diff --git a/mmseg/datasets/transforms/formatting.py b/mmseg/datasets/transforms/formatting.py
index 57cda9b10..46171d64f 100644
--- a/mmseg/datasets/transforms/formatting.py
+++ b/mmseg/datasets/transforms/formatting.py
@@ -74,12 +74,12 @@ class PackSegInputs(BaseTransform):
 
         data_sample = SegDataSample()
         if 'gt_seg_map' in results:
-            if results['gt_seg_map'].shape == 2:
+            if len(results['gt_seg_map'].shape) == 2:
                 data = to_tensor(results['gt_seg_map'][None,
                                                        ...].astype(np.int64))
             else:
                 warnings.warn('Please pay attention your ground truth '
-                              'segmentation map, usually the segentation '
+                              'segmentation map, usually the segmentation '
                               'map is 2D, but got '
                               f'{results["gt_seg_map"].shape}')
                 data = to_tensor(results['gt_seg_map'].astype(np.int64))
diff --git a/tests/test_datasets/test_formatting.py b/tests/test_datasets/test_formatting.py
index 51fd90d04..d0e5820ec 100644
--- a/tests/test_datasets/test_formatting.py
+++ b/tests/test_datasets/test_formatting.py
@@ -4,6 +4,7 @@ import os.path as osp
 import unittest
 
 import numpy as np
+import pytest
 from mmengine.structures import BaseDataElement
 
 from mmseg.datasets.transforms import PackSegInputs
@@ -46,8 +47,11 @@ class TestPackSegInputs(unittest.TestCase):
         self.assertEqual(results['data_samples'].ori_shape,
                          results['data_samples'].gt_sem_seg.shape)
         results = copy.deepcopy(self.results)
+        # test dataset shape is not 2D
         results['gt_seg_map'] = np.random.rand(3, 300, 400)
-        results = transform(results)
+        msg = 'the segmentation map is 2D'
+        with pytest.warns(UserWarning, match=msg):
+            results = transform(results)
         self.assertEqual(results['data_samples'].ori_shape,
                          results['data_samples'].gt_sem_seg.shape)