town op• Data kinds: none → table (an op determined by its arguments alone — it takes no image or data input)
• Call: import fullseye as fs; fs.ledger.kyosoku_summary(path=None) -> 'Dict[str, object]' (to call the implementation directly, import drivetown; drivetown.kyosoku_summary(path=None) -> 'Dict[str, object]'; from the registry, opsdrive.get("kyosoku_summary"))
Reads the ledger of reproduced Rules of the Road (Kyosoku) scenarios (docs/drive/kyosoku_scenarios.json) and turns it into a category × status count table.
> The detailed description below is the original text — the summary and the headings are translated.
path = None なら repo の docs/drive/kyosoku_scenarios.json(このモジュールの場所から引く)。返り値 {"total", "statuses" (順序つき), "by_status": {status: n}, "categories": [...] (件数の多い順), "by_category": {category: {status: n}}, "table": [[category, n_reproduced, n_partial, n_pending, n_not_reproducible, total], ...]}。
Raises ValueError: ファイルが無い・JSON でない・scenarios が無い・場面に id/category/status が無い・ status が KYOSOKU_STATUSES に無い・id が重複。
• 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_town — py -3.11 examples/poc_driving_town.py
table as input)course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same
town)town_chain · town_layout · town_world · town_centerline · town_stop_lines · town_rules · town_crossing_state · town_run
*Provenance: drivetown.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.