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https://github.com/wassname/scikit-image.git
synced 2026-08-12 12:30:16 +08:00
Refactor geometric transforms.
This commit is contained in:
Stefan van der Walt
@@ -1,12 +1,10 @@
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import numpy as np
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from numpy.testing import assert_array_almost_equal
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from skimage.transform.geometric import _stackcopy
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from skimage.transform import estimate_transformation, homography, warp, \
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fast_homography, SimilarityTransformation, AffineTransformation, \
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ProjectiveTransformation, PolynomialTransformation
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from skimage import transform as tf, data, img_as_float
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from skimage.color import rgb2gray
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from skimage.transform._geometric import _stackcopy
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from skimage.transform import (estimate_transform, SimilarityTransform,
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AffineTransform, ProjectiveTransform,
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PolynomialTransform)
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SRC = np.array([
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@@ -42,171 +40,50 @@ def test_stackcopy():
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def test_similarity_estimation():
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#: exact solution
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tform = estimate_transformation('similarity', SRC[:2, :], DST[:2, :])
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assert_array_almost_equal(tform.forward(SRC[:2, :]), DST[:2, :])
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assert_array_almost_equal(tform.reverse(tform.forward(SRC)), SRC)
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tform = estimate_transform('similarity', SRC[:2, :], DST[:2, :])
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assert_array_almost_equal(tform(SRC[:2, :]), DST[:2, :])
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assert_array_almost_equal(tform.inverse(tform(SRC)), SRC)
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#: over-determined
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tform = estimate_transformation('similarity', SRC, DST)
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ref = np.array(
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[[2.3632898110e+02, -5.5876792257e+00, 2.5331569391e+03],
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[5.5876792257e+00, 2.3632898110e+02, 2.4358232635e+03],
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[0.0000000000e+00, 0.0000000000e+00, 1.0000000000e+00]])
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assert_array_almost_equal(tform.matrix, ref)
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assert_array_almost_equal(tform.reverse(tform.forward(SRC)), SRC)
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tform = estimate_transform('similarity', SRC, DST)
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assert_array_almost_equal(tform.inverse(tform(SRC)), SRC)
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def test_similarity_explicit():
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tform = SimilarityTransformation()
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scale = 0.1
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rotation = 1
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translation = (1, 1)
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tform.from_params(scale, rotation, translation)
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assert_array_almost_equal(tform.scale, scale)
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assert_array_almost_equal(tform.rotation, rotation)
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assert_array_almost_equal(tform.translation, translation)
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def test_affine_estimation():
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#: exact solution
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tform = estimate_transformation('affine', SRC[:3, :], DST[:3, :])
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assert_array_almost_equal(tform.forward(SRC[:3, :]), DST[:3, :])
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assert_array_almost_equal(tform.reverse(tform.forward(SRC)), SRC)
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tform = estimate_transform('affine', SRC[:3, :], DST[:3, :])
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assert_array_almost_equal(tform(SRC[:3, :]), DST[:3, :])
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assert_array_almost_equal(tform.inverse(tform(SRC)), SRC)
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#: over-determined
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tform = estimate_transformation('affine', SRC, DST)
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ref = np.array(
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[[2.2573930047e+02, 7.1588596765e+00, 2.5126622012e+03],
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[2.1234856855e+01, 2.4931019555e+02, 2.4143862183e+03],
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[0.0000000000e+00, 0.0000000000e+00, 1.0000000000e+00]])
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assert_array_almost_equal(tform.matrix, ref)
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assert_array_almost_equal(tform.reverse(tform.forward(SRC)), SRC)
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def test_affine_explicit():
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tform = AffineTransformation()
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scale = (0.1, 0.13)
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rotation = 1
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shear = 0.1
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translation = (1, 1)
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tform.from_params(scale, rotation, shear, translation)
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assert_array_almost_equal(tform.scale, scale)
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assert_array_almost_equal(tform.rotation, rotation)
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assert_array_almost_equal(tform.shear, shear)
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assert_array_almost_equal(tform.translation, translation)
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tform = estimate_transform('affine', SRC, DST)
