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feat(perception): qualify lidar evidence before models

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DCCONSTRUCTIONS
2026-07-25 01:00:26 +03:00
parent 37c24b5fa8
commit 3f549f91f1
8 changed files with 1185 additions and 0 deletions
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experiments/perception/worker/run_e15_shadow_inference.py
+14
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@@ -92,6 +92,11 @@ from k1link.compute.inline_temporal import (
read_inline_profile,
stabilize_world_state,
)
from k1link.compute.lidar_contract import (
K1_LIVE_LIDAR_PROFILE,
LidarQualityMonitor,
lidar_readiness_document,
)
from k1link.compute.live_perception import (
LIVE_RESULT_MAX_PAYLOAD_BYTES,
LiveSensorSynchronizer,
@@ -563,6 +568,7 @@ def _receiver(
max_duration_seconds: float,
decoder: PersistentFmp4Decoder,
synchronizer: LiveSensorSynchronizer,
lidar_quality: LidarQualityMonitor,
state: _TransportState,
sensor_decode_ms: dict[str, list[float]],
result_queue: queue.Queue[bytes],
@@ -690,6 +696,7 @@ def _receiver(
)
sensor_decode_ms[modality].append((time.perf_counter() - decode_started) * 1000)
if modality == "lidar" and isinstance(normalized, DecodedPointCloudView):
lidar_quality.observe(normalized)
synchronizer.publish_point_cloud(normalized)
elif modality == "pose" and isinstance(normalized, DecodedPoseView):
synchronizer.publish_pose(normalized)
@@ -919,6 +926,7 @@ def run(args: argparse.Namespace, loaded: _LoadedModels | None = None) -> int:
capacity_per_modality=int(temporal["buffer_capacity_per_modality"]),
retention_seconds=float(temporal["retention_seconds"]),
)
lidar_quality = LidarQualityMonitor(K1_LIVE_LIDAR_PROFILE)
first_camera_epoch_ns: list[int] = []
last_camera_epoch_ns: list[int] = []
decoded_frame_count = 0
@@ -1034,6 +1042,7 @@ def run(args: argparse.Namespace, loaded: _LoadedModels | None = None) -> int:
"semantic": semantic_queue.snapshot,
"decoder": decoder.snapshot,
"synchronizer": synchronizer.snapshot,
"lidar_quality": lidar_quality.snapshot,
"result": lambda: {
"capacity": result_queue.maxsize,
"depth": result_queue.qsize(),
@@ -1102,6 +1111,7 @@ def run(args: argparse.Namespace, loaded: _LoadedModels | None = None) -> int:
"max_duration_seconds": args.max_duration_seconds,
"decoder": decoder,
"synchronizer": synchronizer,
"lidar_quality": lidar_quality,
"state": transport,
"sensor_decode_ms": sensor_decode_ms,
"result_queue": result_queue,
@@ -1491,6 +1501,7 @@ def run(args: argparse.Namespace, loaded: _LoadedModels | None = None) -> int:
"id": common["projection_manifest"]["pack_id"],
"identity_sha256": common["projection_manifest"]["identity_sha256"],
},
"lidar_evidence": lidar_readiness_document(K1_LIVE_LIDAR_PROFILE),
"worker_package": {
"id": common["worker_package"]["package_id"],
"identity_sha256": common["worker_package"]["identity_sha256"],
@@ -1554,6 +1565,7 @@ def run(args: argparse.Namespace, loaded: _LoadedModels | None = None) -> int:
"synchronizer": synchronizer.snapshot(),
"sensor_decode_ms": sensor_decode_summary,
},
"lidar_quality": lidar_quality.snapshot(),
"latency_ms": latency_summary,
"temporal_stability": {
"enabled": stability is not None,
@@ -1602,6 +1614,8 @@ def run(args: argparse.Namespace, loaded: _LoadedModels | None = None) -> int:
"limitations": [
"Shadow diagnostic authority only; no commands or navigation output.",
"Camera/LiDAR matching uses recorded host arrival time, not a hardware clock.",
"K1 LiDAR is a vendor map increment, not an admitted raw sensor sweep.",
"K1 LiDAR has no admitted per-point time, ring, scan geometry or IMU stream.",
"Cross-host source epoch age is diagnostic and excluded from acceptance.",
"COCO and Cityscapes models are not forest-domain or safety validated.",
"Amodal cuboids infer unobserved volume from class priors.",