Expand regional corpus and aerial finetuning controls

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))