shape_descriptor op• Data kinds: points → descriptor
• Call: import fullseye as fs; fs.ledger.d2_distribution(points, bins: 'int' = 64, samples: 'int' = 100000, seed: 'int' = 0) -> 'np.ndarray' (to call the implementation directly, import descriptors3d; descriptors3d.d2_distribution(points, bins: 'int' = 64, samples: 'int' = 100000, seed: 'int' = 0) -> 'np.ndarray'; from the registry, ops3d.get("d2_distribution"))
The distribution of Euclidean distances between random point pairs (Osada 2002's D2).
Randomly draws samples pairs of distinct points (i, j) from the N points and aggregates their distances. Distances are normalised by dividing by the mean distance, so the result is invariant to rotation, translation and scale. Returns a normalised histogram (bins,) over the fixed range [0, _D2_MAX] (sum 1).
points : array_like, shape (N, 3)
Point cloud. N >= 2 is required.
bins : int
Number of histogram bins.
samples : int
Number of point pairs to draw. More lowers the variance (sampling error ~ 1/sqrt(samples)).
seed : int
Random seed. Same seed and same point cloud give deterministically identical results.
np.ndarray, shape (bins,)
Normalised distance histogram.
• 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.
• shape_desc_pose — py -3.11 examples_3d/shape_desc_pose.py
descriptor as input)fuse_to_voxel · shape_distance
shape_descriptor)a3_distribution · extent_signature · describe · shape_distance
*Provenance: descriptors3d.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.