def test_orthographic(self):
cameras = OrthographicCameras()
P = cameras.get_projection_transform()
vertices = torch.randn([3, 4, 3], dtype=torch.float32)
projected_verts = vertices.clone()
v1 = P.transform_points(vertices)
v2 = orthographic_project_naive(vertices)
self.assertClose(v1[..., :2], v2[..., :2])
self.assertClose(v1, projected_verts)
def test_orthographic_kwargs(self):
cameras = OrthographicCameras(focal_length=5.0,
principal_point=((2.5, 2.5), ))
P = cameras.get_projection_transform(focal_length=2.0,
principal_point=((2.5, 3.5), ))
vertices = torch.randn([3, 4, 3], dtype=torch.float32)
projected_verts = vertices.clone()
projected_verts[:, :, :2] *= 2.0
projected_verts[:, :, 0] += 2.5
projected_verts[:, :, 1] += 3.5
v1 = P.transform_points(vertices)
self.assertClose(v1, projected_verts)
def test_orthographic_scaled(self):
focal_length_x = 10.0
focal_length_y = 15.0
cameras = OrthographicCameras(focal_length=((focal_length_x, focal_length_y),))
P = cameras.get_projection_transform()
vertices = torch.randn([3, 4, 3], dtype=torch.float32)
projected_verts = vertices.clone()
projected_verts[:, :, 0] *= focal_length_x
projected_verts[:, :, 1] *= focal_length_y
v1 = P.transform_points(vertices)
v2 = orthographic_project_naive(
vertices, scale_xyz=(focal_length_x, focal_length_y, 1.0)
)
v3 = cameras.transform_points(vertices)
self.assertClose(v1[..., :2], v2[..., :2])
self.assertClose(v3[..., :2], v2[..., :2])
self.assertClose(v1, projected_verts)
