def _compare(self, boxlist1, boxlist2): """Compute matrix of (negated) sq distances. Args: boxlist1: BoxList holding N boxes. boxlist2: BoxList holding M boxes. Returns: A tensor with shape [N, M] representing negated pairwise squared distance. """ return -1 * box_list_ops.sq_dist(boxlist1, boxlist2)
def graph_fn(): corners1 = tf.constant([[0.0, 0.0, 0.0, 0.0], [1.0, 1.0, 0.0, 2.0]]) corners2 = tf.constant([[3.0, 4.0, 1.0, 0.0], [-4.0, 0.0, 0.0, 3.0], [0.0, 0.0, 0.0, 0.0]]) boxes1 = box_list.BoxList(corners1) boxes2 = box_list.BoxList(corners2) dist_matrix = box_list_ops.sq_dist(boxes1, boxes2) return dist_matrix
def _compare(self, boxlist1, boxlist2): """Compute matrix of (negated) sq distances. Args: boxlist1: BoxList holding N boxes. boxlist2: BoxList holding M boxes. Returns: A tensor with shape [N, M] representing negated pairwise squared distance. """ return -1 * box_list_ops.sq_dist(boxlist1, boxlist2)
def test_pairwise_distances(self): corners1 = tf.constant([[0.0, 0.0, 0.0, 0.0], [1.0, 1.0, 0.0, 2.0]]) corners2 = tf.constant([[3.0, 4.0, 1.0, 0.0], [-4.0, 0.0, 0.0, 3.0], [0.0, 0.0, 0.0, 0.0]]) exp_output = [[26, 25, 0], [18, 27, 6]] boxes1 = box_list.BoxList(corners1) boxes2 = box_list.BoxList(corners2) dist_matrix = box_list_ops.sq_dist(boxes1, boxes2) with self.test_session() as sess: dist_output = sess.run(dist_matrix) self.assertAllClose(dist_output, exp_output)
def test_pairwise_distances(self): corners1 = tf.constant([[0.0, 0.0, 0.0, 0.0], [1.0, 1.0, 0.0, 2.0]]) corners2 = tf.constant([[3.0, 4.0, 1.0, 0.0], [-4.0, 0.0, 0.0, 3.0], [0.0, 0.0, 0.0, 0.0]]) exp_output = [[26, 25, 0], [18, 27, 6]] boxes1 = box_list.BoxList(corners1) boxes2 = box_list.BoxList(corners2) dist_matrix = box_list_ops.sq_dist(boxes1, boxes2) with self.test_session() as sess: dist_output = sess.run(dist_matrix) self.assertAllClose(dist_output, exp_output)
def _compare(self, boxlist1, boxlist2): reserved_ioa = tf.transpose(box_list_ops.ioa(boxlist2, boxlist1)) neg_sq_dist = -1 * box_list_ops.sq_dist(boxlist1, boxlist2) return tf.multiply(tf.scalar_mul(2, tf.sigmoid(neg_sq_dist)), reserved_ioa)