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Merge pull request #1051 from ahojnnes/bicubic-interp

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Bicubic interpolation fix and reference
This commit is contained in:
Stefan van der Walt
2014-12-15 23:15:13 +02:00
parent ea95835017 00c3a978aa
commit a2a8696ee9
3 changed files with 97 additions and 111 deletions
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skimage/transform/_geometric.py
+12 -1
View File
@@ -1134,7 +1134,18 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
out = None
if order in range(4) and not map_args:
if order == 2:
# When fixing this issue, make sure to fix the branches further
# below in this function
warnings.warn("Bi-quadratic interpolation behavior has changed due "
"to a bug in the implementation of scikit-image. "
"The new version now serves as a wrapper "
"around SciPy's interpolation functions, which itself "
"is not verified to be a correct implementation. Until "
"skimage's implementation is fixed, we recommend "
"to use bi-linear or bi-cubic interpolation instead.")
if order in (0, 1, 3) and not map_args:
# use fast Cython version for specific interpolation orders and input
matrix = None
skimage/transform/tests/test_warps.py
+19 -54
View File
@@ -1,4 +1,4 @@
from numpy.testing import (assert_array_almost_equal, run_module_suite,
from numpy.testing import (assert_almost_equal, run_module_suite,
assert_array_equal, assert_raises)
import numpy as np
from scipy.ndimage import map_coordinates
@@ -22,10 +22,10 @@ def test_warp_tform():
tform = SimilarityTransform(scale=1, rotation=theta, translation=(0, 4))
x90 = warp(x, tform, order=1)
assert_array_almost_equal(x90, np.rot90(x))
assert_almost_equal(x90, np.rot90(x))
x90 = warp(x, tform.inverse, order=1)
assert_array_almost_equal(x90, np.rot90(x))
assert_almost_equal(x90, np.rot90(x))
def test_warp_callable():
@@ -37,7 +37,7 @@ def test_warp_callable():
shift = lambda xy: xy + 1
outx = warp(x, shift, order=1)
assert_array_almost_equal(outx, refx)
assert_almost_equal(outx, refx)
def test_warp_matrix():
@@ -50,7 +50,7 @@ def test_warp_matrix():
# _warp_fast
outx = warp(x, matrix, order=1)
assert_array_almost_equal(outx, refx)
assert_almost_equal(outx, refx)
# check for ndimage.map_coordinates
outx = warp(x, matrix, order=5)
@@ -71,7 +71,7 @@ def test_warp_nd():
outx = warp(x, coords, order=0, cval=0)
assert_array_almost_equal(outx, refx)
assert_almost_equal(outx, refx)
def test_warp_clip():
@@ -79,10 +79,10 @@ def test_warp_clip():
matrix = np.eye(3)
outx = warp(x, matrix, order=0, clip=False)
assert_array_almost_equal(x, outx)
assert_almost_equal(x, outx)
outx = warp(x, matrix, order=0, clip=True)
assert_array_almost_equal(x / 2, outx)
assert_almost_equal(x / 2, outx)
def test_homography():
@@ -96,49 +96,14 @@ def test_homography():
x90 = warp(x,
inverse_map=ProjectiveTransform(M).inverse,
order=1)
assert_array_almost_equal(x90, np.rot90(x))
def test_fast_homography():
img = rgb2gray(data.astronaut()).astype(np.uint8)
img = img[:, :100]
theta = np.deg2rad(30)
scale = 0.5
tx, ty = 50, 50
H = np.eye(3)
S = scale * np.sin(theta)
C = scale * np.cos(theta)
H[:2, :2] = [[C, -S], [S, C]]
H[:2, 2] = [tx, ty]
tform = ProjectiveTransform(H)
coords = warp_coords(tform.inverse, (img.shape[0], img.shape[1]))
for order in range(4):
for mode in ('constant', 'reflect', 'wrap', 'nearest'):
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)
# ax0.imshow(img)
# ax1.imshow(p0, cmap=plt.cm.gray)
# ax2.imshow(p1, cmap=plt.cm.gray)
# ax3.imshow(np.abs(p0 - p1), cmap=plt.cm.gray)
# plt.show()
d = np.mean(np.abs(p0 - p1))
assert d < 0.001
assert_almost_equal(x90, np.rot90(x))
def test_rotate():
x = np.zeros((5, 5), dtype=np.double)
x[1, 1] = 1
x90 = rotate(x, 90)
assert_array_almost_equal(x90, np.rot90(x))
assert_almost_equal(x90, np.rot90(x))
def test_rotate_resize():
@@ -158,9 +123,9 @@ def test_rotate_center():
refx = np.zeros((10, 10), dtype=np.double)
refx[2, 5] = 1
x20 = rotate(x, 20, order=0, center=(0, 0))
assert_array_almost_equal(x20, refx)
assert_almost_equal(x20, refx)
x0 = rotate(x20, -20, order=0, center=(0, 0))
assert_array_almost_equal(x0, x)
assert_almost_equal(x0, x)
def test_rescale():
@@ -170,7 +135,7 @@ def test_rescale():
scaled = rescale(x, 2, order=0)
ref = np.zeros((10, 10))
ref[2:4, 2:4] = 1
assert_array_almost_equal(scaled, ref)
assert_almost_equal(scaled, ref)
# different scale factors
x = np.zeros((5, 5), dtype=np.double)
@@ -178,7 +143,7 @@ def test_rescale():
scaled = rescale(x, (2, 1), order=0)
ref = np.zeros((10, 5))
ref[2:4, 1] = 1
assert_array_almost_equal(scaled, ref)
assert_almost_equal(scaled, ref)
def test_resize2d():
@@ -187,7 +152,7 @@ def test_resize2d():
resized = resize(x, (10, 10), order=0)
ref = np.zeros((10, 10))
ref[2:4, 2:4] = 1
assert_array_almost_equal(resized, ref)
assert_almost_equal(resized, ref)
def test_resize3d_keep():
@@ -197,9 +162,9 @@ def test_resize3d_keep():
resized = resize(x, (10, 10), order=0)
ref = np.zeros((10, 10, 3))
ref[2:4, 2:4, :] = 1
assert_array_almost_equal(resized, ref)
assert_almost_equal(resized, ref)
resized = resize(x, (10, 10, 3), order=0)
assert_array_almost_equal(resized, ref)
assert_almost_equal(resized, ref)
def test_resize3d_resize():
@@ -209,7 +174,7 @@ def test_resize3d_resize():
resized = resize(x, (10, 10, 1), order=0)
ref = np.zeros((10, 10, 1))
ref[2:4, 2:4] = 1
assert_array_almost_equal(resized, ref)
assert_almost_equal(resized, ref)
def test_resize3d_bilinear():
@@ -223,7 +188,7 @@ def test_resize3d_bilinear():
ref[1:5, 2:4, :] = 0.09375
ref[2:4, 1:5, :] = 0.09375
ref[2:4, 2:4, :] = 0.28125
assert_array_almost_equal(resized, ref)
assert_almost_equal(resized, ref)
def test_swirl():