augment op• Data kinds: points → points
• Call: import fullseye as fs; fs.ledger.random_dropout(points, ratio: 'float', seed: 'int' = 0) -> 'Tuple[np.ndarray, np.ndarray]' (to call the implementation directly, import pcl_augment; pcl_augment.random_dropout(points, ratio: 'float', seed: 'int' = 0) -> 'Tuple[np.ndarray, np.ndarray]'; from the registry, ops3d.get("random_dropout"))
• Return value through the ledger: fullseye.ledger.random_dropout(...) returns only the declared out type points (the underlying function also returns auxiliary values). When you need what was dropped, use fullseye.ledger.random_dropout.raw(...) or call pcl_augment.random_dropout directly.
Randomly remove a ratio fraction of the points and return (kept, kept_idx) (mimicking dropout).
The number of points kept is round((1-ratio)*N). kept_idx is an ascending index into the original array, and kept == points[kept_idx] holds exactly. Reproduces point loss from occlusion / sparse viewpoints in training. Requires 0 <= ratio <= 1.
ratio outside [0,1] raises ValueError. ratio=1 gives an empty (0,3) and an empty index, ratio=0 gives all points (in the original order). The number of points kept is decided by Python's round (round half to even), so at .5 ties it goes to the even side. seed fixes the permutation, so it is deterministic. The return value is (kept float64 (M,3), kept_idx int64 (M,)). Removal is spatially uniform, so to mimic local loss (occlusion) use cutout.
• 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.
• augment_pointcloud — py -3.11 examples_3d/augment_pointcloud.py
points as input)points_to_voxel · gaussians_to_voxel · estimate_point_normals · to_points · match_points_ncc · match_pca · moment_axes · icp_point2point_3d
augment)jitter · random_rotation · random_scale · 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.