env_render — DRIVE `env` op

• Data kinds: table × matrix × matrix → table

• Call: import fullseye as fs; fs.ledger.env_render(world: 'dict', pose, K, width: 'int' = 640, height: 'int' = 400, env: 'Optional[dict]' = None, *, ego=None, ego_pose=None, shadows: 'bool' = True, shadow_cache: 'Optional[dict]' = None, shadow_res: 'int' = 1024) -> 'Dict[str, np.ndarray]' (to call the implementation directly, import driveenv; driveenv.env_render(world: 'dict', pose, K, width: 'int' = 640, height: 'int' = 400, env: 'Optional[dict]' = None, *, ego=None, ego_pose=None, shadows: 'bool' = True, shadow_cache: 'Optional[dict]' = None, shadow_res: 'int' = 1024) -> 'Dict[str, np.ndarray]'; from the registry, opsdrive.get("env_render"))

Usage

Renders sun, sky, shadows, lamps, headlights, fog, rain and glare in physical units.

Returns

dict : color (camera linear RGB [0,1], compressed by tone_map —— image processing reads this), display (sRGB-encoded,

for display, used only for figures), radiance (RGB luminance cd/m², linear), depth, label, face (same as driveworld.world_camera), shadow (bool, pixels in sun shadow), exposure (multiplier used), veil (veiling luminance cd/m² (H,W)), illuminance (surface illuminance lx (H,W)).

ego_pose=(x, y, yaw) = pose of the ego vehicle carrying the headlamps (2 lamps at front end 2.25 m, ±0.6 m left/right, height 0.65 m). Passing a dict to shadow_cache reuses the sun's shadow map (as long as the sun and the world do not change).

Empty input (world is an empty dict) raises ValueError.

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_driving_weather — py -3.11 examples/poc_driving_weather.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 (`env`)

julian_day · sun_at · sun_events · sun_vector · sun_illuminance · koschmieder · mor_from_beta · beta_from_mor

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

env_render — DRIVE env op