Adding kwargs to Mask.regionprops

src/tracksdata/nodes/_mask.py

@@ -373,24 +373,26 @@ def move(
         if image_shape is not None:
             self._crop_overhang(image_shape)
 
-    def regionprops(self, spacing: tuple[float, ...] | None = None) -> "RegionProperties":
+    def regionprops(self, **kwargs) -> "RegionProperties":
         """
         Compute scikit-image regionprops for this mask.
 
         The computation is aware of the mask bounding box, so coordinate-based
         properties (e.g. centroid, coords) are returned in absolute
         image coordinates.
 
+        IMPORTANT: When providing an intensity image it should match the bounding box shape, not the actual image shape.
+
         Parameters
         ----------
-        spacing : tuple[float, ...] | None
-            The spacing of the image in each dimension (scale).
+        **kwargs : dict
+            Keyword arguments to pass to regionprops.
         """
         props = regionprops(
             self._mask.astype(np.uint16),
             cache=True,
             offset=tuple(self._bbox[: self._mask.ndim]),
-            spacing=spacing,
+            **kwargs,
         )
 
         if len(props) != 1:

src/tracksdata/nodes/_test/test_mask.py

@@ -67,6 +67,17 @@ def test_mask_regionprops_empty() -> None:
         _ = Mask(mask_array, bbox).regionprops()
 
 
+def test_mask_regionprops_intensity_image() -> None:
+    """Regionprops should handle intensity images."""
+    mask_array = np.array([[False, True], [True, False]], dtype=bool)
+    bbox = np.array([0, 0, 2, 2])
+    intensity_image = np.array([[1, 2], [3, 4]])
+
+    props = Mask(mask_array, bbox).regionprops(intensity_image=intensity_image)
+    assert props.intensity_max == 3  # 4 is outside the mask
+    assert props.intensity_min == 2  # 0 is outside the mask
+
+
 def test_mask_getstate_setstate() -> None:
     """Test Mask serialization and deserialization."""
     mask_array = np.array([[True, False], [False, True]], dtype=bool)