diff --git a/tools/export_model.py b/tools/export_model.py
index 243f87f9..1607c44e 100644
--- a/tools/export_model.py
+++ b/tools/export_model.py
@@ -47,9 +47,10 @@ def get_parser():
     )
     parser.add_argument(
         "--image_size",
-        default=640,
+        nargs="+",
         type=int,
-        help="Image size for evaluation (default: 640).",
+        default=[640, 640],
+        help="Image size for evaluation (default: 640, 640).",
     )
     parser.add_argument("--batch_size", default=1, type=int, help="Batch size.")
     parser.add_argument("--opset", default=DEFAULT_OPSET, type=int, help="opset_version")
@@ -128,9 +129,10 @@ def cli_main():
     checkpoint_path = Path(args.checkpoint_path)
     assert checkpoint_path.exists(), f"Not found checkpoint file at '{checkpoint_path}'"
 
+    image_size = args.image_size * 2 if len(args.image_size) == 1 else 1  # expand
     if args.skip_preprocess:
         # input data
-        inputs = torch.rand(args.batch_size, 3, args.image_size, args.image_size)
+        inputs = torch.rand(args.batch_size, 3, *image_size)
         dynamic_axes = {
             "images_tensors": {0: "batch", 2: "height", 3: "width"},
             "boxes": {0: "batch", 1: "num_objects"},
@@ -147,7 +149,7 @@ def cli_main():
         model.eval()
     else:
         # input data
-        images = [torch.rand(3, args.image_size, args.image_size)]
+        images = [torch.rand(3, *image_size)]
         inputs = (images,)
         dynamic_axes = {
             "images_tensors": {1: "height", 2: "width"},
@@ -159,7 +161,8 @@ def cli_main():
         output_names = ["scores", "labels", "boxes"]
         model = YOLOv5.load_from_yolov5(
             checkpoint_path,
-            score_thresh=args.score_thresh,
+            size=tuple(image_size),
+            core_thresh=args.score_thresh,
             version=args.version,
         )
         model.eval()