feat: add measured detection review loop

2026-07-15 03:00:08 +02:00
parent 94ecd377b7
commit d22abe8e7b
27 changed files with 1578 additions and 29 deletions
@@ -0,0 +1,253 @@
+from __future__ import annotations
+
+from pathlib import Path
+from uuid import UUID, uuid4
+
+import pytest
+from fastapi.testclient import TestClient
+from geoalchemy2.shape import from_shape
+from shapely.geometry import box
+
+from app.core.errors import AppError
+from app.db.session import get_db
+from app.main import app
+from app.models import Detection, DetectionReview, QualityCheck, VectorFeature
+from app.schemas.detection_review import (
+    DetectionReviewList,
+    DetectionReviewRead,
+    DetectionReviewSummary,
+    DetectionReviewUpsert,
+)
+from app.services.detection_review_service import DetectionReviewService
+
+
+ROOT = Path(__file__).resolve().parents[2]
+
+
+class FakeQuery:
+    def __init__(self, rows):
+        self.rows = list(rows)
+
+    def filter(self, *criteria):
+        for criterion in criteria:
+            left = getattr(criterion, "left", None)
+            right = getattr(criterion, "right", None)
+            operator = getattr(criterion, "operator", None)
+            name = getattr(left, "name", None)
+            value = getattr(right, "value", right)
+            if name and operator and operator.__name__ == "eq":
+                self.rows = [row for row in self.rows if getattr(row, name) == value]
+        return self
+
+    def all(self):
+        return list(self.rows)
+
+    def first(self):
+        return self.rows[0] if self.rows else None
+
+
+class FakeSession:
+    def __init__(self, objects=None, query_rows=None) -> None:
+        self.objects = objects or {}
+        self.query_rows = query_rows or {}
+
+    def get(self, model, item_id):
+        return self.objects.get((model, item_id))
+
+    def query(self, model):
+        return FakeQuery(self.query_rows.setdefault(model, []))
+
+    def add(self, row):
+        rows = self.query_rows.setdefault(type(row), [])
+        if row not in rows:
+            rows.append(row)
+        self.objects[(type(row), row.id)] = row
+
+    def commit(self):
+        return None
+
+    def refresh(self, _row):
+        return None
+
+
+def _review_context() -> tuple[FakeSession, UUID, UUID, Detection, VectorFeature]:
+    project_id = uuid4()
+    quality_check_id = uuid4()
+    analysis_run_id = uuid4()
+    candidate_dataset_id = uuid4()
+    reference_dataset_id = uuid4()
+    detection = Detection(
+        id=uuid4(),
+        project_id=project_id,
+        dataset_id=candidate_dataset_id,
+        analysis_run_id=analysis_run_id,
+        model_name="yolo-configured",
+        class_name="building",
+        confidence=0.62,
+        geometry=from_shape(box(5.0, 51.0, 5.001, 51.001), srid=4326),
+    )
+    reference = VectorFeature(
+        id=uuid4(),
+        dataset_id=reference_dataset_id,
+        source_feature_id="grb-missed",
+        feature_class="building",
+        properties_json={},
+        geometry=from_shape(box(5.002, 51.002, 5.003, 51.003), srid=4326),
+    )
+    quality_check = QualityCheck(
+        id=quality_check_id,
+        project_id=project_id,
+        analysis_run_id=analysis_run_id,
+        candidate_dataset_id=candidate_dataset_id,
+        reference_dataset_id=reference_dataset_id,
+        check_type="detections_vs_reference",
+        status="ok",
+        findings_json={
+            "false_positive_evidence": [{"candidate_feature_id": str(detection.id)}],
+            "false_negative_evidence": [{"reference_feature_id": str(reference.id)}],
+        },
+    )
+    db = FakeSession(
+        objects={
+            (QualityCheck, quality_check_id): quality_check,
+            (Detection, detection.id): detection,
+            (VectorFeature, reference.id): reference,
+        },
+        query_rows={DetectionReview: []},
+    )
+    return db, project_id, quality_check_id, detection, reference
+
+
+def test_detection_review_model_and_migration_are_aligned() -> None:
+    migration = (ROOT / "backend" / "alembic" / "versions" / "202607150001_detection_reviews.py").read_text(encoding="utf-8")
+    columns = DetectionReview.__table__.columns
+
+    for name in (
+        "project_id",
+        "quality_check_id",
+        "analysis_run_id",
+        "evidence_role",
+        "evidence_feature_id",
+        "detection_id",
+        "reference_feature_id",
+        "decision",
+        "notes",
+        "reviewed_by",
+        "created_at",
+        "updated_at",
+    ):
+        assert name in columns
