tb_cutout — 2D `typed` op

• Data kinds: points → points

• Call: fullseye.apply(img, "tb_cutout", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Removes a spatial axis-aligned box region and returns `(kept, kept_idx)` (mimicking localized missing data).

> The detailed description below is the original text — the summary and the headings are translated.

既存の点を 1 つ一様サンプルして中心とし、辺長 `extent`(スカラ=立方体, または

`(3,)`=各軸辺長)のボックス内の点をすべて除去する。中心点自身が必ず入るため

最低 1 点は除去される。除去点は必ず辺長 `extent` のボックスに収まる(空間的に

局所的 = ランダム散布とは判別可能)。`kept == points[kept_idx]、extent > 0`。

2-D 進化レジストリへ橋渡しした 3d の op `cutout。実装は同じで、呼び出し規約だけ op(v, a, b) に合わせてある。この op に調整点は無く、a も b` も使われない。

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• (none yet)

Ops the type connects to (they accept `points` as input)

identity · tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal

Same category (`typed`)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

tb_cutout — 2D typed op