regionprops op• Data kinds: voxel → voxel
• Call: import fullseye as fs; fs.ledger.largest_component(vol, connectivity: 'int' = 26) -> 'np.ndarray' (to call the implementation directly, import regionprops3d; regionprops3d.largest_component(vol, connectivity: 'int' = 26) -> 'np.ndarray'; from the registry, ops3d.get("largest_component"))
Return the bool mask of the largest (most voxels) connected component.
If there is no foreground, an all-False mask (same shape as vol).
Notes:
• Calls label_components internally, counts voxels per label with bincount and picks the largest. On a tie the label with the smaller number (earlier in scipy's scan order) wins.
• The input is converted to bool with everything other than 0 as foreground (NaN is foreground too). The axis order is (z, y, x).
• The return value is bool with the same shape as the input. With no foreground it is all False (no exception).
• Raises ValueError: input that is not 3-dimensional, connectivity other than 6/18/26.
• Typical: from a binary volume produced by thresholding, discard noise blobs and keep only the main object. To keep several, use filter_by_volume; to select by features, vol_select_labels.
• measurement_uncertainty — Measurement uncertainty and calibration — what it takes to claim you are measuring
• 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.
• region_props_3d — py -3.11 examples_3d/region_props_3d.py
voxel as input)voxel_to_mips · voxel_to_mesh · signed_distance_field · to_points · sobel3d · hessian3d · curvature_maps · edt_jfa
regionprops)label_components · region_props · filter_by_volume · inner_box3 · vol_label · vol_region_props
*Provenance: regionprops3d.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.