BREAKING LandmarkGroups are now Shapes

docs/source/api/landmark/index.rst

@@ -29,9 +29,9 @@ Landmarks & Labeller
   :maxdepth: 2
 
   LandmarkManager
-  LandmarkGroup
   labeller
 
+
 Bounding Box Labels
 -------------------
 
@@ -41,6 +41,7 @@ Bounding Box Labels
   bounding_box_mirrored_to_bounding_box
   bounding_box_to_bounding_box
 
+
 Labels
 ------
 Pre-defined landmark labels that normally correspond to standard database

docs/source/api/shape/LabelledPointUndirectedGraph.rst

@@ -0,0 +1,13 @@
+.. _menpo-shape-LabelledPointUndirectedGraph:
+
+.. currentmodule:: menpo.shape
+
+LabelledPointUndirectedGraph
+============================
+.. autoclass:: LabelledPointUndirectedGraph
+  :members:
+  :inherited-members:
+  :show-inheritance:
+
+  .. automethod:: _view_2d
+  .. automethod:: _view_landmarks_2d

docs/source/api/shape/index.rst

@@ -46,6 +46,18 @@ Mix-ins of Graphs and :map:`PointCloud` for graphs with geometry.
   PointTree
 
 
+LabelledPointGraph
+------------------
+
+A subclass of :map:`PointUndirectedGraph` that allows the attaching of
+`labels` associated with semantic parts of the object.
+
+.. toctree::
+  :maxdepth: 2
+
+  LabelledPointUndirectedGraph
+
+
 Predefined Graphs
 -----------------
 

docs/source/changelog.rst

@@ -375,7 +375,7 @@ Breaking Changes
     not been deprecated due to the changes. However, the new changes mean
     that the naming scheme of labels is now much more intuitive. Practically,
     the usage of labelling has only changed in that now it is possible to label
-    not only :map:`LandmarkGroup` but also :map:`PointCloud` and numpy arrays
+    not only `LandmarkGroup` but also :map:`PointCloud` and numpy arrays
     directly.
   - Landmarks are now warped by default, where previously they were not.
   - All vlfeat features have now become optional and will not appear if

docs/xref_map.py

@@ -24,10 +24,10 @@
 'ImageBoundaryError': ('class', 'menpo.image.ImageBoundaryError'),
 'InstanceBackedModel': ('class', 'menpo.model.instancebacked.InstanceBackedModel'),
 'Invertible': ('class', 'menpo.transform.base.invertible.Invertible'),
+'LabelledPointUndirectedGraph': ('class', 'menpo.shape.LabelledPointUndirectedGraph'),
 'Landmarkable': ('class', 'menpo.landmark.Landmarkable'),
 'LandmarkableViewable': ('class', 'menpo.visualize.LandmarkableViewable'),
 'landmark_file_paths': ('function', 'menpo.io.landmark_file_paths'),
-'LandmarkGroup': ('class', 'menpo.landmark.LandmarkGroup'),
 'LandmarkManager': ('class', 'menpo.landmark.LandmarkManager'),
 'LabellingError': ('class', 'menpo.landmark.LabellingError'),
 'LazyList': ('class', 'menpo.base.LazyList'),
@@ -37,6 +37,7 @@
 'MeanInstanceLinearModel': ('class', 'menpo.model.MeanInstanceLinearModel'),
 'MeanLinearModel': ('class', 'menpo.model.linear.MeanLinearModel'),
 'MultipleAlignment': ('class', 'menpo.transform.MultipleAlignment'),
+'pickle_paths': ('function', 'menpo.io.input.base.pickle_paths'),
 'PCAModel': ('class', 'menpo.model.pca.PCAModel'),
 'PCAVectorModel': ('class', 'menpo.model.pca.PCAVectorModel'),
 'PiecewiseAffine': ('class', 'menpo.transform.PiecewiseAffine'),

