anomaly_eval op• データ種: video × video → table
• 呼び出し: import fullseye as fs; fs.ledger.anomaly_pro(scores, masks, fpr_max=0.3) (実装を直接呼ぶなら import anomeval; anomeval.anomaly_pro(scores, masks, fpr_max=0.3)、台帳から引くなら opsspc.get("anomaly_pro"))
Per-region overlap (PRO) curve and its normalised area AUPRO up to fpr_max (table).
Definition (Bergmann et al., CVPR 2020): at a threshold t, every 8-connected defect region C of every mask scores |{score >= t} ∩ C| / |C|; PRO(t) is the mean over all regions, so a small defect weighs as much as a large one. FPR(t) is the fraction of all good pixels with score >= t. The curve is evaluated exactly at every distinct score (sorted cumulative sums, no threshold grid), starts at (0, 0), is integrated by the trapezoid rule up to fpr_max (the customary 0.3; linear interpolation at the cut) and divided by fpr_max → aupro in [0, 1]. Returns aupro, fpr / pro (the curve up to the cut), n_regions, fpr_max.
Raises ValueError on empty / mismatched / non-finite input, non-binary masks, no defect region, no good pixel, or fpr_max outside (0, 1].
• サンプルデータ カタログ(DL URL / ライセンス) — 2-D は skimage.data(BSD/public)+ 合成、3-D は実データ源(Stanford/PDS 等)の DL URL。
• 演算子の来歴・参考文献 — この op 族の元になった研究/手法の出典。
• アルゴリズムの正典(著者・年)と用途は上記ファミリ使い方ガイドに記載。
• anomaly_eval_metrics — py -3.11 examples/anomaly_eval_metrics.py
• poc_good_sample_variation_model — py -3.11 examples/poc_good_sample_variation_model.py
• poc_patch_anomaly — py -3.11 examples/poc_patch_anomaly.py
table を入力に取れる)msa_anova_table · msa_gauge_rr · msa_bias_linearity · msa_attribute_agreement · gum_standard_uncertainty · gum_propagate · gum_expanded · gum_monte_carlo
anomaly_eval)anomaly_image_auroc · anomaly_pixel_auroc · anomaly_region_overlap · anomaly_pixel_f1_max · anomaly_image_f1_max · anomaly_operating_point
*Provenance: anomeval.py — SPC operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.