def guess_init_3d(model_joints, 
                  j3d, 
                  joints_category="orig"):
    """Initialize the camera translation via triangle similarity, by using the torso joints        .
    :param model_joints: SMPL model with pre joints
    :param j3d: 25x3 array of Kinect Joints
    :returns: 3D vector corresponding to the estimated camera translation
    """
    # get the indexed four
    gt_joints = ['RHip', 'LHip', 'RShoulder', 'LShoulder']
    gt_joints_ind = [config.JOINT_MAP[joint] for joint in gt_joints]
    
    if joints_category=="orig":
        joints_ind_category = [config.JOINT_MAP[joint] for joint in gt_joints]
    elif joints_category=="AMASS":
        joints_ind_category = [config.AMASS_JOINT_MAP[joint] for joint in gt_joints] 
    elif joints_category=="MMM":
        joints_ind_category = [config.MMM_JOINT_MAP[joint] for joint in gt_joints] 
    else:
        print("NO SUCH JOINTS CATEGORY!") 

    sum_init_t = (j3d[:, joints_ind_category] - model_joints[:, gt_joints_ind]).sum(dim=1)
    init_t = sum_init_t / 4.0
    return init_t
Initialize the camera translation via triangle similarity, by using the torso joints        .
    :param model_joints: SMPL model with pre joints
    :param j3d: 25x3 array of Kinect Joints
    :returns: 3D vector corresponding to the estimated camera translation
    
mGPT/data/transforms/joints2rots/smplify.py