menpo/feature/test/test_features.py

@@ -302,14 +302,14 @@ def test_constrain_landmarks():
     breaking_bad = breaking_bad.resize([50, 50])
     breaking_bad.constrain_mask_to_landmarks()
     hog_b = hog(breaking_bad, mode='sparse')
-    x = np.where(hog_b.landmarks['PTS'].lms.points[:, 0] > hog_b.shape[1] - 1)
-    y = np.where(hog_b.landmarks['PTS'].lms.points[:, 0] > hog_b.shape[0] - 1)
+    x = np.where(hog_b.landmarks['PTS'].points[:, 0] > hog_b.shape[1] - 1)
+    y = np.where(hog_b.landmarks['PTS'].points[:, 0] > hog_b.shape[0] - 1)
     assert_allclose(len(x[0]) + len(y[0]), 12)
     hog_b = hog(breaking_bad, mode='sparse')
-    hog_b.landmarks['PTS'] = hog_b.landmarks['PTS'].lms.constrain_to_bounds(
+    hog_b.landmarks['PTS'] = hog_b.landmarks['PTS'].constrain_to_bounds(
         hog_b.bounds())
-    x = np.where(hog_b.landmarks['PTS'].lms.points[:, 0] > hog_b.shape[1] - 1)
-    y = np.where(hog_b.landmarks['PTS'].lms.points[:, 0] > hog_b.shape[0] - 1)
+    x = np.where(hog_b.landmarks['PTS'].points[:, 0] > hog_b.shape[1] - 1)
+    y = np.where(hog_b.landmarks['PTS'].points[:, 0] > hog_b.shape[0] - 1)
     assert_allclose(len(x[0]) + len(y[0]), 0)
 
 

menpo/image/base.py

@@ -1256,7 +1256,7 @@ def crop_to_landmarks(self, group=None, boundary=0,
             Raised if ``constrain_to_boundary=False``, and an attempt is made
             to crop the image in a way that violates the image bounds.
         """
-        pc = self.landmarks[group].lms
+        pc = self.landmarks[group]
         return self.crop_to_pointcloud(
             pc, boundary=boundary, constrain_to_boundary=constrain_to_boundary,
             return_transform=return_transform)
@@ -1359,7 +1359,7 @@ def crop_to_landmarks_proportion(self, boundary_proportion,
             Raised if ``constrain_to_boundary=False``, and an attempt is made
             to crop the image in a way that violates the image bounds.
         """
-        pc = self.landmarks[group].lms
+        pc = self.landmarks[group]
         return self.crop_to_pointcloud_proportion(
             pc, boundary_proportion, minimum=minimum,
             constrain_to_boundary=constrain_to_boundary,
@@ -1493,7 +1493,7 @@ def extract_patches_around_landmarks(
         ValueError
             If image is not 2D
         """
-        return self.extract_patches(self.landmarks[group].lms,
+        return self.extract_patches(self.landmarks[group],
                                     patch_shape=patch_shape,
                                     sample_offsets=sample_offsets,
                                     as_single_array=as_single_array)
@@ -1610,7 +1610,7 @@ def set_patches_around_landmarks(self, patches, group=None,
         ValueError
             If offset does not have shape (1, 2)
         """
-        return self.set_patches(patches, self.landmarks[group].lms,
+        return self.set_patches(patches, self.landmarks[group],
                                 offset=offset, offset_index=offset_index)
 
     def warp_to_mask(self, template_mask, transform, warp_landmarks=True,
@@ -2035,7 +2035,7 @@ def rescale_to_pointcloud(self, pointcloud, group=None,
             The transform that was used. It only applies if
             `return_transform` is ``True``.
         """
-        pc = self.landmarks[group].lms
+        pc = self.landmarks[group]
         scale = AlignmentUniformScale(pc, pointcloud).as_vector().copy()
         return self.rescale(scale, round=round, order=order,
                             return_transform=return_transform)
@@ -2084,7 +2084,7 @@ def rescale_landmarks_to_diagonal_range(self, diagonal_range, group=None,
             The transform that was used. It only applies if
             `return_transform` is ``True``.
         """
-        x, y = self.landmarks[group].lms.range()
+        x, y = self.landmarks[group].range()
         scale = diagonal_range / np.sqrt(x ** 2 + y ** 2)
         return self.rescale(scale, round=round, order=order,
                             return_transform=return_transform)
@@ -2723,7 +2723,7 @@ def has_landmarks_outside_bounds(self):
         """
         if self.has_landmarks:
             for l_group in self.landmarks:
-                pc = self.landmarks[l_group].lms.points
+                pc = self.landmarks[l_group].points
                 if np.any(np.logical_or(self.shape - pc < 1, pc < 0)):
                     return True
         return False
@@ -2735,7 +2735,7 @@ def constrain_landmarks_to_bounds(self):
         method. For example:
 
