import tensorflow as tf


            # data processing
            inputs_list = []
            for i in range(num_gpu):
                img = tf.expand_dims(img_batch[i], axis=0)
                pretrain_zoo = PretrainModelZoo()
                if self.cfgs.NET_NAME in pretrain_zoo.pth_zoo or self.cfgs.NET_NAME in pretrain_zoo.mxnet_zoo:
                    img = img / tf.constant([cfgs.PIXEL_STD])

                gtboxes_and_label_r = tf.py_func(backward_convert,
                                                 inp=[gtboxes_and_label_batch[i]],
                                                 Tout=tf.float32)
                gtboxes_and_label_r = tf.reshape(gtboxes_and_label_r, [-1, 6])

                gtboxes_and_label_h = get_horizen_minAreaRectangle(gtboxes_and_label_batch[i])
                gtboxes_and_label_h = tf.reshape(gtboxes_and_label_h, [-1, 5])

                num_objects = num_objects_batch[i]
