Fix peak finding for empty images when indices=True

Tony Tung · Tony Tung · commit fee6d140bf83 · 2019-10-21T11:32:01.000-07:00
scikit-image#3984 adds an optimization where a flat image immediately returns. However, it returns an array where the shape is incorrectly set to always be 2D when indices=True. A test is added to catch this scenario, and a fix is introduced where we set the output array's shape based on the input array's shape.
diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
@@ -165,7 +165,7 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
     # no peak for a trivial image
     if np.all(image == image.flat[0]):
         if indices is True:
-            return np.empty((0, 2), np.int)
+            return np.empty((0, image.ndim), np.int)
         else:
             return out
 
diff --git a/skimage/feature/tests/test_peak.py b/skimage/feature/tests/test_peak.py
@@ -228,6 +228,15 @@ def test_empty(self):
                                      indices=False, exclude_border=False)
         assert np.all(~ result)
 
+    def test_empty_non2d_indices(self):
+        image = np.zeros((10, 10, 10))
+        result = peak.peak_local_max(image,
+                                     footprint=np.ones((3, 3), bool),
+                                     min_distance=1, threshold_rel=0,
+                                     indices=True, exclude_border=False)
+        assert result.shape[0] == 0
+        assert result.shape[1] == image.ndim
+
     def test_one_point(self):
         image = np.zeros((10, 20))
         labels = np.zeros((10, 20), int)
