def setUp(self):
self.tol = 6
self.p1 = np.array([
[99.0825859985542, 1136.84241396289, -1031.66650596755, -117.325418998838],
[-301.923289351466, 1760.62028612233, -533.989983528509, 566.900954605729]
])
self.p2 = np.array([
[1829.78818884974, 15378.7866880232, 612.159309750213, 2756.44403323769],
[474.180433404958, 4677.92468041337, 1092.76420021176, 1874.89973953780]
])
self.R1 = np.array([
[0.983417707845482, 0.013453875580959, 0.180855204867843],
[-0.060089831339915, 0.965084992860598, 0.254951306575981],
[-0.171110560940808, -0.261591188282616, 0.949890112669571]
])
self.R2 = np.array([
[0.556837962037774, 0.329755275145440, 0.762360113428931],
[-0.787076103923440, 0.502747650438714, 0.357429722618378],
[-0.265410419287405, -0.799065866178820, 0.539491474299248]
])
self.sols = dpl.get_valtonenornhag_arxiv_2021_frEfr(
np.asfortranarray(self.p1),
np.asfortranarray(self.p2),
np.asfortranarray(self.R1),
np.asfortranarray(self.R2),
False
)
def test_valtonenornhag_arxiv_2021_frEfr_dimensions02(self):
"""Check that an exception is raised when dimensions are incorrect."""
p1 = np.random.randn(2, 3)
p2 = np.random.randn(2, 2)
R1 = np.random.randn(3, 3)
R2 = np.random.randn(3, 3)
with self.assertRaises(ValueError):
sols = dpl.get_valtonenornhag_arxiv_2021_frEfr( # noqa
np.asfortranarray(p1), np.asfortranarray(p2),
np.asfortranarray(R1), np.asfortranarray(R2), False)
def setUp(self):
"""This mimicks the example/synthetic script."""
rng = np.random.default_rng(2021)
# There are some reproducibility issues between Travis setup and local ones
self.tol = 11
N = 4
distortion_param = -1e-07
R1, R2, f, F, x1, x2, R, t, x1u, x2u = generate_points_realistic(
N, distortion_param, rng)
use_fast_solver = False
out = dpl.get_valtonenornhag_arxiv_2021_frEfr(
np.asfortranarray(x1[:2, :]), np.asfortranarray(x2[:2, :]),
np.asfortranarray(R1), np.asfortranarray(R2), use_fast_solver)
self.f_err, self.F_err, self.r_err = compare_to_gt(
out, f, F, distortion_param)
r_err = min([abs(r - sol['r']) / abs(r) for sol in sols])
return f_err, F_err, r_err
if __name__ == '__main__':
# Test a minimal sample
print('frEfr:')
N = 4
distortion_param = -1e-07
R1, R2, f, F, x1, x2, R, t, x1u, x2u = generate_points_realistic(
N, distortion_param)
print(f'F =\n{F / F[2, 2]}')
print(f'f = {f}')
print(f'r = {distortion_param}')
print(f'x1 =\n{x1[:2, :]}')
print(f'x2 =\n{x2[:2, :]}')
use_fast_solver = False
out = dpl.get_valtonenornhag_arxiv_2021_frEfr(np.asfortranarray(x1[:2, :]),
np.asfortranarray(x2[:2, :]),
np.asfortranarray(R1),
np.asfortranarray(R2),
use_fast_solver)
f_err, F_err, r_err = compare_to_gt(out, f, F, distortion_param)
print(f'Focal length error: {f_err}')
print(f'Fundamental matrix error: {F_err}')
print(f'Radial distortion parameter error: {r_err}')