seg_under_over_segmentation — SEGMENTATION `score` op

• Data kinds: labels2d × labels2d → table

• Call: import fullseye as fs; fs.ledger.seg_under_over_segmentation(labels_pred, labels_true, *, background: 'int' = 0) -> 'Dict[str, object]' (to call the implementation directly, import segeval; segeval.seg_under_over_segmentation(labels_pred, labels_true, *, background: 'int' = 0) -> 'Dict[str, object]'; from the registry, opssegmentation.get("seg_under_over_segmentation"))

Usage

Counts over- and under-segmentation as the multiplicity of the contingency-table majority vote (Levine & Nazif style) (seg_under_over_segmentation).

> The detailed description below is the original text — the summary and the headings are translated.

各予測(背景以外)を、最も重なる真(背景も候補)に帰属させる。真 i に帰属した予測の数 k_i が `pieces_per_true`、

`over` = Σ max(k_i − 1, 0)(1 つの真が何個に割れたか)。各真を最も重なる予測に帰属させ、予測 j に帰属した真の数 m_j が

`objects_per_pred、under` = Σ max(m_j − 1, 0)(1 つの予測が何個の真を抱えたか)。

背景に帰属した予測は `spurious(偽)、背景に帰属した真は missed`(欠落)に数える。

返り値: `over、under、spurious、missed、labels_true / pieces_per_true、labels_pred / objects_per_pred`、

`over_segmented_true(k ≥ 2 の真のラベル)、under_segmented_pred`(m ≥ 2 の予測のラベル)。

Detailed usage guide

• halcon_segmentation family guide

Background guides (the physics and conventions behind this op)

• segmentation_scoring_and_worlds — 分割の採点と真値つき合成世界 — どの物差しがどの壊れ方に盲目か

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_graph_hierarchy_segmentation — py -3.11 examples/poc_graph_hierarchy_segmentation.py

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

class_ndim_norm

Same category (`score`)

seg_confusion_table · seg_dice_jaccard · seg_boundary_f · seg_hausdorff · seg_mean_surface_distance · seg_object_counts_match · seg_score_card

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

seg_under_over_segmentation — SEGMENTATION score op