typed op• Data kinds: points → points
• Call: fullseye.apply(img, "tb_random_rotation", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*
*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
Stages (the ops that come before → this op, left to right):
▸ tb_random_rotation: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ tb_random_rotation: other inputs (docs site)
Applies a random rotation and returns `(rotated, R)` (mimicking viewpoint change).
> The detailed description below is the original text — the summary and the headings are translated.
`R は正規直交・det=+1(rotated = points @ R.T = 各点に R` を左作用、
逆変換は `rotated @ R)。max_angle=None` なら Shoemake 法で一様ランダム回転、
`max_angle 指定(ラジアン, 期待 [0, π])なら軸を球面一様・角を [0, max_angle]`
一様に取り、回転角を制限する(`arccos((tr R -1)/2) ≤ max_angle` を厳密に保証)。
`max_angle < 0 は ValueError、max_angle=0` は単位行列。単位はラジアン(度で
渡すと桁違いに大きくなる)。`max_angle=None` の一様回転は上限 π までの大きな回転も
普通に出るので、視点変化の範囲を絞りたいときは `max_angle` を使う。回転は原点まわり
で、雲が原点から離れていれば重心も動く。`R の規約 rotated = points @ R.T` は
`register_fpfh・register_shot が返す dst ≈ src @ R.T + t` と同じ向きなので、
推定結果との角度誤差は `arccos((tr(R_est·Rᵀ)-1)/2) で測れる。seed` で決定論的
(同 seed なら同じ `R)。返り値は float64 の (N,3) と (3,3)`。
2-D 進化レジストリへ橋渡しした 3d の op `random_rotation。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。
• 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 program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.
img_to_points 0.50 0.50 tb_random_rotation 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op random_rotation. This bridge op is the same implementation adapted to the fn(v, a, b) convention, so the behaviour carries over unchanged (only the call form differs).
• augment_pointcloud — py -3.11 examples_3d/augment_pointcloud.py
• sh_descriptor_retrieval — py -3.11 examples_3d/sh_descriptor_retrieval.py
• shape_retrieval — py -3.11 examples_3d/shape_retrieval.py
points as input)identity · tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal
typed)tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal · tb_voxel_grid_downsample
*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.