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Johannes Schönberger
2014-09-18 20:22:35 -04:00
parent da36750d55
commit 6ff1bf26ee
1 changed files with 12 additions and 10 deletions
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skimage/transform/_geometric.py
+12 -10
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@@ -1124,24 +1124,24 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
out = None
# use fast Cython version for specific interpolation orders and input
if order in range(4) and not map_args:
# use fast Cython version for specific interpolation orders and input
matrix = None
# inverse_map is a transformation matrix as numpy array
if isinstance(inverse_map, np.ndarray) and inverse_map.shape == (3, 3):
# inverse_map is a transformation matrix as numpy array
matrix = inverse_map
# inverse_map is a homography
elif isinstance(inverse_map, HOMOGRAPHY_TRANSFORMS):
# inverse_map is a homography
matrix = inverse_map.params
# inverse_map is the inverse of a homography
elif (hasattr(inverse_map, '__name__')
and inverse_map.__name__ == 'inverse'
and get_bound_method_class(inverse_map) \
in HOMOGRAPHY_TRANSFORMS):
# inverse_map is the inverse of a homography
matrix = np.linalg.inv(six.get_method_self(inverse_map).params)
if matrix is not None:
@@ -1158,11 +1158,13 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
order=order, mode=mode, cval=cval))
out = np.dstack(dims)
if out is None: # use ndimage.map_coordinates
# inverse_map is a transformation matrix as numpy array,
# this is only used for order >= 4.
if out is None:
# use ndimage.map_coordinates
if (isinstance(inverse_map, np.ndarray)
and inverse_map.shape == (3, 3)):
# inverse_map is a transformation matrix as numpy array,
# this is only used for order >= 4.
inverse_map = ProjectiveTransform(matrix=inverse_map)
if isinstance(inverse_map, np.ndarray):
@@ -1181,10 +1183,10 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
def coord_map(*args):
return inverse_map(*args, **map_args)
# Input image is 2D and has color channel, but output_shape is
# given for 2-D images. Automatically add the color channel
# dimensionality.
if len(input_shape) == 3 and len(output_shape) == 2:
# Input image is 2D and has color channel, but output_shape is
# given for 2-D images. Automatically add the color channel
# dimensionality.
output_shape = (output_shape[0], output_shape[1],
input_shape[2])