tb_random_scale — 2D `typed` op

• Data kinds: points → points

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

tb_random_scale: input → output

*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_scale: stages (docs site)

On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):

▸ tb_random_scale: other inputs (docs site)

Usage

Applies a uniform scale `s ~ U(lo, hi) about the origin and returns (scaled, s)`.

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

`scaled = points * s。bbox 対角長はちょうど s 倍になる(s > 0` なので

`max/min が共に s 倍 → 対角 ‖max-min‖ も s` 倍)。物体スケールの

ばらつき(距離/センサ倍率)を学習に注入する。`0 < lo <= hi` を要求(fail-closed)。

`lo <= 0 または hi < lo は ValueError(lo == hi は許され常に s = lo`)。

原点まわりの拡大なので、雲が原点から離れていれば重心も `s` 倍の位置へ動く(位置と

大きさが同時に変わる)。大きさだけ変えたいなら事前に重心を原点へ寄せる。`s` は

Python float、返り値の点群は float64。`seed` で決定論的。空入力は空を返す。

2-D 進化レジストリへ橋渡しした 3d の op `random_scale。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.

Try it in Studio

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_scale 0.50 0.50

▸ Load this pipeline · Load & run

Runnable examples (verified samples that actually call this op)

The examples below call the underlying ledger op random_scale. 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

Ops the type connects to (they accept `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

Same category (`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).*

tb_random_scale — 2D typed op