import tensorflow as tf

            # Load the model
            input_map = {'image_batch': image_batch, 'label_batch': label_batch, 'phase_train': phase_train_placeholder}
            facenet.load_model(args.model, input_map=input_map)

            # Get output tensor
            embeddings = tf.get_default_graph().get_tensor_by_name("embeddings:0")
#
            coord = tf.train.Coordinator()
            tf.train.start_queue_runners(coord=coord, sess=sess)

            evaluate(sess, eval_enqueue_op, image_paths_placeholder, labels_placeholder, phase_train_placeholder, batch_size_placeholder, control_placeholder,
                embeddings, label_batch, paths, actual_issame, args.lfw_batch_size, args.lfw_nrof_folds, args.distance_metric, args.subtract_mean,
                args.use_flipped_images, args.use_fixed_image_standardization, args.warmup_steps, args.max_steps)

