def relative_pose_ransac_rotation_only(b1, b2, threshold, iterations,
probability):
params = pyrobust.RobustEstimatorParams()
params.iterations = 1000
result = pyrobust.ransac_relative_rotation(b1, b2, threshold, params,
pyrobust.RansacType.RANSAC)
return result.lo_model.T
def relative_pose_ransac_rotation_only(
b1: np.ndarray,
b2: np.ndarray,
threshold: float,
iterations: int,
probability: float,
) -> np.ndarray:
params = pyrobust.RobustEstimatorParams()
params.iterations = iterations
result = pyrobust.ransac_relative_rotation(b1, b2, threshold, params,
pyrobust.RansacType.RANSAC)
return result.lo_model.T
def test_outliers_relative_rotation_ransac(pairs_and_their_E):
for f1, _, _, _ in pairs_and_their_E:
vec_x = np.random.rand(3)
vec_x /= np.linalg.norm(vec_x)
vec_y = np.array([-vec_x[1], vec_x[0], 0.])
vec_y /= np.linalg.norm(vec_y)
vec_z = np.cross(vec_x, vec_y)
rotation = np.array([vec_x, vec_y, vec_z])
f1 /= np.linalg.norm(f1, axis=1)[:, None]
f2 = [rotation.dot(x) for x in f1]
points = np.concatenate((f1, f2), axis=1)
scale = 1e-3
points += np.random.rand(*points.shape) * scale
ratio_outliers = 0.3
add_outliers(ratio_outliers, points, 0.1, 1.0)
f1, f2 = points[:, 0:3], points[:, 3:6]
f1 /= np.linalg.norm(f1, axis=1)[:, None]
f2 /= np.linalg.norm(f2, axis=1)[:, None]
params = pyrobust.RobustEstimatorParams()
params.iterations = 1000
result = pyrobust.ransac_relative_rotation(f1, f2,
np.sqrt(3 * scale * scale),
params,
pyrobust.RansacType.RANSAC)
tolerance = 0.04
inliers_count = (1 - ratio_outliers) * len(points)
assert np.isclose(len(result.inliers_indices),
inliers_count,
rtol=tolerance)
assert np.linalg.norm(rotation - result.lo_model, ord='fro') < 8e-2
def relative_pose_ransac_rotation_only(b1, b2, threshold, iterations,
probability):
# in-house estimation
if in_house_multiview:
threshold = np.arccos(1 - threshold)
params = pyrobust.RobustEstimatorParams()
params.iterations = 1000
result = pyrobust.ransac_relative_rotation(b1, b2, threshold, params,
pyrobust.RansacType.RANSAC)
return result.lo_model.T
else:
try:
return pyopengv.relative_pose_ransac_rotation_only(
b1,
b2,
threshold,
iterations=iterations,
probability=probability)
except Exception:
# Older versions of pyopengv do not accept the probability argument.
return pyopengv.relative_pose_ransac_rotation_only(
b1, b2, threshold, iterations)
