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()