mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-29 09:06:25 +08:00
Neil Yager
145 lines
6.2 KiB
Python
145 lines
6.2 KiB
Python
import numpy as np
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from skimage.feature import greycomatrix, greycoprops
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class TestGLCM():
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def setup(self):
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self.image = np.array([[0, 0, 1, 1],
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[0, 0, 1, 1],
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[0, 2, 2, 2],
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[2, 2, 3, 3]], dtype=np.uint8)
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def test_output_angles(self):
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result = greycomatrix(self.image, [1], [0, np.pi / 2], 4)
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assert result.shape == (4, 4, 1, 2)
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expected1 = np.array([[2, 2, 1, 0],
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[0, 2, 0, 0],
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[0, 0, 3, 1],
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[0, 0, 0, 1]], dtype=np.uint32)
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np.testing.assert_array_equal(result[:, :, 0, 0], expected1)
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expected2 = np.array([[3, 0, 2, 0],
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[0, 2, 2, 0],
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[0, 0, 1, 2],
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[0, 0, 0, 0]], dtype=np.uint32)
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np.testing.assert_array_equal(result[:, :, 0, 1], expected2)
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def test_output_symmetric_1(self):
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result = greycomatrix(self.image, [1], [np.pi / 2], 4,
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symmetric=True)
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assert result.shape == (4, 4, 1, 1)
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expected = np.array([[6, 0, 2, 0],
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[0, 4, 2, 0],
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[2, 2, 2, 2],
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[0, 0, 2, 0]], dtype=np.uint32)
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np.testing.assert_array_equal(result[:, :, 0, 0], expected)
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def test_output_distance(self):
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im = np.array([[0, 0, 0, 0],
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[1, 0, 0, 1],
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[2, 0, 0, 2],
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[3, 0, 0, 3]], dtype=np.uint8)
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result = greycomatrix(im, [3], [0], 4, symmetric=False)
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expected = np.array([[1, 0, 0, 0],
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[0, 1, 0, 0],
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[0, 0, 1, 0],
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[0, 0, 0, 1]], dtype=np.uint32)
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np.testing.assert_array_equal(result[:, :, 0, 0], expected)
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def test_output_combo(self):
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im = np.array([[0],
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[1],
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[2],
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[3]], dtype=np.uint8)
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result = greycomatrix(im, [1, 2], [0, np.pi / 2], 4)
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assert result.shape == (4, 4, 2, 2)
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z = np.zeros((4, 4), dtype=np.uint32)
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e1 = np.array([[0, 1, 0, 0],
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[0, 0, 1, 0],
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[0, 0, 0, 1],
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[0, 0, 0, 0]], dtype=np.uint32)
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e2 = np.array([[0, 0, 1, 0],
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[0, 0, 0, 1],
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[0, 0, 0, 0],
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[0, 0, 0, 0]], dtype=np.uint32)
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np.testing.assert_array_equal(result[:, :, 0, 0], z)
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np.testing.assert_array_equal(result[:, :, 1, 0], z)
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np.testing.assert_array_equal(result[:, :, 0, 1], e1)
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np.testing.assert_array_equal(result[:, :, 1, 1], e2)
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def test_output_empty(self):
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result = greycomatrix(self.image, [10], [0], 4)
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np.testing.assert_array_equal(result[:, :, 0, 0],
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np.zeros((4, 4), dtype=np.uint32))
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result = greycomatrix(self.image, [10], [0], 4, normed=True)
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np.testing.assert_array_equal(result[:, :, 0, 0],
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np.zeros((4, 4), dtype=np.uint32))
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def test_normed_symmetric(self):
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result = greycomatrix(self.image, [1, 2, 3],
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[0, np.pi / 2, np.pi], 4,
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normed=True, symmetric=True)
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for d in range(result.shape[2]):
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for a in range(result.shape[3]):
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np.testing.assert_almost_equal(result[:, :, d, a].sum(),
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1.0)
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np.testing.assert_array_equal(result[:, :, d, a],
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result[:, :, d, a].transpose())
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def test_contrast(self):
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result = greycomatrix(self.image, [1, 2], [0], 4,
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normed=True, symmetric=True)
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result = np.round(result, 3)
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contrast = greycoprops(result, 'contrast')
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np.testing.assert_almost_equal(contrast[0, 0], 0.586)
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def test_dissimilarity(self):
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result = greycomatrix(self.image, [1], [0, np.pi / 2], 4,
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normed=True, symmetric=True)
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result = np.round(result, 3)
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dissimilarity = greycoprops(result, 'dissimilarity')
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np.testing.assert_almost_equal(dissimilarity[0, 0], 0.418)
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def test_dissimilarity_2(self):
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result = greycomatrix(self.image, [1, 3], [np.pi/2], 4,
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normed=True, symmetric=True)
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result = np.round(result, 3)
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dissimilarity = greycoprops(result, 'dissimilarity')[0, 0]
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np.testing.assert_almost_equal(dissimilarity, 0.664)
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def test_invalid_property(self):
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result = greycomatrix(self.image, [1], [0], 4)
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np.testing.assert_raises(ValueError, greycoprops,
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result, 'ABC')
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def test_homogeneity(self):
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result = greycomatrix(self.image, [1], [0, 6], 4, normed=True,
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symmetric=True)
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homogeneity = greycoprops(result, 'homogeneity')[0, 0]
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np.testing.assert_almost_equal(homogeneity, 0.80833333)
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def test_energy(self):
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result = greycomatrix(self.image, [1], [0, 4], 4, normed=True,
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symmetric=True)
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energy = greycoprops(result, 'energy')[0, 0]
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np.testing.assert_almost_equal(energy, 0.38188131)
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def test_correlation(self):
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result = greycomatrix(self.image, [1, 2], [0], 4, normed=True,
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symmetric=True)
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energy = greycoprops(result, 'correlation')
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np.testing.assert_almost_equal(energy[0, 0], 0.71953255)
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np.testing.assert_almost_equal(energy[1, 0], 0.41176470)
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def test_uniform_properties(self):
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im = np.ones((4, 4), dtype=np.uint8)
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result = greycomatrix(im, [1, 2, 8], [0, np.pi / 2], 4, normed=True,
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symmetric=True)
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for prop in ['contrast', 'dissimilarity', 'homogeneity',
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'energy', 'correlation', 'ASM']:
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greycoprops(result, prop)
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if __name__ == '__main__':
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np.testing.run_module_suite()
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