import tensorflow as tf

    for classes, sdfs, poses in [(predicted_classes,
                                  predicted_sdfs,
                                  predicted_poses)]:
      for i in range(classes.shape[0]):
        sdf = tf.expand_dims(sdfs[i], -1)
        sdf = sdf * -1.0  # inside positive, outside zero
        samples_object = centernet_utils.transform_pointcloud(
            tf.reshape(samples_world, [1, 1, -1, 3]),
