import tensorflow as tf

                                                    weights_regularizer=weights_regularizer,
                                                    biases_regularizer=biases_regularizer,
                                                    biases_initializer=tf.constant_initializer(0.0)):

                                    gtboxes_and_label_h, gtboxes_and_label_r = tf.py_func(self.get_gtboxes_and_label,
                                                                                          inp=[inputs_list[i][1],
                                                                                               inputs_list[i][2],
                                                                                               inputs_list[i][3]],
                                                                                          Tout=[tf.float32, tf.float32])
                                    gtboxes_and_label_h = tf.reshape(gtboxes_and_label_h, [-1, 5])
                                    gtboxes_and_label_r = tf.reshape(gtboxes_and_label_r, [-1, 6])

                                    if cfgs.ANGLE_RANGE == 180:
                                        gtboxes_and_label_r_ = tf.py_func(coordinate_present_convert,
                                                                          inp=[gtboxes_and_label_r, -1],
                                                                          Tout=tf.float32)
                                        gtboxes_and_label_r_ = tf.reshape(gtboxes_and_label_r_, [-1, 6])

                                        gt_encode_label = tf.py_func(angle_label_encode,
                                                                     inp=[gtboxes_and_label_r_[:, -2], cfgs.ANGLE_RANGE,
