macro op• Data kinds: image → image
• Call: fullseye.apply(img, "macro_binarize", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
A fixed pipeline discovered by evolutionary search: `bilateral(a=0.06,b=0.89) → unsharp(a=0.51,b=0.34) → bilateral(a=0.04,b=0.24) → lowpass(a=0.75,b=0.59) → gopen(a=0.38,b=1.00) → unsharp(a=0.78,b=0.68)` (6 stages that alternate smoothing and unsharp masking, clean up with a lowpass and grayscale opening, then sharpen once more).
> The detailed description below is the original text — the summary and the headings are translated.
`a, b` は凍結済みで未使用。binarize 課題（IoU）でロック済みホールドアウト 0.75、手作りベースライン 0.62 を上回るが、train 0.91 / holdout0.95 に対し locked_holdout は 0.75 まで落ちる —— 分割ごとの差を隠さず書く（feedback_benchmark_honest_disclosure）。HALCON に対応する単一オペレータは無い。
• gallery2d_physics_alife_3d family guide
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• gallery2d_physics_alife_3d — py -3.11 examples/gallery2d_physics_alife_3d.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
macro)macro_denoise · macro_edge · macro_vol_denoise
*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.