             >>> im.constrain_landmarks_to_bounds()  # Equivalent to below
-            >>> im.landmarks['test'] = im.landmarks['test'].lms.constrain_to_bounds(im.bounds())
+            >>> im.landmarks['test'] = im.landmarks['test'].constrain_to_bounds(im.bounds())
         """
         warn('This method is no longer supported and will be removed in a '
              'future version of Menpo. '
@@ -2744,11 +2744,11 @@ def constrain_landmarks_to_bounds(self):
 
         for l_group in self.landmarks:
             l = self.landmarks[l_group]
-            for k in range(l.lms.points.shape[1]):
-                tmp = l.lms.points[:, k]
+            for k in range(l.points.shape[1]):
+                tmp = l.points[:, k]
                 tmp[tmp < 0] = 0
                 tmp[tmp > self.shape[k] - 1] = self.shape[k] - 1
-                l.lms.points[:, k] = tmp
+                l.points[:, k] = tmp
             self.landmarks[l_group] = l
 
     def normalize_std(self, mode='all', **kwargs):
@@ -2959,7 +2959,7 @@ def _create_patches_image(patches, patch_centers, patches_indices=None,
     r"""
     Creates an :map:`Image` object in which the patches are located on the
     correct regions based on the centers. Thus, the image is a block-sparse
-    matrix. It has also two attached :map:`LandmarkGroup` objects. The
+    matrix. It has also two attached :map:`PointCloud` objects. The
     `all_patch_centers` one contains all the patch centers, while the
     `selected_patch_centers` one contains only the centers that correspond to
     the patches that the user selected to set.

menpo/image/boolean.py

@@ -605,7 +605,7 @@ def constrain_to_landmarks(self, group=None, batch_size=None):
         constrained : :map:`BooleanImage`
             The new boolean image, constrained by the given landmark group.
         """
-        return self.constrain_to_pointcloud(self.landmarks[group].lms,
+        return self.constrain_to_pointcloud(self.landmarks[group],
                                             batch_size=batch_size)
 
     def constrain_to_pointcloud(self, pointcloud, batch_size=None,

menpo/image/masked.py

@@ -1158,7 +1158,7 @@ def constrain_mask_to_landmarks(self, group=None, batch_size=None,
         """
         copy = self.copy()
         copy.mask = copy.mask.constrain_to_pointcloud(
-            copy.landmarks[group].lms, batch_size=batch_size,
+            copy.landmarks[group], batch_size=batch_size,
             point_in_pointcloud=point_in_pointcloud)
         return copy
 
@@ -1198,7 +1198,7 @@ def constrain_mask_to_patches_around_landmarks(self, patch_shape,
         """
         copy = self.copy()
         # get the selected pointcloud
-        pc = copy.landmarks[group].lms
+        pc = copy.landmarks[group]
         # temporarily set all mask values to False
         copy.mask.pixels[:] = False
         # create a patches array of the correct size, full of True values

menpo/image/rasterize.py

@@ -236,9 +236,9 @@ def rasterize_landmarks_2d(image, group=None, render_lines=True, line_style='-',
 
     if backend in _RASTERIZE_BACKENDS:
         if isinstance(group, list):
-            landmarks = [image.landmarks[g].lms for g in group]
+            landmarks = [image.landmarks[g] for g in group]
         else:
-            landmarks = [image.landmarks[group].lms]
+            landmarks = [image.landmarks[group]]
 
         # Validate all the parameters for multiple landmark groups being
         # passed in

menpo/image/test/image_basics_test.py

@@ -144,4 +144,4 @@ def test_constrain_landmarks_to_bounds():
         warnings.simplefilter('ignore')
         im.constrain_landmarks_to_bounds()
     assert not im.has_landmarks_outside_bounds()
-    assert_allclose(im.landmarks['test'].lms.bounds(), im.bounds())
+    assert_allclose(im.landmarks['test'].bounds(), im.bounds())

menpo/image/test/image_copy_test.py

@@ -13,8 +13,8 @@ def test_image_copy():
     im_copy = im.copy()
 
     assert (not is_same_array(im.pixels, im_copy.pixels))
-    assert (not is_same_array(im_copy.landmarks['test'].lms.points,
-                              im.landmarks['test'].lms.points))
+    assert (not is_same_array(im_copy.landmarks['test'].points,
+                              im.landmarks['test'].points))
 
 
 def test_booleanimage_copy():
@@ -25,8 +25,8 @@ def test_booleanimage_copy():
     im_copy = im.copy()
 
     assert (not is_same_array(im.pixels, im_copy.pixels))
-    assert (not is_same_array(im_copy.landmarks['test'].lms.points,
-                              im.landmarks['test'].lms.points))
+    assert (not is_same_array(im_copy.landmarks['test'].points,
+                              im.landmarks['test'].points))
 
 
 def test_maskedimage_copy():
@@ -37,5 +37,5 @@ def test_maskedimage_copy():
     im_copy = im.copy()
 
     assert (not is_same_array(im.pixels, im_copy.pixels))
-    assert (not is_same_array(im_copy.landmarks['test'].lms.points,
-                              im.landmarks['test'].lms.points))
+    assert (not is_same_array(im_copy.landmarks['test'].points,
+                              im.landmarks['test'].points))

