feat(lab): complete E30 evidence review gate
This commit is contained in:
DCCONSTRUCTIONS
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from __future__ import annotations
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import hashlib
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import json
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from pathlib import Path
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from typing import Any
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import numpy as np
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from fastapi import APIRouter
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from fastapi.routing import APIRoute
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from k1link.compute import e30_materialization as materialization
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from k1link.compute.e30_materialization import build_e30_materialization
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from k1link.compute.semantic_geometry_fusion import (
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CameraGeometryFusionProfile,
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_projection_profile,
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_semantic_support,
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)
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from k1link.device_plugins.xgrids_k1.analyze.calibrated_projection import (
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project_map_points_kb4,
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)
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from k1link.web.e30_review_api import build_e30_review_router
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def _canonical(value: object) -> bytes:
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return json.dumps(
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value,
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ensure_ascii=False,
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sort_keys=True,
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separators=(",", ":"),
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allow_nan=False,
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).encode()
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def _sha256(path: Path) -> str:
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return hashlib.sha256(path.read_bytes()).hexdigest()
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def _endpoint(router: APIRouter, path: str) -> object:
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for route in router.routes:
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if (
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isinstance(route, APIRoute)
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and route.path == path
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and route.methods is not None
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and "GET" in route.methods
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):
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return route.endpoint
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raise AssertionError(f"GET {path} route is missing")
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class _FakeSource:
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def __init__(self, root: Path) -> None:
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self.root = root
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self.pack_id = root.name
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self.arrays = {
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"cloud_offsets": np.asarray([0, 4], dtype=np.int64),
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"cloud_points_map": np.asarray(
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[
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[0.00, 0.00, 2.0],
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[0.10, 0.00, 2.0],
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[0.20, 0.00, 2.0],
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[1.50, 1.50, 2.0],
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],
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dtype=np.float32,
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),
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"pose_positions_map": np.zeros((1, 3), dtype=np.float64),
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"pose_quaternions_map_from_lidar": np.asarray(
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[[0.0, 0.0, 0.0, 1.0]],
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dtype=np.float64,
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),
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"sample_available": np.asarray([True], dtype=np.bool_),
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"source_frame_indices": np.asarray([10], dtype=np.int64),
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"session_seconds": np.asarray([12.5], dtype=np.float64),
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"intrinsic_fx_fy_cx_cy": np.asarray(
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[100.0, 100.0, 50.0, 50.0],
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dtype=np.float64,
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),
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"distortion_kb4": np.zeros(4, dtype=np.float64),
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"t_camera_from_lidar": np.eye(4, dtype=np.float64),
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}
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self.identity: dict[str, Any] = {
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"session_id": "source-session",
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"frame_count": 1,
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"point_count": 4,
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"source_id": "sensor.camera.right",
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"camera_slot": "camera_1",
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"projection": {"width": 100, "height": 100},
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}
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self.manifest = {"artifact": {"sha256": "1" * 64}}
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@property
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def frame_count(self) -> int:
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return 1
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@property
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def point_count(self) -> int:
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return 4
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def close(self) -> None:
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pass
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class _FakeSurface:
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def __init__(self, root: Path) -> None:
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self.root = root
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self.model_id = root.name
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self.identity: dict[str, Any] = {
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"source_pack_id": "e10-lidar-pack-" + "b" * 64,
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"frame_count": 1,
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"point_count": 4,
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}
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self.arrays = {
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"frame_valid": np.asarray([True], dtype=np.bool_),
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"point_class": np.asarray([2, 2, 2, 1], dtype=np.uint8),
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"point_height_m": np.asarray([0.5, 0.5, 0.5, 0.0], dtype=np.float32),
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}
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self.manifest = {
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"artifacts": [
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{"role": "local-surface", "sha256": "2" * 64},
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]
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}
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def close(self) -> None:
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pass
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def _write_source_tree(tmp_path: Path) -> tuple[dict[str, Path], str]:
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source_pack_id = "e10-lidar-pack-" + "b" * 64
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local_surface_id = "k1-local-surface-" + "c" * 64
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source_result_identity = {"schema_version": "test-source/v1"}
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source_result_identity_sha256 = hashlib.sha256(
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_canonical(source_result_identity)
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).hexdigest()
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source_result_id = (
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f"e10-integrated-perception-{source_result_identity_sha256}"
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)
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roots = {
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"e29": tmp_path / "e29",
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"source_results": tmp_path / "source-results",
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"source_packs": tmp_path / "source-packs",
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"surfaces": tmp_path / "surfaces",
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"reviews": tmp_path / "reviews",
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"output": tmp_path / "output",