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assert_array_almost_equal(tform.inverse(tform(SRC)), SRC)
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def test_projective():
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#: exact solution
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tform = estimate_transformation('projective', SRC[:4, :], DST[:4, :])
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ref = np.array(
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[[ 1.9466901291e+02, -1.1888183994e+01, 2.2832379309e+03],
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[ -8.6910077540e+00, 2.2162069773e+02, 2.2211673699e+03],
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[ -1.2695966735e-02, -9.6053624285e-03, 1.0000000000e+00]])
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assert_array_almost_equal(tform.matrix, ref, 6)
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assert_array_almost_equal(tform.reverse(tform.forward(SRC)), SRC)
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tform = estimate_transform('projective', SRC[:4, :], DST[:4, :])
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assert_array_almost_equal(tform.inverse(tform(SRC)), SRC)
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#: over-determined
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tform = estimate_transformation('projective', SRC[:4, :], DST[:4, :])
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ref = np.array(
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[[ 1.9466901291e+02, -1.1888183994e+01, 2.2832379309e+03],
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[ -8.6910077540e+00, 2.2162069773e+02, 2.2211673699e+03],
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[ -1.2695966735e-02, -9.6053624285e-03, 1.0000000000e+00]])
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assert_array_almost_equal(tform.matrix, ref, 6)
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assert_array_almost_equal(tform.reverse(tform.forward(SRC)), SRC)
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tform = estimate_transform('projective', SRC[:4, :], DST[:4, :])
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assert_array_almost_equal(tform.inverse(tform(SRC)), SRC)
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def test_polynomial():
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tform = estimate_transformation('polynomial', SRC, DST, order=10)
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assert_array_almost_equal(tform.forward(SRC), DST, 6)
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tform = estimate_transform('polynomial', SRC, DST, order=10)
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assert_array_almost_equal(tform(SRC), DST, 6)
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def test_union():
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tform1 = SimilarityTransformation()
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scale1 = 0.1
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rotation1 = 1
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translation1 = (0, 0)
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tform1.from_params(scale1, rotation1, translation1)
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tform2 = SimilarityTransformation()
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scale2 = 0.1
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rotation2 = 1
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translation2 = (0, 0)
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tform2.from_params(scale2, rotation2, translation2)
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tform1 = SimilarityTransform(1, 0.3)
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tform2 = SimilarityTransform(1, 0.6)
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tform3 = SimilarityTransform(1, 0.9)
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tform = tform1 + tform2
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assert_array_almost_equal(tform.scale, scale1 * scale2)
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assert_array_almost_equal(tform.rotation, rotation1 + rotation2)
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def test_warp():
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x = np.zeros((5, 5), dtype=np.uint8)
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x[2, 2] = 255
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x = img_as_float(x)
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theta = -np.pi/2
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tform = SimilarityTransformation()
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tform.from_params(1, theta, (0, 4))
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x90 = warp(x, tform, order=1)
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assert_array_almost_equal(x90, np.rot90(x))
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x90 = warp(x, tform.reverse, order=1)
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assert_array_almost_equal(x90, np.rot90(x))
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def test_homography():
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x = np.zeros((5, 5), dtype=np.uint8)
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x[1, 1] = 255
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x = img_as_float(x)
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theta = -np.pi/2
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M = np.array([[np.cos(theta),-np.sin(theta),0],
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[np.sin(theta), np.cos(theta),4],
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[0, 0, 1]])
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x90 = homography(x, M, order=1)
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assert_array_almost_equal(x90, np.rot90(x))
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def test_fast_homography():
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img = rgb2gray(data.lena()).astype(np.uint8)
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img = img[:, :100]
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theta = np.deg2rad(30)
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scale = 0.5
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tx, ty = 50, 50
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H = np.eye(3)
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S = scale * np.sin(theta)
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C = scale * np.cos(theta)
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H[:2, :2] = [[C, -S], [S, C]]
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H[:2, 2] = [tx, ty]
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for mode in ('constant', 'mirror', 'wrap'):
