seg_label_changes — EMPROOF `inject` op

• Data kinds: labels2d × labels2d → table

• Call: import fullseye as fs; fs.ledger.seg_label_changes(before, after, min_pixels: 'int' = 1, ignore_zero: 'bool' = True) -> 'dict' (to call the implementation directly, import emproof; emproof.seg_label_changes(before, after, min_pixels: 'int' = 1, ignore_zero: 'bool' = True) -> 'dict'; from the registry, opsemproof.get("seg_label_changes"))

Usage

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

2 枚のラベル画像の差を融合と分断の対として返す(校正の前後、または仕込んだ誤りの答え合わせ)。

`before のラベル b と after のラベル a が同じ画素を min_pixels` 以上共有する対を数え、

• 融合 = after の 1 ラベルが before の 2 ラベル以上を覆う → `merge_after / merge_before`(対ごとに 1 行。

吸った側の id 自身も before の 1 つとして並ぶ)

• 分断 = before の 1 ラベルが after の 2 ラベル以上に割れる → `split_before / split_after`(同様に

残った側の id も並ぶ)

`n_merged / n_split` は誤りの数(after 側・before 側の id で数える)。id の一致は見ない

(ラベルを振り直した 2 枚でも使える)。

>>> ch = seg_label_changes(truth, seg_inject_merge(truth))

>>> int(ch["n_merged"])

Detailed usage guide

• emproof 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_em_second_opinion — py -3.11 examples/poc_em_second_opinion.py

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

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Same category (`inject`)

seg_inject_merge · seg_inject_split

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

seg_label_changes — EMPROOF inject op