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}
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for root in roots.values():
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root.mkdir()
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(roots["source_packs"] / source_pack_id).mkdir()
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(roots["surfaces"] / local_surface_id).mkdir()
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source_result = roots["source_results"] / source_result_id
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source_result.mkdir()
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result_document = {
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"result_id": source_result_id,
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"identity_sha256": source_result_identity_sha256,
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"identity": source_result_identity,
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}
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(source_result / "result.json").write_bytes(_canonical(result_document))
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fusion_frame = {
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"schema_version": "missioncore.e10-fusion-frame/v1",
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"frame_index": 0,
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"source_frame_index": 10,
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"session_seconds": 12.5,
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"objects": [
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{
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"source_track_id": 7,
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"track_id": 70,
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"label": "car",
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"association_group": "vehicle",
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"score": 0.9,
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"bbox_xyxy": [40.0, 40.0, 70.0, 60.0],
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"cuboid_status": "observed",
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"camera_motion_state": "static",
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"camera_motion_confidence": 0.8,
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"motion_state": "unknown",
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"motion_status": "test",
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}
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],
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}
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fusion_path = source_result / "fusion-frames.jsonl"
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fusion_path.write_bytes(_canonical(fusion_frame) + b"\n")
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source = _FakeSource(roots["source_packs"] / source_pack_id)
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profile = CameraGeometryFusionProfile()
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points = np.asarray(source.arrays["cloud_points_map"], dtype=np.float64)
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projected = project_map_points_kb4(
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points,
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position_map_xyz=(0.0, 0.0, 0.0),
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orientation_map_from_lidar_xyzw=(0.0, 0.0, 0.0, 1.0),
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profile=_projection_profile(source), # type: ignore[arg-type]
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)
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snapshot = _semantic_support(
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fusion_frame["objects"][0],
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projected=projected,
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frame_points_map=points,
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point_class=np.asarray([2, 2, 2, 1], dtype=np.uint8),
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point_height_m=np.asarray([0.5, 0.5, 0.5, 0.0], dtype=np.float32),
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source_available=True,
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surface_valid=True,
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profile=profile,
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).document
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assert snapshot["geometry_status"] == "agree"
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e29_identity = {
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"schema_version": "missioncore.e29-camera-geometry-fusion/v1",
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"source_result_id": source_result_id,
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"source_fusion_frames_sha256": _sha256(fusion_path),
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"source_pack_id": source_pack_id,
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"local_surface_model_id": local_surface_id,
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"frame_count": 1,
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"profile": profile.to_dict(),
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"authority": {
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"commands_enabled": False,
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"navigation_or_safety_accepted": False,
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},
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}
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e29_identity_sha256 = hashlib.sha256(_canonical(e29_identity)).hexdigest()
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e29_result_id = f"e29-camera-geometry-{e29_identity_sha256}"
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e29_result = roots["e29"] / e29_result_id
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e29_result.mkdir()
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e29_manifest = {
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"schema_version": "missioncore.e29-camera-geometry-fusion/v1",
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"result_id": e29_result_id,
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"identity_sha256": e29_identity_sha256,
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"identity": e29_identity,
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}
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(e29_result / "manifest.json").write_bytes(_canonical(e29_manifest))
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review_item_id = "e30-review-item-" + "d" * 64
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review_item = {
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"schema_version": "missioncore.e30-evidence-review-item/v1",
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"sequence": 0,
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"item_id": review_item_id,
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"review_key": "semantic:0:0",
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"stratum": "agree",
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"range_bucket": "near",
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"evidence_binding": {
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"frame_index": 0,
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"source_frame_index": 10,
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"session_seconds": 12.5,
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},
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"e29_locator": {
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"kind": "semantic-observation",
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"observation_index": 0,
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},
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"e29_snapshot": snapshot,
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"review": {"state": "unreviewed", "reason_code": None, "notes": None},
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"authority": {
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"commands_enabled": False,
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"navigation_or_safety_accepted": False,
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},
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}
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review_items = _canonical(review_item) + b"\n"
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review_identity = {
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"source": {
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"e29_result_id": e29_result_id,
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"e29_identity_sha256": e29_identity_sha256,
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"camera_result_id": source_result_id,
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"lidar_pack_id": source_pack_id,
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"local_surface_model_id": local_surface_id,
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},
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"reason_taxonomy": [
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"no_lidar_observation",
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"outside_lidar_support",
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"outside_camera_fov",
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"time_mismatch",
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"semantic_mismatch",
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"geometry_mismatch",
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"insufficient_evidence",
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"other",
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],
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}
