Revert to Python float that is out of range

In `test_overrange_tolerance_float`:
The previous test actually checked what happens if a Python float that
is out of range for the image type is used as the tolerance. Not casting
with `max_value.item()` would result in `np.float32(inf)` which is a
different test.

In `flood`:
Furthermore, we need to turn `min_value` and `max_value` into Python
scalars with `.item()` as well. Otherwise `max` and `min` seem to
trigger an overflow error during the comparison.

skimage/morphology/_flood_fill.py

@@ -276,8 +276,8 @@ def flood(image, seed_point, *, footprint=None, connectivity=None, tolerance=Non
             # Account for over- & underflow problems with seed_value ± tolerance
             # in a way that works with NumPy 1 & 2
             min_value, max_value = numeric_dtype_min_max(seed_value.dtype)
-            low_tol = max(min_value, seed_value.item() - tolerance)
-            high_tol = min(max_value, seed_value.item() + tolerance)
+            low_tol = max(min_value.item(), seed_value.item() - tolerance)
+            high_tol = min(max_value.item(), seed_value.item() + tolerance)
 
             _flood_fill_tolerance(
                 working_image.ravel(order),

skimage/morphology/tests/test_flood_fill.py

@@ -40,9 +40,7 @@ def test_overrange_tolerance_float():
     image *= max_value
 
     expected = np.ones_like(image)
-    with np.errstate(over="ignore"):
-        tolerance = max_value * 10
-    output = flood_fill(image, (0, 1), 1.0, tolerance=tolerance)
+    output = flood_fill(image, (0, 1), 1.0, tolerance=max_value.item() * 10)
 
     np.testing.assert_equal(output, expected)