score op• Data kinds: labels2d × labels2d → table
• Call: import fullseye as fs; fs.ledger.seg_variation_of_information(a, b, ignore_label=None) (to call the implementation directly, import segcompare; segcompare.seg_variation_of_information(a, b, ignore_label=None); from the registry, opsemproof.get("seg_variation_of_information"))
Variation of information between truth a and candidate b, in bits.
Returns voi = split + merge, with split = H(b|a) (how much the candidate cuts true objects apart) and merge = H(a|b) (how much it glues different true objects together), plus the entropies h_a, h_b and the mutual information mi.
Raises ValueError: as seg_contingency.
• 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_em_split_merge_score — py -3.11 examples/poc_em_split_merge_score.py
• poc_em_wiring_errors — py -3.11 examples/poc_em_wiring_errors.py
• poc_skeleton_run_length_vs_voi — py -3.11 examples/poc_skeleton_run_length_vs_voi.py
table as input)seg_synapse_partners · seg_wiring_variation · seg_synapse_nri · seg_wiring_exposure
score)*Provenance: segcompare.py — EMPROOF 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.