label_extent — DRIVE `ttc` op

• Data kinds: labels2d → table

• Call: import fullseye as fs; fs.ledger.label_extent(label, value: 'int') -> 'dict' (to call the implementation directly, import drivettc; drivettc.label_extent(label, value: 'int') -> 'dict'; from the registry, opsdrive.get("label_extent"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

ラベル像の中で値 `value の画素の箱: {"col0", "col1", "row0", "row1", "width", "height", "n"}`。

幅・高さは画素数(`col1 − col0 + 1)。無ければ全部 0。:func:ttc_from_scale` の入力(完全な検出器の代役)。

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_ttc_rss — py -3.11 examples/poc_ttc_rss.py

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

course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same

Same category (`ttc`)

relative_motion · foe_from_motion · flow_from_depth_motion · ttc_truth · ttc_from_flow · ttc_from_scale · ttc_from_range · foe_from_flow

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

label_extent — DRIVE ttc op