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Open Source Computer Vision Library
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97 lines
3.2 KiB
97 lines
3.2 KiB
#!/usr/bin/env python |
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# 2009-01-16, Xavier Delacour <xavier.delacour@gmail.com> |
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import unittest |
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from numpy import *; |
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from numpy.linalg import *; |
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import sys; |
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import cvtestutils |
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from cv import *; |
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from adaptors import *; |
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def transform(H,x): |
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x1 = H * asmatrix(r_[x[0],x[1],1]).transpose() |
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x1 = asarray(x1).flatten() |
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return r_[x1[0]/x1[2],x1[1]/x1[2]] |
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class homography_test(unittest.TestCase): |
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def test_ransac_identity(self): |
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pts1 = random.rand(100,2); |
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result,H = cvFindHomography(pts1, pts1, CV_RANSAC, 1e-5); |
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assert(result and all(abs(Ipl2NumPy(H) - eye(3)) < 1e-5)); |
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def test_ransac_0_outliers(self): |
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pts1 = random.rand(100,2); |
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H1 = asmatrix(random.rand(3,3)); |
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H1 = H1 / H1[2,2] |
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pts2 = [transform(H1,x) for x in pts1] |
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result,H = cvFindHomography(pts1, pts2, CV_RANSAC, 1e-5); |
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assert(result and all(abs(H1-H)<1e-5)) |
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def test_ransac_30_outliers(self): |
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pts1 = random.rand(100,2); |
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H1 = asmatrix(random.rand(3,3)); |
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H1 = H1 / H1[2,2] |
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pts2 = [transform(H1,x) for x in pts1] |
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pts2[0:30] = random.rand(30,2) |
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result,H = cvFindHomography(pts1, pts2, CV_RANSAC, 1e-5); |
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assert(result and all(abs(H1-H)<1e-5)) |
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def test_ransac_70_outliers(self): |
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pts1 = random.rand(100,2); |
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H1 = asmatrix(random.rand(3,3)); |
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H1 = H1 / H1[2,2] |
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pts2 = [transform(H1,x) for x in pts1] |
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pts2[0:70] = random.rand(70,2) |
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result,H = cvFindHomography(pts1, pts2, CV_RANSAC, 1e-5); |
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assert(result and all(abs(H1-H)<1e-5)) |
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def test_ransac_90_outliers(self): |
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pts1 = random.rand(100,2); |
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H1 = asmatrix(random.rand(3,3)); |
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H1 = H1 / H1[2,2] |
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pts2 = [transform(H1,x) for x in pts1] |
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pts2[0:90] = random.rand(90,2) |
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result,H = cvFindHomography(pts1, pts2, CV_RANSAC, 1e-5); |
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assert(not result or not all(abs(H1-H)<1e-5)) |
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def test_lmeds_identity(self): |
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pts1 = random.rand(100,2); |
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result,H = cvFindHomography(pts1, pts1, CV_LMEDS); |
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assert(result and all(abs(Ipl2NumPy(H) - eye(3)) < 1e-5)); |
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def test_lmeds_0_outliers(self): |
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pts1 = random.rand(100,2); |
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H1 = asmatrix(random.rand(3,3)); |
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H1 = H1 / H1[2,2] |
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pts2 = [transform(H1,x) for x in pts1] |
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result,H = cvFindHomography(pts1, pts2, CV_LMEDS); |
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assert(result and all(abs(H1-H)<1e-5)) |
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def test_lmeds_30_outliers(self): |
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pts1 = random.rand(100,2); |
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H1 = asmatrix(random.rand(3,3)); |
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H1 = H1 / H1[2,2] |
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pts2 = [transform(H1,x) for x in pts1] |
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pts2[0:30] = random.rand(30,2) |
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result,H = cvFindHomography(pts1, pts2, CV_LMEDS); |
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assert(result and all(abs(H1-H)<1e-5)) |
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def test_lmeds_70_outliers(self): |
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pts1 = random.rand(100,2); |
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H1 = asmatrix(random.rand(3,3)); |
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H1 = H1 / H1[2,2] |
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pts2 = vstack([transform(H1,x) for x in pts1]) |
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pts2[0:70] = random.rand(70,2) |
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result,H = cvFindHomography(pts1, pts2, CV_LMEDS); |
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assert(not result or not all(abs(H1-H)<1e-5)) |
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def suite(): |
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return unittest.TestLoader().loadTestsFromTestCase(homography_test) |
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if __name__ == '__main__': |
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unittest.TextTestRunner(verbosity=2).run(suite()) |
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