Merge pull request #441 from jabooth/booleanconstrain

adds constrain_to_landmarks on BooleanImage

menpo/image/boolean.py

@@ -348,3 +348,64 @@ def _build_warped_image(self, template_mask, sampled_pixel_values,
         # more manually than other image classes.
         warped_image.pixels[warped_image.mask] = sampled_pixel_values
         return warped_image
+
+    def constrain_to_landmarks(self, group=None, label=None, trilist=None):
+        r"""
+        Restricts this mask to be equal to the convex hull around the
+        landmarks chosen.
+
+        Parameters
+        ----------
+        group : string, Optional
+            The key of the landmark set that should be used. If None,
+            and if there is only one set of landmarks, this set will be used.
+
+            Default: None
+
+        label: string, Optional
+            The label of of the landmark manager that you wish to use. If no
+            label is passed, the convex hull of all landmarks is used.
+
+            Default: None
+
+        trilist: (t, 3) ndarray, Optional
+            Triangle list to be used on the landmarked points in selecting
+            the mask region. If None defaults to performing Delaunay
+            triangulation on the points.
+
+            Default: None
+        """
+        self.constrain_to_pointcloud(self.landmarks[group][label],
+                                     trilist=trilist)
+
+    def constrain_to_pointcloud(self, pointcloud, trilist=None):
+        r"""
+        Restricts this mask to be equal to the convex hull around a point cloud
+
+        Parameters
+        ----------
+        pointcloud : :map:`PointCloud`
+            The pointcloud of points that should be constrained to
+
+        trilist: (t, 3) ndarray, Optional
+            Triangle list to be used on the points in selecting
+            the mask region. If None defaults to performing Delaunay
+            triangulation on the points.
+
+            Default: None
+        """
+        from menpo.transform.piecewiseaffine import PiecewiseAffine
+        from menpo.transform.piecewiseaffine import TriangleContainmentError
+
+        if self.n_dims != 2:
+            raise ValueError("can only constrain mask on 2D images.")
+
+        if trilist is not None:
+            from menpo.shape import TriMesh
+            pointcloud = TriMesh(pointcloud.points, trilist)
+
+        pwa = PiecewiseAffine(pointcloud, pointcloud)
+        try:
+            pwa.apply(self.indices)
+        except TriangleContainmentError as e:
+            self.from_vector_inplace(~e.points_outside_source_domain)

menpo/image/masked.py

@@ -593,7 +593,6 @@ def gradient(self, nullify_values_at_mask_boundaries=False):
         grad_image.landmarks = self.landmarks
         return grad_image
 
-    # TODO maybe we should be stricter about the trilist here, feels flakey
     def constrain_mask_to_landmarks(self, group=None, label=None,
                                     trilist=None):
         r"""
@@ -621,25 +620,8 @@ def constrain_mask_to_landmarks(self, group=None, label=None,
 
             Default: None
         """
-        from menpo.transform.piecewiseaffine import PiecewiseAffine
-        from menpo.transform.piecewiseaffine import TriangleContainmentError
-
-        if self.n_dims != 2:
-            raise ValueError("can only constrain mask on 2D images.")
-
-        pc = self.landmarks[group][label]
-        if trilist is not None:
-            from menpo.shape import TriMesh
-
-            pc = TriMesh(pc.points, trilist)
-
-        pwa = PiecewiseAffine(pc, pc)
-        try:
-            # Call the superclass indices property because we actually want
-            # ALL the indices, not just the true ones.
-            pwa.apply(Image.indices.fget(self))
-        except TriangleContainmentError as e:
-            self.mask.from_vector_inplace(~e.points_outside_source_domain)
+        self.mask.constrain_to_pointcloud(self.landmarks[group][label],
+                                          trilist=trilist)
 
     def rescale(self, scale, interpolator='scipy', round='ceil', **kwargs):
         r"""A copy of this MaskedImage, rescaled by a given factor.