fusion op• Data kinds: any → voxel
• Call: import fullseye as fs; fs.ledger.fuse_to_voxel(items, size=64, bounds=None, device='cpu', smooth=0.8) (to call the implementation directly, import fuse3d; fuse3d.fuse_to_voxel(items, size=64, bounds=None, device='cpu', smooth=0.8); from the registry, ops3d.get("fuse_to_voxel"))
• Return value through the ledger: fullseye.ledger.fuse_to_voxel(...) returns only the declared out type voxel (the underlying function also returns auxiliary values). When you need what was dropped, use fullseye.ledger.fuse_to_voxel.raw(...) or call fuse3d.fuse_to_voxel directly.
• Underlying return: (voxel, bounds)
• GPU: this op has a GPU path (device="cuda")
Fuse several structures into one common density voxel volume (TRIZ integration). items=[(data, kind, params_dict), ...].
Brings complementary structures such as mesh (topology) + points (samples) + depth (observations) into 1 representation. Returns (voxel, bounds).
Procedure: each (data, kind, params) is turned into a point cloud with to_points(data, kind, **params), concatenated vertically, and splatted into a size^3 density grid with match3d.points_to_voxel (+1 to the cell each point falls into; if smooth > 0, smoothed with a Gaussian of σ = smooth voxels). If bounds=None, the (min, max) of the concatenated point cloud becomes the grid range.
Args:
• items: a non-empty list/tuple whose elements are length-3 (data, kind, params_dict) (params_dict must be a dict). To change samples of to_points, put samples= into params.
• size: number of voxels per 1 axis (fixed cubic grid).
• bounds: (lo, hi), each of length 3. When putting several clouds on the same grid (comparison, voxel_iou), always give it explicitly.
• device: torch device ("cpu" / "cuda"). smooth: Gaussian σ [voxel].
Returns: (voxel, bounds) — voxel is a (size, size, size) float64 point-count density (sum ≈ total number of points, not a probability), bounds is the (lo, hi) actually used. The grid index is floor((p - lo) / span * (size - 1)) of points_to_voxel, and axis 0 corresponds to the x component of the points (voxel axis order = point component order).
Validation (ValueError): items not a list/tuple, empty, elements not 3-tuples, params not a dict (stops at the entrance the misuse of passing raw data directly).
• depth_sensors — Depth sensors — ranging principles, real-device figures, how dropouts appear
• 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.
• transforms_repr — py -3.11 examples_3d/transforms_repr.py
voxel as input)voxel_to_mips · voxel_to_mesh · signed_distance_field · to_points · sobel3d · hessian3d · curvature_maps · edt_jfa
fusion)*Provenance: fuse3d.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.