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Refactor image warps

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* Fix cval bug in interpolation which was ignored
* Remove fast_homography as standalone function and automatically include
  functionality in warp
* Fix bug in warp_coords for graylevel images
* move warp functions to warp file
This commit is contained in:
Johannes Schönberger
2012-08-27 13:31:33 +02:00
parent 77f1e0ba47
commit a6532a8dae
7 changed files with 245 additions and 214 deletions
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skimage/transform/tests/test_warps.py
+9 -7
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@@ -2,7 +2,7 @@ from numpy.testing import assert_array_almost_equal, run_module_suite
import numpy as np
from scipy.ndimage import map_coordinates
from skimage.transform import (warp, warp_coords, fast_homography,
from skimage.transform import (warp, warp_coords,
AffineTransform,
ProjectiveTransform,
SimilarityTransform)
@@ -55,11 +55,12 @@ def test_fast_homography():
H[:2, 2] = [tx, ty]
tform = ProjectiveTransform(H)
coords = warp_coords(tform.inverse, (img.shape[0], img.shape[1]))
for order in range(2):
for mode in ('constant', 'mirror', 'wrap'):
p0 = warp(img, tform.inverse, mode=mode, order=order)
p1 = fast_homography(img, H, mode=mode, order=order)
for mode in ('constant', 'reflect', 'wrap'):
p0 = map_coordinates(img, coords, mode=mode, order=order)
p1 = warp(img, tform, mode=mode, order=order)
# import matplotlib.pyplot as plt
# f, (ax0, ax1, ax2, ax3) = plt.subplots(1, 4)
@@ -85,8 +86,9 @@ def test_swirl():
def test_const_cval_out_of_range():
img = np.random.randn(100, 100)
warped = warp(img, AffineTransform(translation=(10, 10)), cval=-10)
assert np.sum(warped < 0) == (2 * 100 * 10 - 10 * 10)
cval = - 10
warped = warp(img, AffineTransform(translation=(10, 10)), cval=cval)
assert np.sum(warped == cval) == (2 * 100 * 10 - 10 * 10)
def test_warp_identity():
@@ -107,7 +109,7 @@ def test_warp_coords_example():
image = data.lena().astype(np.float32)
assert 3 == image.shape[2]
tform = SimilarityTransform(translation=(0, -10))
coords = warp_coords(30, 30, 3, tform)
coords = warp_coords(tform, (30, 30, 3))
warped_image1 = map_coordinates(image[:, :, 0], coords[:2])