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"))
• GPU:无(仅 CPU 参考实现)
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, a negative / non-finite smooth, or an image on another pixel scale than the good images (integer vs float dtype, or values outside the training range widened by one training span on each side).
• 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。
• poc_ai_built_inspection_scored — py -3.11 examples/poc_ai_built_inspection_scored.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_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.