def test_triangulation_inliers(pairs_and_their_E):
for f1, f2, _, pose in pairs_and_their_E:
Rt = pose.get_cam_to_world()[:3]
count_outliers = np.random.randint(0, len(f1) / 10)
f1[:count_outliers, :] += np.random.uniform(0,
1e-1,
size=(count_outliers, 3))
inliers = matching.compute_inliers_bearings(f1, f2, Rt[:, :3], Rt[:,
3])
assert sum(inliers) >= len(f1) - count_outliers
def _two_view_reconstruction_inliers(b1: np.ndarray, b2: np.ndarray,
R: np.ndarray, t: np.ndarray,
threshold: float) -> List[int]:
"""Returns indices of matches that can be triangulated."""
ok = matching.compute_inliers_bearings(b1, b2, R, t, threshold)
return np.nonzero(ok)[0]
def _two_view_reconstruction_inliers(b1, b2, R, t, threshold):
""" Returns indices of matches that can be triangulated. """
ok = matching.compute_inliers_bearings(b1, b2, R, t, threshold)
return np.nonzero(ok)[0]
