japan op• Data kinds: table → table
• Call: import fullseye as fs; fs.ledger.osm_road_loops(roadmask: 'dict', *, tolerance_px: 'float' = 0.75) -> 'Dict[str, object]' (to call the implementation directly, import drivejapan; drivejapan.osm_road_loops(roadmask: 'dict', *, tolerance_px: 'float' = 0.75) -> 'Dict[str, object]'; from the registry, opsdrive.get("osm_road_loops"))
Boundary loops of the union of roads. Splits them into outer loops (road edges) and holes (city blocks) and simplifies them with Douglas–Peucker.
The tracing follows pixel edges (contours_xld._trace_mask_boundaries), so the sum of loop areas before decimation = number of pixels × step² (outer − holes) holds exactly (area_check). Whether a loop is a hole or outer is decided by whether the pixel just to the right of the loop's leftmost vertical edge is road. Return value {"outer": [(K,2) xy], "holes": [(K,2) xy], "outer_raw", "holes_raw", "area_check": {"loops_m2", "pixels_m2", "abs_err"}}.
Empty input (roadmask is an empty dict) raises ValueError.
• 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_japan_town — py -3.11 examples/poc_driving_japan_town.py
table as input)course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same
japan)osm_synthetic · osm_parse · osm_road_graph · osm_road_mask · osm_route · japan_world · japan_stats · latlon_to_local
*Provenance: drivejapan.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.