Expand regional corpus and aerial finetuning controls

backend/tests/test_belgium_candidate_evaluation.py

@@ -22,3 +22,7 @@ def test_empty_reference_counts_false_positives() -> None:
     predictions = [((0.0, 0.0, 10.0, 10.0), 0.4)]
     assert MODULE.match_boxes(predictions, [], confidence=0.25, match_iou=0.5) == (0, 1, 0)
     assert MODULE.match_boxes(predictions, [], confidence=0.5, match_iou=0.5) == (0, 0, 0)
+
+
+def test_box_scaling_preserves_center() -> None:
+    assert MODULE.scale_box((10.0, 20.0, 30.0, 40.0), 1.5) == (5.0, 15.0, 35.0, 45.0)

backend/tests/test_belgium_training_loop.py

@@ -33,6 +33,32 @@ def test_training_command_is_cuda_deterministic_and_bound_to_frozen_inputs(tmp_p
     assert "epochs=160" in command
     assert "max_det=1000" in command
     assert "imgsz=640" in command
+    assert "optimizer=auto" in command
+    assert "mosaic=1.0" in command
+
+
+def test_training_command_supports_conservative_aerial_finetuning(tmp_path: Path) -> None:
+    command = MODULE.training_command(
+        "yolo",
+        model=tmp_path / "base.pt",
+        data=tmp_path / "dataset.yaml",
+        project=tmp_path / "runs",
+        name="aerial",
+        epochs=50,
+        seed=42,
+        batch=2,
+        workers=0,
+        optimizer="AdamW",
+        lr0=0.0001,
+        mosaic=0.0,
+        scale=0.2,
+        translate=0.05,
+    )
+    assert "optimizer=AdamW" in command
+    assert "lr0=0.0001" in command
+    assert "mosaic=0.0" in command
+    assert "scale=0.2" in command
+    assert "translate=0.05" in command
     assert f"data={tmp_path / 'dataset.yaml'}" in command