feat(perception): add camera ego-motion evidence
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DCCONSTRUCTIONS
@@ -22,6 +22,10 @@ from k1link.sessions import (
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publish_lab_replay_cache,
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)
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from .camera_ego_motion import (
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CameraEgoMotionBuild,
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build_camera_ego_motion_result,
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)
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from .inline_temporal import StreamingSemanticStabilizer, read_inline_profile
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from .integrated_perception import (
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IntegratedPerceptionResult,
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@@ -71,6 +75,14 @@ class PublishedPersistentSupportLabInstance:
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build: PersistentSupportBuild
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@dataclass(frozen=True, slots=True)
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class PublishedCameraEgoMotionLabInstance:
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binding: LabSessionBinding
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job: CameraComputeJob
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result: IntegratedPerceptionResult
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build: CameraEgoMotionBuild
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def publish_integrated_lab_instance(
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*,
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repository_root: Path,
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@@ -709,6 +721,144 @@ def publish_e25_lab_instance(
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)
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def publish_e26_lab_instance(
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*,
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repository_root: Path,
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lidar_result_root: Path,
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camera_result_root: Path,
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profile_path: Path,
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benchmark_path: Path,
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lab_session_id: str,
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lab_id: str,
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display_name: str,
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) -> PublishedCameraEgoMotionLabInstance:
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"""Derive and publish one bounded camera/ego-motion evidence LAB run."""
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root = repository_root.expanduser().resolve(strict=True)
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jobs_root = root / ".runtime" / "compute-jobs"
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results_root = root / ".runtime" / "compute-experiments" / "e10" / "worker-results"
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packs_root = root / ".runtime" / "compute-experiments" / "e10" / "lidar-packs"
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def source(path: Path, label: str) -> IntegratedPerceptionResult:
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resolved = path.expanduser().resolve(strict=True)
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document = _read_object(resolved / "result.json", resolved)
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identity = document.get("identity")
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if not isinstance(identity, dict) or not isinstance(identity.get("job_id"), str):
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raise SessionIntegrityError(f"E26 {label} source has no job identity")
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validated = validate_integrated_perception_result(
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jobs_root / identity["job_id"],
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resolved,
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packs_root,
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)
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if not validated.accepted:
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raise SessionIntegrityError(f"E26 {label} source result is not accepted")
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return validated
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lidar_source = source(lidar_result_root, "LiDAR")
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camera_source = source(camera_result_root, "camera")
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if lidar_source.job.source_id != camera_source.job.source_id:
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raise SessionIntegrityError("E26 source camera identities differ")
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lab_job = _publish_lab_job(lidar_source.job, jobs_root, lab_session_id)
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lab_pack = _publish_lab_pack(
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lidar_source,
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lab_job,
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packs_root,
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lab_session_id,
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)
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build = build_camera_ego_motion_result(
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lidar_source=lidar_source,
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camera_source=camera_source,
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lab_job=lab_job,
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lab_pack=lab_pack,
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results_root=results_root,
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profile_path=profile_path,
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benchmark_path=benchmark_path,
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)
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validated = validate_integrated_perception_result(
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lab_job.job_root,
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build.result_root,
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packs_root,
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)
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if not validated.accepted:
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failed = [
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name
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for name, accepted in build.report["acceptance"]["checks"].items()
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if not accepted
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]
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raise SessionIntegrityError(
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f"E26 camera/ego-motion artifact acceptance failed: {', '.join(failed)}"
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)
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store = SessionStore(root)
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source_lab = store.get_lab_instance(lidar_source.job.session_id)
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source_session_id = (
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lidar_source.job.session_id
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if source_lab is None
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else source_lab.source_session_id
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)
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publish_lab_replay_cache(
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store.data_dir,
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source_session_id=source_session_id,
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lab_session_id=lab_session_id,
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timeline_start_ns=round(
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validated.timeline_start_seconds * 1_000_000_000
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),
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timeline_end_ns=round(
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validated.timeline_end_seconds * 1_000_000_000
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),
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)
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metrics = build.report["metrics"]
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binding = store.publish_lab_instance(
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session_id=lab_session_id,
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source_session_id=source_session_id,
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display_name=display_name,
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lab_id=lab_id,
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result_kind="e26-camera-ego-motion-fusion",
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result_id=validated.result_id,
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source_result_id=lidar_source.result_id,
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config_sha256=build.profile_sha256,
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run_created_at_utc=validated.created_at_utc,
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duration_seconds=(
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validated.timeline_end_seconds
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- validated.timeline_start_seconds
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),
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include_recorded_media=False,
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provenance={
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"schema_version": "missioncore.e26-lab-publication/v1",
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"storage_mode": (
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"bounded-camera-ego-motion-and-immutable-lidar-source-replay"
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),
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"source_result_id": lidar_source.result_id,
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"camera_source_result_id": camera_source.result_id,
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"source_lab_session_id": (
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None if source_lab is None else source_lab.session_id
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),
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"source_payloads_mutated": False,
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"coordinate_frame": "k1-map",
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"camera_measurement": "kb4-multiview-static-world-hypothesis",
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"metric_measurement": "e25-persistent-lidar-support",
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"lookahead_frames": 0,
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"benchmark_sha256": build.benchmark_sha256,
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"benchmark_passed": metrics["benchmark"]["passed"],
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"benchmark_passed_events": metrics["benchmark"]["passed_events"],
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"benchmark_total_events": metrics["benchmark"]["total_events"],
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"camera_ego_motion_processing_p95_ms": metrics["runtime"][
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"camera_ego_motion_frame_processing_ms"
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]["p95"],
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"peak_tracks": metrics["runtime"]["peak_tracks"],
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"camera_only_metric_velocity_valid": False,
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"navigation_or_safety_accepted": False,
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},
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)
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return PublishedCameraEgoMotionLabInstance(
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binding=binding,
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job=lab_job,
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result=validated,
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build=build,
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)
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def _validate_e23_inputs(
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worker_root: Path,
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source_report_path: Path,
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