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review_identity_sha256 = hashlib.sha256(_canonical(review_identity)).hexdigest()
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review_result_id = f"e30-review-pack-{review_identity_sha256}"
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review_root = roots["reviews"] / review_result_id
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review_root.mkdir()
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items_path = review_root / "review-items.jsonl"
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items_path.write_bytes(review_items)
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review_manifest = {
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"schema_version": "missioncore.e30-evidence-review-pack/v1",
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"result_id": review_result_id,
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"identity_sha256": review_identity_sha256,
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"identity": review_identity,
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"human_review_complete": False,
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"lab_published": False,
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"selected_item_count": 1,
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"artifacts": [
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{
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"role": "review-items",
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"path": items_path.name,
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"byte_length": items_path.stat().st_size,
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"sha256": _sha256(items_path),
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}
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],
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"authority": {
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"commands_enabled": False,
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"navigation_or_safety_accepted": False,
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},
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}
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(review_root / "manifest.json").write_bytes(_canonical(review_manifest))
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roots["review_root"] = review_root
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return roots, review_item_id
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def test_materialization_replays_exact_support_and_publishes_point_indices(
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tmp_path: Path,
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monkeypatch: Any,
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) -> None:
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roots, review_item_id = _write_source_tree(tmp_path)
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monkeypatch.setattr(materialization, "E10LidarFieldSource", _FakeSource)
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monkeypatch.setattr(materialization, "K1LocalSurfaceV1", _FakeSurface)
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result = build_e30_materialization(
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review_pack_root=roots["review_root"],
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e29_root=roots["e29"],
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source_result_root=roots["source_results"],
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source_pack_root=roots["source_packs"],
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local_surface_root=roots["surfaces"],
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output_root=roots["output"],
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)
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assert result.manifest["item_count"] == 1
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assert result.manifest["human_review_complete"] is False
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index = json.loads(
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(result.result_root / "materialized-items.jsonl").read_text()
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)
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assert index["item_id"] == review_item_id
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assert index["materialization"]["selected_point_count"] == 3
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assert index["materialization"]["source_reprojection_required"] is False
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artifact = result.result_root / index["artifact"]["path"]
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with np.load(artifact, allow_pickle=False) as arrays:
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assert arrays["selected_source_indices"].tolist() == [0, 1, 2]
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assert arrays["projected_selected_mask"].sum() == 3
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assert arrays["projected_candidate_mask"].sum() >= 3
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def test_e30_review_api_exposes_verified_read_only_evidence(
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tmp_path: Path,
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monkeypatch: Any,
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) -> None:
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roots, review_item_id = _write_source_tree(tmp_path)
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monkeypatch.setattr(materialization, "E10LidarFieldSource", _FakeSource)
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monkeypatch.setattr(materialization, "K1LocalSurfaceV1", _FakeSurface)
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result = build_e30_materialization(
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review_pack_root=roots["review_root"],
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e29_root=roots["e29"],
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source_result_root=roots["source_results"],
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source_pack_root=roots["source_packs"],
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local_surface_root=roots["surfaces"],
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output_root=roots["output"],
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)
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router = build_e30_review_router(
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materialization_root_provider=lambda: roots["output"],
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review_pack_root_provider=lambda: roots["reviews"],
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)
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catalog_route = _endpoint(router, "/api/v1/laboratory/e30/reviews")
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items_route = _endpoint(
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router,
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"/api/v1/laboratory/e30/reviews/{result_id}/items",
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)
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detail_route = _endpoint(
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router,
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"/api/v1/laboratory/e30/reviews/{result_id}/items/{item_id}",
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)
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catalog = catalog_route(limit=1) # type: ignore[operator]
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items = items_route( # type: ignore[operator]
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result_id=result.result_id,
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stratum="agree",
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limit=48,
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cursor=0,
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)
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detail = detail_route( # type: ignore[operator]
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result_id=result.result_id,
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item_id=review_item_id,
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)
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assert catalog["configured"] is True
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assert catalog["items"][0]["access"] == "read-only"
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assert catalog["items"][0]["stratum_counts"]["agree"] == 1
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assert items["total"] == 1
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assert items["items"][0]["item_id"] == review_item_id
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assert detail["item"]["selected"]["source_indices"] == [0, 1, 2]
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assert detail["item"]["projection"]["selected_mask"] == [1, 1, 1]
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assert str(tmp_path) not in repr(catalog)
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assert str(tmp_path) not in repr(items)
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assert str(tmp_path) not in repr(detail)
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artifact = result.result_root / "items" / f"{review_item_id}.npz"
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artifact.write_bytes(artifact.read_bytes() + b"changed")
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tampered = catalog_route(limit=1) # type: ignore[operator]
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assert tampered["candidate_total"] == 1
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assert tampered["invalid_total"] == 1
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assert tampered["items"] == []
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