Files
scikit-image/skimage/transform/tests/test_warps.py
T

80 lines
2.2 KiB
Python

from numpy.testing import assert_array_almost_equal, run_module_suite
import numpy as np
from skimage.transform import (warp, homography, fast_homography,
SimilarityTransform)
from skimage import transform as tf, data, img_as_float
from skimage.color import rgb2gray
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 = SimilarityTransform(scale=1, rotation=theta, translation=(0, 4))
x90 = warp(x, tform, order=1)
assert_array_almost_equal(x90, np.rot90(x))
x90 = warp(x, tform.inverse, order=1)
assert_array_almost_equal(x90, np.rot90(x))
def test_homography():
x = np.zeros((5, 5), dtype=np.uint8)
x[1, 1] = 255
x = img_as_float(x)
theta = -np.pi/2
M = np.array([[np.cos(theta),-np.sin(theta),0],
[np.sin(theta), np.cos(theta),4],
[0, 0, 1]])
x90 = homography(x, M, order=1)
assert_array_almost_equal(x90, np.rot90(x))
def test_fast_homography():
img = rgb2gray(data.lena()).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]
for mode in ('constant', 'mirror', 'wrap'):
p0 = homography(img, H, mode=mode, order=1)
p1 = fast_homography(img, H, mode=mode)
p1 = np.round(p1)
## 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 < 0.2
def test_swirl():
image = img_as_float(data.checkerboard())
swirl_params = {'radius': 80, 'rotation': 0, 'order': 2, 'mode': 'reflect'}
swirled = tf.swirl(image, strength=10, **swirl_params)
unswirled = tf.swirl(swirled, strength=-10, **swirl_params)
assert np.mean(np.abs(image - unswirled)) < 0.01
if __name__ == "__main__":
run_module_suite()