import tensorflow as tf

    def get_box_indices(proposals):
      proposals_shape = proposals.get_shape().as_list()
      if any(dim is None for dim in proposals_shape):
        proposals_shape = tf.shape(proposals)
      ones_mat = tf.ones(proposals_shape[:2], dtype=tf.int32)
      multiplier = tf.expand_dims(
          tf.range(start=0, limit=proposals_shape[0]), 1)
      return tf.reshape(ones_mat * multiplier, [-1])

    net = image_features
    with slim.arg_scope(self._conv_hyperparams):
      net = slim.conv2d(net, self._depth, [1, 1], scope='reduce_depth')
