score op• Data kinds: labels2d × labels2d → table
• Call: import fullseye as fs; fs.ledger.seg_boundary_f(labels_pred, labels_true, *, tau: 'float' = 2.0) -> 'Dict[str, object]' (to call the implementation directly, import segeval; segeval.seg_boundary_f(labels_pred, labels_true, *, tau: 'float' = 2.0) -> 'Dict[str, object]'; from the registry, opssegmentation.get("seg_boundary_f"))
Boundary F-measure at tolerance tau: precision = fraction of predicted boundary pixels within tau of a true boundary, recall the reverse (seg_boundary_f).
F = 2PR/(P+R). Boundaries follow the convention of _boundary (cracks between labels, 1 pixel wide), so they do not depend on label numbers or on which label is background (only the shape of the partition matters). Distance is by distance transform (Euclidean, pixel centres). τ = 0 means pixel coincidence. If both boundaries are empty (both 1 colour), P = R = F = 1; if only one is empty, 0.
Returns: f, precision, recall, tau, n_pred_boundary / n_true_boundary, dist_pred_to_true / dist_true_to_pred (distance per boundary pixel).
• halcon_segmentation family guide
• segmentation_scoring_and_worlds — Scoring segmentations and synthetic worlds with ground truth — which metric is blind to which failure
• 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.
• poc_am_thermal_to_ct — py -3.11 examples/poc_am_thermal_to_ct.py
• poc_graph_hierarchy_segmentation — py -3.11 examples/poc_graph_hierarchy_segmentation.py
table as input)score)seg_confusion_table · seg_dice_jaccard · seg_hausdorff · seg_mean_surface_distance · seg_under_over_segmentation · 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).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.