ttc op• Data kinds: image2d × image2d → table
• Call: import fullseye as fs; fs.ledger.ttc_from_flow(u, v, dt: 'float', *, foe=None, mask=None, min_speed: 'float' = 0.001, at_first_frame: 'bool' = True) -> 'dict' (to call the implementation directly, import drivettc; drivettc.ttc_from_flow(u, v, dt: 'float', *, foe=None, mask=None, min_speed: 'float' = 0.001, at_first_frame: 'bool' = True) -> 'dict'; from the registry, opsdrive.get("ttc_from_flow"))
τ (seconds) from optical flow: {"tau_map", "tau", "n", "foe"}.
> The detailed description below is the original text — the summary and the headings are translated.
sceneflow.time_to_contact(画素ごと、コマ単位、FoE からの半径² / 半径方向の流れ)を秒に直す。2 コマの差分の流れが返すのは 2 コマ目の時刻の τ(Z₁ / (Z₀ − Z₁) コマ)なので、at_first_frame=True (既定)は 1 コマ足して最初のコマの τ にする(等速なら厳密、ttc_truth と同じ時刻)。foe を省くと流れから推定する(sceneflow.focus_of_expansion)。真の FoE は foe_from_motion。tau は mask(省略時は全画素)の中で有限・正の τ の中央値(無ければ inf)、n はその画素数。
• 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_ttc_rss — py -3.11 examples/poc_ttc_rss.py
table as input)course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same
ttc)relative_motion · foe_from_motion · flow_from_depth_motion · ttc_truth · ttc_from_scale · ttc_from_range · label_extent · foe_from_flow
*Provenance: drivettc.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.