Raise configured YOLO max detections

backend/tests/test_sprint8b_yolo_foundation.py

@@ -93,7 +93,7 @@ class RecordingPredictModel:
     def __init__(self) -> None:
         self.seen_sources: list[dict] = []
 
-    def predict(self, *, source, conf, imgsz, device, verbose):
+    def predict(self, *, source, conf, imgsz, device, verbose, max_det):
         from PIL import Image
 
         with Image.open(source) as image:
@@ -106,6 +106,7 @@ class RecordingPredictModel:
                     "imgsz": imgsz,
                     "device": device,
                     "verbose": verbose,
+                    "max_det": max_det,
                 }
             )
         return []
@@ -399,6 +400,20 @@ def test_yolo_adapter_converts_single_band_tiles_to_rgb_before_prediction(tmp_pa
     assert model.seen_sources[0]["imgsz"] == 64
     assert model.seen_sources[0]["device"] == "cpu"
     assert model.seen_sources[0]["verbose"] is False
+    assert model.seen_sources[0]["max_det"] == 1000
+
+
+def test_yolo_adapter_uses_configured_max_detections(tmp_path: Path) -> None:
+    Image = pytest.importorskip("PIL.Image")
+    tile_path = tmp_path / "rgb_tile.png"
+    Image.new("RGB", (16, 16), (10, 20, 30)).save(tile_path)
+    model = RecordingPredictModel()
+    settings = _settings(tmp_path, yolo_max_detections=1500)
+
+    detections = YoloDetectionAdapter(settings).predict_tile(model, tile_path, confidence_threshold=0.25)
+
+    assert detections == []
+    assert model.seen_sources[0]["max_det"] == 1500
 
 
 def test_yolo_adapter_wraps_prediction_runtime_errors(tmp_path: Path) -> None: