def test_chamfer_distance1(self, device, dtype, get_input, get_tol):
p1, p2 = get_input
output1 = pc.chamfer_distance(p1, p2)
output2 = pc.chamfer_distance(p2, p1)
expected1 = torch.tensor([72.5838, 151.0809],
dtype=dtype,
device=device)
atol, rtol = get_tol
assert torch.allclose(output1, expected1, atol=atol, rtol=rtol)
def test_chamfer_distance(self, device, dtype, p1, p2, tolerances):
output = pc.chamfer_distance(p1, p2)
expected = torch.tensor([72.5838, 151.0809], dtype=dtype, device=device)
atol, rtol = tolerances
assert torch.allclose(output, expected, atol=atol, rtol=rtol)
def test_chamfer_distance2(self, device, dtype, get_input, get_tol):
p1, p2 = get_input
output2 = pc.chamfer_distance(p1, p2, w1=1.3, w2=0.8)
expected2 = torch.tensor([71.4303, 150.8620],
dtype=dtype,
device=device)
atol, rtol = get_tol
assert torch.allclose(output2, expected2, atol=atol, rtol=rtol)
def test_chamfer_distance_not_squared(self, device, dtype, p1, p2, tolerances):
output = pc.chamfer_distance(p1, p2, squared=False)
expected = torch.tensor([11.1704, 17.1130], dtype=dtype, device=device)
atol, rtol = tolerances
assert torch.allclose(output, expected, atol=atol, rtol=rtol)
def test_weighted_chamfer_distance(self, device, dtype, p1, p2, tolerances):
output = pc.chamfer_distance(p1, p2, w1=1.3, w2=0.8)
expected = torch.tensor([71.4303, 150.8620], dtype=dtype, device=device)
atol, rtol = tolerances
assert torch.allclose(output, expected, atol=atol, rtol=rtol)