space_carving op• Data kinds: images → voxel
• Call: import fullseye as fs; fs.ledger.carve(silhouettes: 'Sequence[np.ndarray]', Ks: 'Sequence[np.ndarray]', Rs: 'Sequence[np.ndarray]', ts: 'Sequence[np.ndarray]', bounds: 'Bounds', res: 'int') -> 'np.ndarray' (to call the implementation directly, import visualhull; visualhull.carve(silhouettes: 'Sequence[np.ndarray]', Ks: 'Sequence[np.ndarray]', Rs: 'Sequence[np.ndarray]', ts: 'Sequence[np.ndarray]', bounds: 'Bounds', res: 'int') -> 'np.ndarray'; from the registry, ops3d.get("carve"))
Discretise bounds into res^3 voxels and keep those that project inside every silhouette (space carving).
Projects each voxel centre into every camera m with X_cam = R_m X + t_m, and keeps only the voxels that satisfy depth>0, inside the image, and foreground in silhouettes[m], all of them (intersection of the view cones). Silhouettes/cameras are lists of length M.
silhouettes : list of (H, W) bool array foreground mask of each camera (M of them).
Ks, Rs, ts : list intrinsic parameters, rotation and translation of each camera (M each).
bounds : ((xmin,xmax),(ymin,ymax),(zmin,zmax)) box region to carve.
res : int number of voxel divisions per axis (total voxels = res^3).
(res, res, res) bool ndarray occupied voxels. With indexing='ij' the axes are (x, y, z).
The centre of vox[i,j,k] is (xmin+(i+.5)dx, ymin+(j+.5)dy, zmin+(k+.5)dz).
• blender_interop — Using Blender alongside — build the shape, measure it with fullseye (pitfalls: axes, units, ground truth)
• 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.
• space_carving — py -3.11 examples_3d/space_carving.py
voxel as input)voxel_to_mips · voxel_to_mesh · signed_distance_field · to_points · sobel3d · hessian3d · curvature_maps · edt_jfa
space_carving)visual_hull · synthesize_silhouette · carve_look_at
*Provenance: visualhull.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.