print_layer_defect_map — PRINTPATH `inspect` op

• Data kinds: image2d × image2d → image2d

• Call: import fullseye as fs; fs.ledger.print_layer_defect_map(observed: 'Any', expected: 'Any', tolerance_px: 'int' = 2, threshold: 'float' = 0.5) -> 'np.ndarray' (to call the implementation directly, import printpath; printpath.print_layer_defect_map(observed: 'Any', expected: 'Any', tolerance_px: 'int' = 2, threshold: 'float' = 0.5) -> 'np.ndarray'; from the registry, opsprintpath.get("print_layer_defect_map"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

観測した層画像と期待の層画像(`gcode_layer_image)を比べた**符号つきの欠陥図** image2d`:

+1 = あるはずの所に無い(欠け・詰まり)、−1 = 無いはずの所にある(糸引き・はみ出し・spaghetti)、0 = 一致。

両方を `threshold で二値化し、tolerance_px` だけ膨らませた相手に含まれない画素だけを欠陥にする(位置ずれと

線幅の揺れを許す)。位置合わせはしない —— カメラ像は先に `gcode_layer_image` と同じ画素格子へ写しておく。

Detailed usage guide

• printpath family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• poc_print_layer_inspection — py -3.11 examples/poc_print_layer_inspection.py

Ops the type connects to (they accept `image2d` as input)

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Same category (`inspect`)

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*Provenance: printpath.py — PRINTPATH operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

print_layer_defect_map — PRINTPATH inspect op