menpo/image/test/image_patches_test.py

@@ -14,7 +14,7 @@
 def test_double_type():
     image = mio.import_builtin_asset('breakingbad.jpg')
     patch_shape = (16, 16)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     patch_shape=patch_shape,
                                     as_single_array=False)
     assert(patches[0].pixels.dtype == np.float64)
@@ -24,7 +24,7 @@ def test_float_type():
     image = mio.import_builtin_asset('breakingbad.jpg')
     image.pixels = image.pixels.astype(np.float32)
     patch_shape = (16, 16)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     patch_shape=patch_shape,
                                     as_single_array=False)
     assert(patches[0].pixels.dtype == np.float32)
@@ -33,7 +33,7 @@ def test_float_type():
 def test_uint8_type():
     image = mio.import_builtin_asset('breakingbad.jpg', normalize=False)
     patch_shape = (16, 16)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     patch_shape=patch_shape,
                                     as_single_array=False)
     assert(patches[0].pixels.dtype == np.uint8)
@@ -62,7 +62,7 @@ def test_int_pointcloud():
 def test_uint8_type_single_array():
     image = mio.import_builtin_asset('breakingbad.jpg', normalize=False)
     patch_shape = (16, 16)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     patch_shape=patch_shape,
                                     as_single_array=True)
     assert(patches.dtype == np.uint8)
@@ -71,7 +71,7 @@ def test_uint8_type_single_array():
 def test_squared_even_patches():
     image = mio.import_builtin_asset('breakingbad.jpg')
     patch_shape = (16, 16)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     patch_shape=patch_shape,
                                     as_single_array=False)
     assert_equals(len(patches), 68)
@@ -80,7 +80,7 @@ def test_squared_even_patches():
 def test_squared_odd_patches():
     image = mio.import_builtin_asset('breakingbad.jpg')
     patch_shape = (15, 15)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     patch_shape=patch_shape,
                                     as_single_array=False)
     assert_equals(len(patches), 68)
@@ -89,7 +89,7 @@ def test_squared_odd_patches():
 def test_nonsquared_even_patches():
     image = mio.import_builtin_asset('breakingbad.jpg')
     patch_shape = (16, 18)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     patch_shape=patch_shape,
                                     as_single_array=False)
     assert_equals(len(patches), 68)
@@ -98,7 +98,7 @@ def test_nonsquared_even_patches():
 def test_nonsquared_odd_patches():
     image = mio.import_builtin_asset('breakingbad.jpg')
     patch_shape = (15, 17)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     patch_shape=patch_shape,
                                     as_single_array=False)
     assert_equals(len(patches), 68)
@@ -107,7 +107,7 @@ def test_nonsquared_odd_patches():
 def test_nonsquared_even_odd_patches():
     image = mio.import_builtin_asset('breakingbad.jpg')
     patch_shape = (15, 16)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     patch_shape=patch_shape,
                                     as_single_array=False)
     assert_equals(len(patches), 68)
@@ -125,7 +125,7 @@ def test_squared_even_patches_landmarks():
 def test_squared_even_patches_single_array():
     image = mio.import_builtin_asset('breakingbad.jpg')
     patch_shape = (16, 16)
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     as_single_array=True,
                                     patch_shape=patch_shape)
     assert_equals(patches.shape, ((68, 1, 3) + patch_shape))
@@ -134,7 +134,7 @@ def test_squared_even_patches_single_array():
 def test_squared_even_patches_sample_offsets():
     image = mio.import_builtin_asset('breakingbad.jpg')
     sample_offsets = np.array([[0, 0], [1, 0]])
-    patches = image.extract_patches(image.landmarks['PTS'].lms,
+    patches = image.extract_patches(image.landmarks['PTS'],
                                     sample_offsets=sample_offsets,
                                     as_single_array=False)
     assert_equals(len(patches), 136)
@@ -225,9 +225,9 @@ def test_create_patches_image():
     image = mio.import_builtin_asset.lenna_png()
     patches = image.extract_patches_around_landmarks(
         patch_shape=patch_shape, as_single_array=True)
-    pc = image.landmarks['LJSON'].lms
+    pc = image.landmarks['LJSON']
     patches_image = _create_patches_image(patches, pc, patches_indices=range(17))
     assert(patches_image.n_channels == patches.shape[2])
     assert(patches_image.landmarks.n_groups == 2)
-    assert(patches_image.landmarks['selected_patch_centers'].lms.n_points == 17)
-    assert(patches_image.landmarks['all_patch_centers'].lms.n_points == 68)
+    assert(patches_image.landmarks['selected_patch_centers'].n_points == 17)
+    assert(patches_image.landmarks['all_patch_centers'].n_points == 68)