patchbank_score — SPC anomaly_patch op

• 数据种类:image2d × table → table

• 调用: import fullseye as fs; fs.ledger.patchbank_score(image, model, k=1, smooth=4.0)(要直接调用实现,import anomaly_patch; anomaly_patch.patchbank_score(image, model, k=1, smooth=4.0);从台账取用则 opsspc.get("patchbank_score"))

用法

将一张图像与记忆库比较:由各图块到最近 k 个良品图块的距离生成异常图(table)。

> 以下的详细说明为原文 —— 摘要与标题已翻译。

model comes from patchbank_fit; image must have the training images' shape. The distance (Euclidean, in standardised feature space; the mean over the k nearest) is computed exactly by brute force, interpolated to the image size and smoothed by a Gaussian of smooth px. Returns map (H, W), grid (raw distances), image_score (maximum of the smoothed map), k and smooth.

Raises ValueError for a model that is not a patchbank_fit result, a different image shape, k larger than the bank, or a negative / non-finite smooth.

参考(示例数据、文献)

• 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。

可运行的示例(实际调用该算子并已验证的样例)

• poc_patch_anomaly — py -3.11 examples/poc_patch_anomaly.py

类型可衔接的下一个算子(可接受 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

同类别(anomaly_patch)

patch_features · patchdist_fit · patchdist_score · patchbank_fit


*Provenance: anomaly_patch.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.