add support for using transformation objects in warp function

skimage/transform/geometric.py

@@ -495,10 +495,12 @@ def warp(image, reverse_map=None, map_args={}, output_shape=None, order=1,
     ----------
     image : 2-D array
         Input image.
-    reverse_map : callable xy = f(xy, **kwargs)
-        Reverse coordinate map.  A function that transforms a Px2 array of
+    reverse_map : transformation object, callable xy = f(xy, **kwargs)
+        Reverse coordinate map. A function that transforms a Px2 array of
         ``(x, y)`` coordinates in the *output image* into their corresponding
-        coordinates in the *source image*.  Also see examples below.
+        coordinates in the *source image*. In case of a transformation object
+        its `reverse` method will be used as transformation function. Also see
+        examples below.
     map_args : dict, optional
         Keyword arguments passed to `reverse_map`.
     output_shape : tuple (rows, cols)
@@ -548,6 +550,8 @@ def warp(image, reverse_map=None, map_args={}, output_shape=None, order=1,
 
     # Map each (x, y) pair to the source image according to
     # the user-provided mapping
+    if callable(getattr(reverse_map, 'reverse', None)):
+        reverse_map = reverse_map.reverse
     tf_coords = reverse_map(tf_coords, **map_args)
 
     # Reshape back to a (2, M, N) coordinate grid

skimage/transform/tests/test_geometric.py

@@ -2,10 +2,9 @@ import numpy as np
 from numpy.testing import assert_array_almost_equal
 
 from skimage.transform.geometric import _stackcopy
-from skimage.transform import estimate_transformation, \
-    SimilarityTransformation, AffineTransformation, ProjectiveTransformation, \
-    PolynomialTransformation
-from skimage.transform import homography, fast_homography
+from skimage.transform import estimate_transformation, homography, warp, \
+    fast_homography, SimilarityTransformation, AffineTransformation, \
+    ProjectiveTransformation, PolynomialTransformation
 from skimage import transform as tf, data, img_as_float
 from skimage.color import rgb2gray
 
@@ -142,8 +141,23 @@ def test_union():
     assert_array_almost_equal(tform.rotation, rotation1 + rotation2)
 
 
+def test_warp():
+    x = np.zeros((5, 5), dtype=np.uint8)
+    x[2, 2] = 255
+    x = img_as_float(x)
+    theta = -np.pi/2
+    tform = SimilarityTransformation()
+    tform.from_params(1, theta, (0, 4))
+
+    x90 = warp(x, tform, order=1)
+    assert_array_almost_equal(x90, np.rot90(x))
+
+    x90 = warp(x, tform.reverse, order=1)
+    assert_array_almost_equal(x90, np.rot90(x))
+
+
 def test_homography():
-    x = np.zeros((5,5), dtype=np.uint8)
+    x = np.zeros((5, 5), dtype=np.uint8)
     x[1, 1] = 255
     x = img_as_float(x)
     theta = -np.pi/2