Test find_objects with some input data

Try testing `find_objects` with some input data that includes labels
within a chunk, labels that span across chunks, and labels that are not
present. Compare the results of the dask-image function to that of the
SciPy function to ensure they match.

tests/test_dask_image/test_ndmeasure/test_core.py

@@ -185,6 +185,31 @@ def test_extrema(shape, chunks, has_lbls, ind):
         assert np.allclose(a_r_i, np.array(d_r[i]), equal_nan=True)
 
 
+@pytest.mark.parametrize(
+    "max_labels", [0, 1, 2, 12, 13]
+)
+def test_find_objects(max_labels):
+    np.random.seed(128)
+
+    shape = (10, 11)
+    thrd = 0.5
+    a = (np.random.random(shape) < thrd)
+    l = spnd.label(a)[0]                   # noqa: E741
+    d_l = da.from_array(l, chunks=(5, 5))
+
+    if max_labels == 0:
+        with pytest.raises(NotImplementedError):
+            dask_image.ndmeasure.find_objects(d_l, max_labels)
+    else:
+        r = spnd.find_objects(l, max_labels)
+        d_r = dask_image.ndmeasure.find_objects(d_l, max_labels)
+
+        assert len(r) == len(d_r)
+
+        for i in irange(len(r)):
+            assert r[i] == d_r[i].compute()
+
+
 @pytest.mark.parametrize(
     "shape, chunks, has_lbls, ind", [
         ((15, 16), (4, 5), False, None),