pointmap_to_points — REPRCONV `structure` op

• Data kinds: pointmap → points

• Call: import fullseye as fs; fs.ledger.pointmap_to_points(pointmap, drop_nonpositive_z=False) (to call the implementation directly, import reprconv; reprconv.pointmap_to_points(pointmap, drop_nonpositive_z=False); from the registry, opsreprconv.get("pointmap_to_points"))

• GPU: none (CPU reference implementation only)

Usage

Grid-organised 3-D points pointmap (H,W,3) → a point cloud points (N,3). The exit from pointmap.

> The detailed description below is the original text — the summary and the headings are translated.

行優先(row-major)に並べ直し、非有限の行は捨てる(pointmap では NaN が「その画素は無効」の印なので、ここでは拒否せず落とす)。drop_nonpositive_z=True は z <= 0 の行も捨てる —— depth_to_organized_points のカメラ座標の pointmap は無効深度 0 が原点に集まるので、その場合に使う(depth_to_points と同じ規約になり、同じ内部行列なら同じ点が同じ順に出る)。地心座標(dem_geocentric_grid)では z が負になりうるので既定は False。列の意味(x, y, z)は入力のまま変えない。

Args:

pointmap: (H, W, 3)。

drop_nonpositive_z: True で z <= 0 の行も捨てる。

Returns:

(N, 3) float64。

Raises:

ValueError: (H, W, 3) でない / 空 / 有効な点が 1 つも残らない。

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• type_connectivity_tour — py -3.11 examples/type_connectivity_tour.py

Ops the type connects to (they accept `points` as input)

points_zyx_to_keypoints_uv · points_to_position · select_points · flow_apply · points_to_gaussians

Same category (`structure`)

frame_axis · knn_graph_to_conn_graph · match_component

*Provenance: reprconv.py — REPRCONV operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

pointmap_to_points — REPRCONV structure op