random_scale — 3D augment op

• Data kinds: points → points

• Call: import fullseye as fs; fs.ledger.random_scale(points, lo: 'float', hi: 'float', seed: 'int' = 0) -> 'Tuple[np.ndarray, float]' (to call the implementation directly, import pcl_augment; pcl_augment.random_scale(points, lo: 'float', hi: 'float', seed: 'int' = 0) -> 'Tuple[np.ndarray, float]'; from the registry, ops3d.get("random_scale"))

• Return value through the ledger: fullseye.ledger.random_scale(...) returns only the declared out type points (the underlying function also returns auxiliary values). When you need what was dropped, use fullseye.ledger.random_scale.raw(...) or call pcl_augment.random_scale directly.

Usage

Apply a uniform scale s ~ U(lo, hi) about the origin and return (scaled, s).

scaled = points * s. The bbox diagonal becomes exactly s times longer (since s > 0, max/min are both multiplied by s → the diagonal ‖max-min‖ is also s times). Injects variation in object scale (distance / sensor magnification) into training. Requires 0 < lo <= hi (fail-closed).

lo <= 0 or hi < lo raises ValueError (lo == hi is allowed and always gives s = lo). Scaling is about the origin, so if the cloud is far from the origin its centroid also moves to s times its position (position and size change at the same time). To change only the size, move the centroid to the origin beforehand. s is a Python float; the returned point cloud is float64. Deterministic with seed. Empty input returns empty.

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)

• augment_pointcloud — py -3.11 examples_3d/augment_pointcloud.py

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

points_to_voxel · gaussians_to_voxel · estimate_point_normals · to_points · match_points_ncc · match_pca · moment_axes · icp_point2point_3d

Same category (augment)

jitter · random_rotation · random_dropout · elastic_deform · cutout

*Provenance: pcl_augment.py — 3D 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.