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
 
 

docs/BELGIUM_BUILDING_TRAINING_LOOP.md

@@ -80,6 +80,10 @@ The active production model remains unchanged while any gate fails.
 
 Every failed assessment returns `continue_training_loop`. Only a report with
 `training_complete` may proceed to final human review and guarded activation.
+Optimizer, initial learning rate, image size and geometric augmentation are
+explicit loop inputs. This permits a conservative aerial-imagery finetune
+(for example AdamW with mosaic disabled) without changing calibration, test
+or release gates.
 
 After a failed assessment,
 `scripts/build_failure_driven_yolo_sampling.py` creates a checksummed,

scripts/evaluate_belgium_building_candidate.py

@@ -52,6 +52,14 @@ def metrics(tp: int, fp: int, fn: int) -> dict[str, float | int]:
     }
 
 
+def scale_box(box: tuple[float, float, float, float], factor: float) -> tuple[float, float, float, float]:
+    """Scale a detector box around its center for calibration-only geometry correction."""
+    x1, y1, x2, y2 = box
+    cx, cy = (x1 + x2) / 2, (y1 + y2) / 2
+    half_width, half_height = (x2 - x1) * factor / 2, (y2 - y1) * factor / 2
+    return cx - half_width, cy - half_height, cx + half_width, cy + half_height
+
+
 def read_references(path: Path, width: int, height: int) -> list[tuple[float, float, float, float]]:
     boxes = []
     for line in path.read_text(encoding="utf-8").splitlines() if path.is_file() else []:
@@ -88,6 +96,7 @@ def main() -> int:
         default=1000,
         help="Maximum detections retained per tile; dense Belgian urban tiles exceed YOLO's default 300.",
     )
+    parser.add_argument("--box-scale", type=float, default=1.0)
     args = parser.parse_args()
 
     from ultralytics import YOLO
@@ -119,7 +128,7 @@ def main() -> int:
     for tile, result in zip(tiles, results, strict=True):
         height, width = result.orig_shape
         predictions = [
-            (tuple(map(float, box)), float(score))
+            (scale_box(tuple(map(float, box)), args.box_scale), float(score))
             for box, score in zip(result.boxes.xyxy.cpu().tolist(), result.boxes.conf.cpu().tolist(), strict=True)
         ]
         observations.append(
@@ -163,6 +172,7 @@ def main() -> int:
         "test_time_augmentation": args.augment,
         "inference_imgsz": args.imgsz,
         "max_detections_per_tile": args.max_det,
+        "box_scale": args.box_scale,
         "tile_count": len(tiles),
         "sweeps": sweeps,
     }

