gaussians op• Data kinds: points → gaussians
• Call: import fullseye as fs; fs.ledger.points_to_gaussians(points, k=6, scale=1.0) (to call the implementation directly, import reprconv; reprconv.points_to_gaussians(points, k=6, scale=1.0); from the registry, opsreprconv.get("points_to_gaussians"))
A point set (N,3) → isotropic gaussians. The only entry into this type.
gaussians is a type that fuse3d.to_points consumes in the ledger, but not even 1 op produced it (measured) -- a type that only has consumers is never executed unless a generator is planted as a seed. Here it is built the same way as the initialisation of 3D Gaussian Splatting: sigma is the mean distance to each point's k nearest neighbours, and the weights are an equal split of 1/N.
mu is the input points themselves, so a round trip with gaussians_to_points is bit-identical (measured max|Δ| = 0.0). sigma and w do not come back in the round trip -- they are quantities the point cloud never had to begin with, so this is not a loss but an addition.
Args:
points: (N, 3). N >= 2.
k: number of neighbours that determines sigma (default 6). Values above N-1 are clipped to N-1.
scale: factor multiplied onto sigma (default 1.0).
Returns:
dict(mu (N,3) / sigma (N,) / w (N,)).
Raises:
ValueError: N < 2 / k < 1 / scale <= 0 / bad shape / non-finite.
• 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 canonical algorithm (author, year) and its uses are named in the family usage guide above.
• representation_roundtrip — py -3.11 examples/representation_roundtrip.py
gaussians as input)gaussians_to_points · gaussians_to_voxel
gaussians)gaussians_to_points · gaussians_to_voxel
*Provenance: reprconv.py — REPRCONV 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.