Fix YOLO class normalization

backend/tests/test_sprint8b_yolo_foundation.py

@@ -77,6 +77,18 @@ class MockYoloAdapter:
         ]
 
 
+class MixedCaseYoloAdapter(MockYoloAdapter):
+    def predict_tile(self, model, tile_path: Path, confidence_threshold: float) -> list[dict]:
+        return [
+            {
+                "class_name": "Building",
+                "confidence": 0.91,
+                "bbox": [10.0, 20.0, 30.0, 40.0],
+                "properties": {"adapter": "mock"},
+            }
+        ]
+
+
 class RecordingPredictModel:
     def __init__(self) -> None:
         self.seen_sources: list[dict] = []
@@ -343,6 +355,33 @@ def test_yolo_run_persists_mocked_georeferenced_detections(tmp_path: Path) -> No
     assert jobs[0].status == "success"
 
 
+def test_yolo_class_filter_is_case_insensitive_and_persists_canonical_class(tmp_path: Path) -> None:
+    db, project_id, dataset_id = _project_and_dataset()
+    model_path = tmp_path / "model.pt"
+    model_path.write_bytes(b"local weights")
+    settings = _settings(tmp_path, yolo_model_path=str(model_path))
+    manifest_path = _manifest(tmp_path, tile_count=1)
+
+    result = DetectionService.run_detection(
+        db=db,
+        project_id=project_id,
+        dataset_id=dataset_id,
+        model_id="yolo-configured",
+        confidence_threshold=0.5,
+        class_filter=["building"],
+        tile_manifest_path=str(manifest_path),
+        settings=settings,
+        yolo_adapter_class=MixedCaseYoloAdapter,
+    )
+
+    detections = [item for item in db.added if isinstance(item, Detection)]
+
+    assert result.status == "success"
+    assert result.detection_count == 1
+    assert detections[0].class_name == "building"
+    assert detections[0].properties_json["model_class_name"] == "Building"
+
+
 def test_yolo_adapter_converts_single_band_tiles_to_rgb_before_prediction(tmp_path: Path) -> None:
     Image = pytest.importorskip("PIL.Image")
     tile_path = tmp_path / "single_band_tile.tif"