classification.dstoutputs) are the acceptance cases.Blocked on #11 (Stand up EasyStitch as an HTTP service for ThreadCraft).
This work has been re-scoped — see the updated body. The reframe replaces
"implement from scratch" with "call the EasyStitch service and render the
result." #11 must complete first; once the service exposes
/v1/digitizeand/v1/export, this work becomes a thin client + canvas rendering job.cc: #11