def test_shape_large(self, device, dtype):
F_mat = torch.rand(1, 2, 3, 3, device=device, dtype=dtype)
K1 = torch.rand(1, 2, 3, 3, device=device, dtype=dtype)
K2 = torch.rand(1, 1, 3, 3, device=device,
dtype=dtype) # check broadcasting
E_mat = epi.essential_from_fundamental(F_mat, K1, K2)
assert E_mat.shape == (1, 2, 3, 3)
def test_from_to_fundamental(self, device, dtype):
F_mat = torch.rand(1, 3, 3, device=device, dtype=dtype)
K1 = torch.rand(1, 3, 3, device=device, dtype=dtype)
K2 = torch.rand(1, 3, 3, device=device, dtype=dtype)
E_mat = epi.essential_from_fundamental(F_mat, K1, K2)
F_hat = epi.fundamental_from_essential(E_mat, K1, K2)
assert_allclose(F_mat, F_hat, atol=1e-4, rtol=1e-4)
def test_shape(self, batch_size, device, dtype):
B: int = batch_size
F_mat = torch.rand(B, 3, 3, device=device, dtype=dtype)
K1 = torch.rand(B, 3, 3, device=device, dtype=dtype)
K2 = torch.rand(1, 3, 3, device=device, dtype=dtype) # check broadcasting
E_mat = epi.essential_from_fundamental(F_mat, K1, K2)
assert E_mat.shape == (B, 3, 3)
def test_from_to_essential(self, device, dtype):
scene = utils.generate_two_view_random_scene(device, dtype)
F_mat = scene['F']
E_mat = epi.essential_from_fundamental(F_mat, scene['K1'], scene['K2'])
F_hat = epi.fundamental_from_essential(E_mat, scene['K1'], scene['K2'])
F_mat_norm = epi.normalize_transformation(F_mat)
F_hat_norm = epi.normalize_transformation(F_hat)
assert_close(F_mat_norm, F_hat_norm, atol=1e-4, rtol=1e-4)
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_from_fundamental(self, device, dtype):
scene = utils.generate_two_view_random_scene(device, dtype)
F_mat = scene['F']
K1 = scene['K1']
K2 = scene['K2']
E_mat = epi.essential_from_fundamental(F_mat, K1, K2)
F_hat = epi.fundamental_from_essential(E_mat, K1, K2)
F_mat_norm = epi.normalize_transformation(F_mat)
F_hat_norm = epi.normalize_transformation(F_hat)
assert_allclose(F_mat_norm, F_hat_norm)
def test_smoke(self, device, dtype):
F_mat = torch.rand(1, 3, 3, device=device, dtype=dtype)
K1 = torch.rand(1, 3, 3, device=device, dtype=dtype)
K2 = torch.rand(1, 3, 3, device=device, dtype=dtype)
E_mat = epi.essential_from_fundamental(F_mat, K1, K2)
assert E_mat.shape == (1, 3, 3)