+        assert f'"{name}"' in migration
+    assert 'op.create_table(\n        "detection_reviews"' in migration
+    assert 'down_revision = "202607140001"' in migration
+
+
+def test_detection_review_queue_persists_only_valid_operator_decisions() -> None:
+    db, project_id, quality_check_id, detection, _reference = _review_context()
+
+    initial = DetectionReviewService.list_reviews(
+        db,
+        project_id=project_id,
+        quality_check_id=quality_check_id,
+    )
+    assert initial.summary.total == 2
+    assert initial.summary.reviewed == 0
+    assert initial.summary.decision_counts == {"unreviewed": 2}
+
+    saved = DetectionReviewService.upsert_review(
+        db,
+        project_id=project_id,
+        quality_check_id=quality_check_id,
+        payload=DetectionReviewUpsert(
+            evidence_role="false_positive",
+            evidence_feature_id=str(detection.id),
+            decision="qa_alignment_mismatch",
+            notes="Box overlaps the official footprint but is not a training negative.",
+        ),
+    )
+    assert saved.decision == "qa_alignment_mismatch"
+    assert saved.detection_id == detection.id
+
+    reviewed = DetectionReviewService.list_reviews(
+        db,
+        project_id=project_id,
+        quality_check_id=quality_check_id,
+        reviewed=True,
+    )
+    assert reviewed.total == 1
+    assert reviewed.summary.reviewed == 1
+    assert reviewed.summary.remaining == 1
+
+    with pytest.raises(AppError) as exc:
+        DetectionReviewService.upsert_review(
+            db,
+            project_id=project_id,
+            quality_check_id=quality_check_id,
+            payload=DetectionReviewUpsert(
+                evidence_role="false_positive",
+                evidence_feature_id=str(detection.id),
+                decision="confirmed_model_false_negative",
+            ),
+        )
+    assert exc.value.code == "INVALID_DETECTION_REVIEW_DECISION"
+
+
+def test_detection_review_endpoints_use_canonical_envelopes(monkeypatch) -> None:
+    project_id = uuid4()
+    quality_check_id = uuid4()
+    item = DetectionReviewRead(
+        project_id=project_id,
+        quality_check_id=quality_check_id,
+        evidence_role="false_positive",
+        evidence_feature_id=str(uuid4()),
+        decision="unreviewed",
+    )
+    result = DetectionReviewList(
+        items=[item],
+        total=1,
+        limit=50,
+        offset=0,
+        summary=DetectionReviewSummary(
+            total=1,
+            reviewed=0,
+            remaining=1,
+            false_positive_total=1,
+            false_negative_total=0,
+            decision_counts={"unreviewed": 1},
+        ),
+    )
+    monkeypatch.setattr(DetectionReviewService, "list_reviews", lambda *_args, **_kwargs: result)
+    monkeypatch.setattr(DetectionReviewService, "upsert_review", lambda *_args, **_kwargs: item)
+    app.dependency_overrides[get_db] = lambda: FakeSession()
+    try:
+        listed = TestClient(app).get(f"/api/v1/projects/{project_id}/quality-checks/{quality_check_id}/reviews")
+        saved = TestClient(app).post(
+            f"/api/v1/projects/{project_id}/quality-checks/{quality_check_id}/reviews",
+            json={
+                "evidence_role": "false_positive",
+                "evidence_feature_id": item.evidence_feature_id,
+                "decision": "unreviewed",
+            },
+        )
+    finally:
+        app.dependency_overrides.pop(get_db, None)
+
+    assert listed.status_code == 200
+    assert set(listed.json()) == {"data"}
+    assert listed.json()["data"]["summary"]["remaining"] == 1
+    assert saved.status_code == 200
+    assert saved.json() == {"data": item.model_dump(mode="json")}
+
+
+def test_map_detection_qa_uses_documented_footprint_threshold_and_honest_labels() -> None:
+    hook = (ROOT / "frontend" / "src" / "hooks" / "useMapOrthophotoAnalysis.ts").read_text(encoding="utf-8")
+    app_source = (ROOT / "frontend" / "src" / "App.tsx").read_text(encoding="utf-8")
+    evidence_service = (ROOT / "backend" / "app" / "services" / "quality_evidence_service.py").read_text(encoding="utf-8")
+
+    assert "MAP_BUILDING_QA_IOU_THRESHOLD = 0.25" in hook
+    assert "kandidaten" in hook
+    assert "precision" in hook.lower()
+    assert "false, iouThreshold" in app_source
+    assert "VectorFeature.id.in_(uuid_identifiers)" in evidence_service
+    assert "VectorFeature.source_feature_id.in_(identifiers)" in evidence_service
+    assert "for row in db.query(VectorFeature).filter(VectorFeature.dataset_id" not in evidence_service