seg_score_card — SEGMENTATION score op

• Data kinds: labels2d × labels2d → table

• Call: import fullseye as fs; fs.ledger.seg_score_card(labels_pred, labels_true, *, background: 'int' = 0, tau: 'float' = 2.0, min_overlap: 'float' = 0.5) -> 'Dict[str, float]' (to call the implementation directly, import segeval; segeval.seg_score_card(labels_pred, labels_true, *, background: 'int' = 0, tau: 'float' = 2.0, min_overlap: 'float' = 0.5) -> 'Dict[str, float]'; from the registry, opssegmentation.get("seg_score_card"))

Usage

All measures on one card: Dice/Jaccard, VI/split/merge, Rand/ARI, boundary F, Hausdorff/HD95/ASSD, over/under, split/merge/missed/false/matched and counts (seg_score_card).

Pass a = truth, b = prediction to segcompare (split = how much the prediction cut the truth, merge = how much the prediction glued the truth together). Values form a flat dict of float or int (lined up directly in a table).

Detailed usage guide

• halcon_segmentation family guide

Background guides (the physics and conventions behind this op)

• segmentation_scoring_and_worlds — Scoring segmentations and synthetic worlds with ground truth — which metric is blind to which failure

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_active_contours — py -3.11 examples/poc_active_contours.py

• poc_graph_hierarchy_segmentation — py -3.11 examples/poc_graph_hierarchy_segmentation.py

• poc_segmentation_gauntlet — py -3.11 examples/poc_segmentation_gauntlet.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_under_over_segmentation · seg_object_counts_match

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

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.