got detection somewhat working

tools/python-detect/manage.py

@@ -7,6 +7,7 @@ Subcommands (all take a positional boss name):
     runs     kulemak                               List training runs + metrics table
     annotate kulemak [dir]                         Launch annotation GUI
     prelabel kulemak [dir] [--model boss-kulemak]  Auto-label unlabeled images
+    export   kulemak [--imgsz 640]                Export .pt to ONNX format
 """
 
 import argparse
@@ -291,6 +292,32 @@ def cmd_prelabel(args):
 _PRELABEL_MODEL_DEFAULT = "__auto__"
 
 
+# ── export ──────────────────────────────────────────────────────
+def cmd_export(args):
+    """Export .pt model to .onnx format for ONNX Runtime inference."""
+    boss = args.boss
+    model_name = f"boss-{boss}"
+    pt_path = os.path.join(MODELS_DIR, f"{model_name}.pt")
+
+    if not os.path.exists(pt_path):
+        print(f"Model not found: {pt_path}")
+        return
+
+    from ultralytics import YOLO
+    model = YOLO(pt_path)
+
+    print(f"Exporting {pt_path} -> ONNX (imgsz={args.imgsz})...")
+    model.export(format="onnx", imgsz=args.imgsz, opset=17, simplify=True, dynamic=False)
+
+    # ultralytics writes the .onnx next to the .pt file
+    onnx_src = os.path.join(MODELS_DIR, f"{model_name}.onnx")
+    if os.path.exists(onnx_src):
+        size_mb = os.path.getsize(onnx_src) / (1024 * 1024)
+        print(f"\nExported: {onnx_src} ({size_mb:.1f} MB)")
+    else:
+        print(f"\nWarning: expected output not found at {onnx_src}")
+
+
 # ── CLI ──────────────────────────────────────────────────────────
 def main():
     parser = argparse.ArgumentParser(
@@ -315,10 +342,10 @@ def main():
     p = sub.add_parser("train", help="Train YOLO model")
     p.add_argument("boss", help="Boss name (e.g. kulemak)")
     p.add_argument("--data", default=None, help="Path to data.yaml")
-    p.add_argument("--model", default="yolo11s", help="YOLO model variant")
+    p.add_argument("--model", default="yolo11n", help="YOLO model variant")
     p.add_argument("--epochs", type=int, default=200, help="Training epochs")
-    p.add_argument("--imgsz", type=int, default=1280, help="Image size")
-    p.add_argument("--batch", type=int, default=8, help="Batch size")
+    p.add_argument("--imgsz", type=int, default=640, help="Image size")
+    p.add_argument("--batch", type=int, default=16, help="Batch size")
     p.add_argument("--device", default="0", help="CUDA device")
     p.add_argument("--name", default=None, help="Run name (auto-increments if omitted)")
 
@@ -333,6 +360,11 @@ def main():
     p.add_argument("--model", default=_PRELABEL_MODEL_DEFAULT, help="Model name in models/ (default: boss-{boss})")
     p.add_argument("--conf", type=float, default=0.20, help="Confidence threshold")
 
+    # export
+    p = sub.add_parser("export", help="Export .pt model to ONNX format")
+    p.add_argument("boss", help="Boss name (e.g. kulemak)")
+    p.add_argument("--imgsz", type=int, default=640, help="Image size for export")
+
     args = parser.parse_args()
 
     if args.command is None:
@@ -345,6 +377,7 @@ def main():
         "train":    cmd_train,
         "runs":     cmd_runs,
         "prelabel": cmd_prelabel,
+        "export":   cmd_export,
     }
     commands[args.command](args)