depth_denoise op• Data kinds: depth × image2d → depth
• Call: import fullseye as fs; fs.ledger.joint_bilateral(depth: 'np.ndarray', guide: 'np.ndarray', spatial_sigma: 'float', range_sigma: 'float', *, invalid: 'float | None' = 0.0, truncate: 'float' = 3.0) -> 'np.ndarray' (to call the implementation directly, import depth_bilateral; depth_bilateral.joint_bilateral(depth: 'np.ndarray', guide: 'np.ndarray', spatial_sigma: 'float', range_sigma: 'float', *, invalid: 'float | None' = 0.0, truncate: 'float' = 3.0) -> 'np.ndarray'; from the registry, ops3d.get("joint_bilateral"))
Joint / cross bilateral: the depth is what gets smoothed, while the range weights come from the differences in the guide. → float64 (H,W).
Even if the depth is coarse, steps can be preserved using the sharp edges of a clean guide (RGB luminance, another sensor). range_sigma is in units of the guide value. Pixels where the guide is non-finite, and pixels where the depth is invalid, do not contribute. guide and depth must have the same shape (fail-closed).
• blender_interop — Using Blender alongside — build the shape, measure it with fullseye (pitfalls: axes, units, ground truth)
• 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.
• sensor_seg — py -3.11 examples_3d/sensor_seg.py
depth as input)depth_to_points · tsdf_from_depth · to_points · fuse_to_voxel · depth_to_organized_points · normals_from_depth · occlusion_edges · bearing_angle_image
depth_denoise)bilateral_filter_depth · fill_holes
*Provenance: depth_bilateral.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.