scripts/provision_belgium_building_training_portfolio.py

@@ -52,6 +52,35 @@ AOIS = (
     Aoi("zeebrugge-port-train-hard", "flanders", "port-hard-negative", "train", 3.205, 51.330, "background_candidate"),
     Aoi("hoge-kempen-train-bg", "flanders", "forest-heath-negative", "train", 5.650, 50.990, "background_candidate"),
     Aoi("westhoek-dunes-train-bg", "flanders", "dunes-negative", "train", 2.590, 51.095, "background_candidate"),
+    # v11 full-AOI review: independent train-only coverage for the Flemish
+    # image/roof domain that remained the limiting release region.  These
+    # centers are separated from the frozen calibration and test AOIs.
+    Aoi("geel-urban-train-v12", "flanders", "mixed-urban", "train", 4.989, 51.165),
+    Aoi("mol-urban-train-v12", "flanders", "ribbon-development", "train", 5.116, 51.190),
+    Aoi("beringen-train-v12", "flanders", "suburban", "train", 5.226, 51.050),
+    Aoi("bilzen-train-v12", "flanders", "small-city", "train", 5.519, 50.871),
+    Aoi("bree-train-v12", "flanders", "small-city", "train", 5.597, 51.141),
+    Aoi("maaseik-train-v12", "flanders", "historic-urban", "train", 5.790, 51.095),
+    Aoi("peer-train-v12", "flanders", "ribbon-development", "train", 5.459, 51.130),
+    Aoi("diksmuide-train-v12", "flanders", "small-city", "train", 2.865, 51.034),
+    Aoi("ieper-train-v12", "flanders", "historic-urban", "train", 2.885, 50.851),
+    Aoi("poperinge-train-v12", "flanders", "rural-town", "train", 2.726, 50.855),
+    Aoi("eeklo-train-v12", "flanders", "mixed-urban", "train", 3.570, 51.185),
+    Aoi("oudenaarde-train-v12", "flanders", "historic-urban", "train", 3.600, 50.845),
+    Aoi("geraardsbergen-train-v12", "flanders", "hilly-urban", "train", 3.882, 50.771),
+    Aoi("ninove-train-v12", "flanders", "mixed-urban", "train", 4.025, 50.835),
+    Aoi("zottegem-train-v12", "flanders", "ribbon-development", "train", 3.815, 50.870),
+    Aoi("ronse-train-v12", "flanders", "regional-architecture", "train", 3.600, 50.745),
+    Aoi("halle-train-v12", "flanders", "dense-urban", "train", 4.235, 50.735),
+    Aoi("vilvoorde-train-v12", "flanders", "urban-industrial", "train", 4.430, 50.930),
+    Aoi("boom-train-v12", "flanders", "dense-urban", "train", 4.370, 51.090),
+    Aoi("heist-op-den-berg-train-v12", "flanders", "ribbon-development", "train", 4.715, 51.075),
+    Aoi("aalter-train-v12", "flanders", "suburban", "train", 3.445, 51.090),
+    Aoi("wetteren-train-v12", "flanders", "mixed-urban", "train", 3.885, 51.005),
+    Aoi("sint-truiden-train-v12", "flanders", "historic-urban", "train", 5.190, 50.815),
+    Aoi("brasschaat-heath-train-v12-bg", "flanders", "heath-hard-negative", "train", 4.525, 51.350, "background_candidate"),
+    Aoi("limburg-pine-train-v12-bg", "flanders", "forest-hard-negative", "train", 5.680, 51.020, "background_candidate"),
+    Aoi("westhoek-field-train-v12-bg", "flanders", "farmland-hard-negative", "train", 2.720, 50.990, "background_candidate"),
     Aoi("bruges-val", "flanders", "historic-urban", "val", 3.224, 51.209),
     Aoi("turnhout-val", "flanders", "suburban", "val", 4.944, 51.322),
     Aoi("hasselt-cal", "flanders", "suburban", "calibration", 5.340, 50.930),
@@ -82,6 +111,14 @@ AOIS = (
     Aoi("arlon-industry-train", "wallonia", "industrial", "train", 5.790, 49.676),
     Aoi("liege-rail-train-hard", "wallonia", "rail-hard-negative", "train", 5.615, 50.625, "background_candidate"),
     Aoi("famenne-quarry-train-hard", "wallonia", "quarry-hard-negative", "train", 5.080, 50.170, "background_candidate"),
+    Aoi("spa-train-v12", "wallonia", "regional-architecture", "train", 5.867, 50.492),
+    Aoi("malmedy-train-v12", "wallonia", "small-city", "train", 6.027, 50.426),
+    Aoi("rochefort-train-v12", "wallonia", "rural-town", "train", 5.222, 50.159),
+    Aoi("beauraing-train-v12", "wallonia", "rural-town", "train", 4.956, 50.110),
+    Aoi("thuin-train-v12", "wallonia", "valley-urban", "train", 4.286, 50.339),
+    Aoi("peruwelz-train-v12", "wallonia", "mixed-urban", "train", 3.591, 50.509),
+    Aoi("ardenne-clearing-train-v12-bg", "wallonia", "forest-hard-negative", "train", 5.460, 50.080, "background_candidate"),
+    Aoi("condroz-open-train-v12-bg", "wallonia", "farmland-hard-negative", "train", 5.020, 50.390, "background_candidate"),
     Aoi("tournai-val", "wallonia", "historic-urban", "val", 3.389, 50.606),
     Aoi("arlon-val", "wallonia", "small-city", "val", 5.817, 49.683),
     Aoi("verviers-cal", "wallonia", "suburban", "calibration", 5.860, 50.590),

scripts/run_belgium_building_training_loop.py

@@ -42,8 +42,13 @@ def training_command(
     workers: int,
     max_det: int = 1000,
     imgsz: int = 640,
+    optimizer: str = "auto",
+    lr0: float | None = None,
+    mosaic: float = 1.0,
+    scale: float = 0.5,
+    translate: float = 0.1,
 ) -> list[str]:
-    return [
+    command = [
         yolo,
         "train",
         f"model={model}",
@@ -57,12 +62,19 @@ def training_command(
         "cache=disk",
         "close_mosaic=20",
         f"max_det={max_det}",
+        f"optimizer={optimizer}",
+        f"mosaic={mosaic}",
+        f"scale={scale}",
+        f"translate={translate}",
         f"seed={seed}",
         "deterministic=True",
         f"project={project}",
         f"name={name}",
         "exist_ok=True",
     ]
+    if lr0 is not None:
+        command.append(f"lr0={lr0}")
+    return command
 
 
 def run(command: list[str], log_path: Path | None = None, *, allowed: set[int] = {0}) -> int:
@@ -93,6 +105,11 @@ def main() -> int:
     parser.add_argument("--workers", type=int, default=4)
     parser.add_argument("--max-det", type=int, default=1000)
     parser.add_argument("--imgsz", type=int, default=640)
+    parser.add_argument("--optimizer", default="auto")
+    parser.add_argument("--lr0", type=float)
+    parser.add_argument("--mosaic", type=float, default=1.0)
+    parser.add_argument("--scale", type=float, default=0.5)
+    parser.add_argument("--translate", type=float, default=0.1)
     parser.add_argument("--seed", type=int, default=20260731)
     parser.add_argument("--yolo", default="yolo")
     parser.add_argument("--dry-run", action="store_true")
@@ -140,6 +157,11 @@ def main() -> int:
             workers=args.workers,
             max_det=args.max_det,
             imgsz=args.imgsz,
+            optimizer=args.optimizer,
+            lr0=args.lr0,
+            mosaic=args.mosaic,
+            scale=args.scale,
+            translate=args.translate,
         )
         if args.dry_run:
             print(json.dumps({"training_command": command}, indent=2))