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p0 = homography(img, H, mode=mode, order=1)
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p1 = fast_homography(img, H, mode=mode)
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p1 = np.round(p1)
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## import matplotlib.pyplot as plt
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## f, (ax0, ax1, ax2, ax3) = plt.subplots(1, 4)
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## ax0.imshow(img)
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## ax1.imshow(p0, cmap=plt.cm.gray)
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## ax2.imshow(p1, cmap=plt.cm.gray)
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## ax3.imshow(np.abs(p0 - p1), cmap=plt.cm.gray)
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## plt.show()
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d = np.mean(np.abs(p0 - p1))
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assert d < 0.2
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def test_swirl():
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image = img_as_float(data.checkerboard())
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swirl_params = {'radius': 80, 'rotation': 0, 'order': 2, 'mode': 'reflect'}
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swirled = tf.swirl(image, strength=10, **swirl_params)
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unswirled = tf.swirl(swirled, strength=-10, **swirl_params)
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assert np.mean(np.abs(image - unswirled)) < 0.01
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assert_array_almost_equal(tform._matrix, tform3._matrix)
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if __name__ == "__main__":
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@@ -0,0 +1,79 @@
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from numpy.testing import assert_array_almost_equal, run_module_suite
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import numpy as np
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from skimage.transform import (warp, homography, fast_homography,
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SimilarityTransform)
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from skimage import transform as tf, data, img_as_float
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from skimage.color import rgb2gray
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def test_warp():
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x = np.zeros((5, 5), dtype=np.uint8)
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x[2, 2] = 255
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x = img_as_float(x)
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theta = -np.pi/2
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tform = SimilarityTransform(1, theta, (0, 4))
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x90 = warp(x, tform, order=1)
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assert_array_almost_equal(x90, np.rot90(x))
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x90 = warp(x, tform.inverse, order=1)
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assert_array_almost_equal(x90, np.rot90(x))
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def test_homography():
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x = np.zeros((5, 5), dtype=np.uint8)
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x[1, 1] = 255
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x = img_as_float(x)
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theta = -np.pi/2
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M = np.array([[np.cos(theta),-np.sin(theta),0],
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[np.sin(theta), np.cos(theta),4],
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[0, 0, 1]])
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x90 = homography(x, M, order=1)
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assert_array_almost_equal(x90, np.rot90(x))
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def test_fast_homography():
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img = rgb2gray(data.lena()).astype(np.uint8)
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img = img[:, :100]
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theta = np.deg2rad(30)
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scale = 0.5
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tx, ty = 50, 50
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H = np.eye(3)
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S = scale * np.sin(theta)
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C = scale * np.cos(theta)
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H[:2, :2] = [[C, -S], [S, C]]
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H[:2, 2] = [tx, ty]
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for mode in ('constant', 'mirror', 'wrap'):
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p0 = homography(img, H, mode=mode, order=1)
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p1 = fast_homography(img, H, mode=mode)
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p1 = np.round(p1)
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## import matplotlib.pyplot as plt
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## f, (ax0, ax1, ax2, ax3) = plt.subplots(1, 4)
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## ax0.imshow(img)
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## ax1.imshow(p0, cmap=plt.cm.gray)
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## ax2.imshow(p1, cmap=plt.cm.gray)
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## ax3.imshow(np.abs(p0 - p1), cmap=plt.cm.gray)
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## plt.show()
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d = np.mean(np.abs(p0 - p1))
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assert d < 0.2
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def test_swirl():
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image = img_as_float(data.checkerboard())
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swirl_params = {'radius': 80, 'rotation': 0, 'order': 2, 'mode': 'reflect'}
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swirled = tf.swirl(image, strength=10, **swirl_params)
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unswirled = tf.swirl(swirled, strength=-10, **swirl_params)
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assert np.mean(np.abs(image - unswirled)) < 0.01
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if __name__ == "__main__":
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run_module_suite()
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