def test_smoke(self, device, dtype):
R1 = torch.rand(1, 3, 3, device=device, dtype=dtype)
t1 = torch.rand(1, 3, 1, device=device, dtype=dtype)
R2 = torch.rand(1, 3, 3, device=device, dtype=dtype)
t2 = torch.rand(1, 3, 1, device=device, dtype=dtype)
E_mat = epi.essential_from_Rt(R1, t1, R2, t2)
assert E_mat.shape == (1, 3, 3)
def test_shape(self, batch_size, device, dtype):
B: int = batch_size
R1 = torch.rand(B, 3, 3, device=device, dtype=dtype)
t1 = torch.rand(B, 3, 1, device=device, dtype=dtype)
R2 = torch.rand(1, 3, 3, device=device, dtype=dtype) # check broadcasting
t2 = torch.rand(B, 3, 1, device=device, dtype=dtype)
E_mat = epi.essential_from_Rt(R1, t1, R2, t2)
assert E_mat.shape == (B, 3, 3)
def test_from_fundamental_Rt(self, device, dtype):
scene = utils.generate_two_view_random_scene(device, dtype)
E_from_Rt = epi.essential_from_Rt(scene['R1'], scene['t1'], scene['R2'], scene['t2'])
E_from_F = epi.essential_from_fundamental(scene['F'], scene['K1'], scene['K2'])
E_from_Rt_norm = epi.normalize_transformation(E_from_Rt)
E_from_F_norm = epi.normalize_transformation(E_from_F)
# TODO: occasionally failed with error > 0.04
assert_close(E_from_Rt_norm, E_from_F_norm, rtol=1e-3, atol=1e-3)
def test_two_view(self, device, dtype):
scene = utils.generate_two_view_random_scene(device, dtype)
E_mat = epi.essential_from_Rt(scene['R1'], scene['t1'], scene['R2'], scene['t2'])
R, t = epi.relative_camera_motion(scene['R1'], scene['t1'], scene['R2'], scene['t2'])
t = torch.nn.functional.normalize(t, dim=1)
R_hat, t_hat, _ = epi.motion_from_essential_choose_solution(
E_mat, scene['K1'], scene['K2'], scene['x1'], scene['x2']
)
assert_close(t, t_hat)
assert_close(R, R_hat, rtol=1e-4, atol=1e-4)
def test_two_view(self, device, dtype):
scene = utils.generate_two_view_random_scene(device, dtype)
R1, t1 = scene['R1'], scene['t1']
R2, t2 = scene['R2'], scene['t2']
E_mat = epi.essential_from_Rt(R1, t1, R2, t2)
R, t = epi.relative_camera_motion(R1, t1, R2, t2)
t = torch.nn.functional.normalize(t, dim=1)
Rs, ts = epi.motion_from_essential(E_mat)
rot_error = (Rs - R).abs().sum((-2, -1))
vec_error = (ts - t).abs().sum((-1))
rtol: float = 1e-4
assert (rot_error < rtol).any() & (vec_error < rtol).any()
