score op• 資料種類:labels2d × labels2d → table
• 呼叫: import fullseye as fs; fs.ledger.seg_contingency(a, b, ignore_label=None)(要直接呼叫實作,import segcompare; segcompare.seg_contingency(a, b, ignore_label=None);從台帳取用則 opsemproof.get("seg_contingency"))
> 該運算子的說明尚無譯文,以下照原文給出。
The contingency table of truth a against candidate b (sparse).
Returns labels_a / labels_b (the distinct labels), rows / cols (indices into them) and counts for every co-occurring pair, plus n (pixels counted), row_sums (size of each truth object) and col_sums (size of each candidate object). counts.sum() == n, row_sums.sum() == col_sums.sum() == n.
Raises ValueError: non-integer, non-finite, boolean-free-but-string or masked input; not 2-D / 3-D; empty; different shapes; every pixel ignored.
• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。
• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。
• 演算法的正典(作者、年份)與用途見上面的族使用指南。
• (尚無)
table 作為輸入)seg_synapse_partners · seg_wiring_variation · seg_synapse_nri · seg_wiring_exposure
score)seg_variation_of_information · seg_rand
*Provenance: segcompare.py — EMPROOF 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.