mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-10 08:20:32 +08:00
Neil Yager
96 lines
3.1 KiB
Python
96 lines
3.1 KiB
Python
import numpy as np
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from scikits.image.morphology import skeletonize
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import numpy.testing
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from scikits.image.draw import draw
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from scipy.ndimage import correlate
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from scikits.image.io import imread
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from scikits.image import data_dir
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import os.path
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class TestSkeletonize():
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def test_skeletonize_no_foreground(self):
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im = np.zeros((5,5))
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result = skeletonize(im)
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numpy.testing.assert_array_equal(result, np.zeros((5,5)))
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def test_skeletonize_wrong_dim1(self):
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im = np.zeros((5))
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numpy.testing.assert_raises(ValueError, skeletonize, im)
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def test_skeletonize_wrong_dim2(self):
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im = np.zeros((5, 5, 5))
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numpy.testing.assert_raises(ValueError, skeletonize, im)
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def test_skeletonize_not_binary(self):
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im = np.zeros((5, 5))
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im[0, 0] = 1
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im[0, 1] = 2
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numpy.testing.assert_raises(ValueError, skeletonize, im)
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def test_skeletonize_unexpected_value(self):
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im = np.zeros((5, 5))
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im[0, 0] = 2
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numpy.testing.assert_raises(ValueError, skeletonize, im)
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def test_skeletonize_all_foreground(self):
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im = np.ones((3,4))
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result = skeletonize(im)
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def test_skeletonize_single_point(self):
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im = np.zeros((5, 5), np.uint8)
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im[3, 3] = 1
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result = skeletonize(im)
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numpy.testing.assert_array_equal(result, im)
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def test_skeletonize_already_thinned(self):
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im = np.zeros((5, 5), np.uint8)
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im[3,1:-1] = 1
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im[2, -1] = 1
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im[4, 0] = 1
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result = skeletonize(im)
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numpy.testing.assert_array_equal(result, im)
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def test_skeletonize_output(self):
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im = imread(os.path.join(data_dir, "bw_text.png"), as_grey=True)
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# make black the foreground
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im = (im==0)
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result = skeletonize(im)
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expected = np.load(os.path.join(data_dir, "bw_text_skeleton.npy"))
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numpy.testing.assert_array_equal(result, expected)
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def test_skeletonize_num_neighbours(self):
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# an empty image
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image = np.zeros((300, 300))
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# foreground object 1
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image[10:-10, 10:100] = 1
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image[-100:-10, 10:-10] = 1
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image[10:-10, -100:-10] = 1
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# foreground object 2
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rs, cs = draw.bresenham(250, 150, 10, 280)
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for i in range(10): image[rs+i, cs] = 1
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rs, cs = draw.bresenham(10, 150, 250, 280)
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for i in range(20): image[rs+i, cs] = 1
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# foreground object 3
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ir, ic = np.indices(image.shape)
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circle1 = (ic - 135)**2 + (ir - 150)**2 < 30**2
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circle2 = (ic - 135)**2 + (ir - 150)**2 < 20**2
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image[circle1] = 1
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image[circle2] = 0
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result = skeletonize(image)
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# there should never be a 2x2 block of foreground pixels in a skeleton
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mask = np.array([[1, 1],
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[1, 1]], np.uint8)
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blocks = correlate(result, mask, mode='constant')
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assert not numpy.any(blocks == 4)
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if __name__ == '__main__':
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np.testing.run_module_suite()
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