import tensorflow as tf

        pred = valid_images_masked + predicted_patch 
       # valid_annotations = np.squeeze(valid_annotations, axis=3)
       # pred = np.squeeze(pred, axis=3)
        print(valid_images.shape)
        print(valid_annotations.shape)
        print(pred.shape)

        for itr in range(FLAGS.batch_size):
            utils.save_image(valid_images_masked[itr].astype(np.uint8), FLAGS.logs_dir, name="inp_" + str(5+itr))
            utils.save_image(valid_annotations[itr].astype(np.uint8), FLAGS.logs_dir, name="gt_" + str(5+itr))
            utils.save_image(pred[itr].astype(np.uint8), FLAGS.logs_dir, name="predz_" + str(5+itr))
            print("Saved image: %d" % itr)


if __name__ == "__main__":
    tf.app.run()
