anomaly_eval op• 数据种类:video × video → table
• 调用: import fullseye as fs; fs.ledger.anomaly_pro(scores, masks, fpr_max=0.3)(要直接调用实现,import anomeval; anomeval.anomaly_pro(scores, masks, fpr_max=0.3);从台账取用则 opsspc.get("anomaly_pro"))
按缺陷连通区域计算的重叠率(PRO)曲线,及积分到 fpr_max 的归一化面积 AUPRO(table)。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
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].
• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。
• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。
• 算法的正典(作者、年份)与用途见上面的族使用指南。
• 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 作为输入)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 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.