swarm_render_overhead — DRIVE swarmflow op

• Data kinds: matrix × any × scalar → image2d

• Call: import fullseye as fs; fs.ledger.swarm_render_overhead(points, shape, res: 'float', center=(0.0, 0.0), diameter_px: 'float' = 3.0, intensity: 'float' = 1.0, background: 'float' = 0.0) -> 'np.ndarray' (to call the implementation directly, import swarmflow; swarmflow.swarm_render_overhead(points, shape, res: 'float', center=(0.0, 0.0), diameter_px: 'float' = 3.0, intensity: 'float' = 1.0, background: 'float' = 0.0) -> 'np.ndarray'; from the registry, opsdrive.get("swarm_render_overhead"))

Usage

Individual positions → 1 overhead frame (Gaussian bright spots, diameter = 2 × standard deviation = the PIV convention, same as pivops).

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

Args:

points: (N, 2) の位置 [m] (空でもよい = 背景だけ)。

shape: (H, W) [px]。

res: 画素の大きさ [m/px]。

center: 画像の中心の世界座標 [m]。

diameter_px: 輝点の直径 [px]。

intensity: 輝点の明るさ。

background: 一様な下駄。

Returns:

(H, W) float64。

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)

• poc_swarm_obstacle_from_flow — py -3.11 examples/poc_swarm_obstacle_from_flow.py

Ops the type connects to (they accept image2d as input)

flow_from_depth_motion · ttc_truth · ttc_from_flow · foe_from_flow · perlin2 · fbm_height · fbm_gradient · radial_periodogram

Same category (swarmflow)

sph_kernel · sph_density_pressure · swarm_simulate · swarm_field_from_tracks · swarm_field_from_piv · potential_flow_cylinder · velocity_deficit_map · stagnation_from_centerline


*Provenance: swarmflow.py — DRIVE 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.