2552 Fix ToNumpy issue with 0-dim data

monai/transforms/utility/array.py

@@ -364,10 +364,12 @@ def __call__(self, img) -> np.ndarray:
         Apply the transform to `img` and make it contiguous.
         """
         if isinstance(img, torch.Tensor):
-            img = img.detach().cpu().numpy()  # type: ignore
+            img = img.detach().cpu().numpy()
         elif has_cp and isinstance(img, cp_ndarray):
-            img = cp.asnumpy(img)  # type: ignore
-        return np.ascontiguousarray(img)
+            img = cp.asnumpy(img)
+
+        array: np.ndarray = np.asarray(img)
+        return np.ascontiguousarray(array) if array.ndim > 0 else array
 
 
 class ToCupy(Transform):
@@ -380,7 +382,7 @@ def __call__(self, img):
         Apply the transform to `img` and make it contiguous.
         """
         if isinstance(img, torch.Tensor):
-            img = img.detach().cpu().numpy()  # type: ignore
+            img = img.detach().cpu().numpy()
         return cp.ascontiguousarray(cp.asarray(img))
 
 

tests/test_to_numpy.py

@@ -58,6 +58,13 @@ def test_list_tuple(self):
         result = ToNumpy()(test_data)
         np.testing.assert_allclose(result, np.asarray(test_data))
 
+    def test_single_value(self):
+        for test_data in [5, np.array(5), torch.tensor(5)]:
+            result = ToNumpy()(test_data)
+            self.assertTrue(isinstance(result, np.ndarray))
+            np.testing.assert_allclose(result, np.asarray(test_data))
+            self.assertEqual(result.ndim, 0)
+
 
 if __name__ == "__main__":
     unittest.main()