lead_truth_depth — DRIVE `carla` op

• Data kinds: table → scalar

• Call: import fullseye as fs; fs.ledger.lead_truth_depth(scene) -> 'float' (to call the implementation directly, import carlabridge; carlabridge.lead_truth_depth(scene) -> 'float'; from the registry, opsdrive.get("lead_truth_depth"))

Usage

Closed form from the recorded pose: image-plane distance [m] to the center of the lead vehicle's rear face. rear face = center − half length × lead vehicle's forward direction, image-plane distance = (rear face − camera)·camera forward direction. inf without a lead vehicle.

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_carla_bridge — py -3.11 examples/poc_carla_bridge.py

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

spin_from_marker_sequence · carla_transform_matrix · carla_pose_to_world · carla_camera_pose · carla_xy_yaw · carla_scene_load · town_chain · osm_parse

Same category (`carla`)

carla_labels · carla_label_map · carla_label_unmap · carla_depth_decode · carla_depth_encode · carla_intrinsics · intrinsics_to_fullseye · intrinsics_to_carla

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

lead_truth_depth — DRIVE carla op