course op• Data kinds: table → image2d
• Call: import fullseye as fs; fs.ledger.course_occupancy(course, cell: 'float' = 0.25, margin: 'float' = 2.0) (to call the implementation directly, import drivecourse; drivecourse.course_occupancy(course, cell: 'float' = 0.25, margin: 'float' = 2.0); from the registry, opsdrive.get("course_occupancy"))
• Return value through the ledger: fullseye.ledger.course_occupancy(...) returns only the declared out type image2d (the underlying function also returns auxiliary values). When you need what was dropped, use fullseye.ledger.course_occupancy.raw(...) or call drivecourse.course_occupancy directly.
Rasterizes a course (element or layout) into an occupancy grid (occ bool [row = y, col = x], extent).
> The detailed description below is the original text — the summary and the headings are translated.
走れる領域の外 = True(障害物)。格子は bounds を margin だけ広げた範囲を cell で覆い、各 cell の中心で偶奇判定する。extent = (xmin, xmax, ymin, ymax) は格子がちょうど覆う範囲(xmax = xmin + nx·cell)、row 0 = ymin。占有率は cell → 0 で 1 − 面積/格子面積 に収束する(門)。
Raises ValueError: cell ≤ 0、margin < 0、course の形が悪い。
• 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.
• poc_driving_school — py -3.11 examples/poc_driving_school.py
image2d as input)flow_from_depth_motion · ttc_truth · ttc_from_flow · foe_from_flow · perlin2 · fbm_height · fbm_gradient · radial_periodogram
course)course_crank · course_s_curve · course_turnaround · course_slope · course_intersection · course_parallel_parking · course_crossing · course_road
*Provenance: drivecourse.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.