def from_vectors(cls, vecs, device="cpu"):
        """
        Parameters
        ----------
        vecs: Iterable[np.ndarray]
            Iterable of 10D pose representation.

        intrinsics: np.ndarray
            (3, 3) intrinsics matrix.
        """
        quats, tvecs, sizes = [], [], []
        for vec in vecs:
            quat = vec[:4]
            tvec = vec[4:7]
            size = vec[7:]

            quats.append(quat)
            tvecs.append(tvec)
            sizes.append(size)

        quats = torch.as_tensor(quats, dtype=torch.float32, device=device)
        tvecs = torch.as_tensor(tvecs, dtype=torch.float32, device=device)
        sizes = torch.as_tensor(sizes, device=device)

        return cls(quats, tvecs, sizes)

        Parameters
        ----------
        vecs: Iterable[np.ndarray]
            Iterable of 10D pose representation.

        intrinsics: np.ndarray
            (3, 3) intrinsics matrix.
        
tridet/structures/boxes3d.py