convert to pb model file and using libtensorflow to interface

[wolf943134497]

Hi @tcies Thanks for your great works!
I want to use your pretrained model in libtensorflow, because I need to use c++ api. I convert your checkpoint files to pb model file using freeze_graph.py scipts, but the pb model can not use in libtensorflow , because I found the pb files only left 1 opts (vgg16_netvlad_pca/WPCA/kernel). my code are as follows:

def freeze_graph(input_checkpoint,output_graph):
output_node_names = "vgg16_netvlad_pca/WPCA/kernel"
saver = tf.train.import_meta_graph(input_checkpoint + '.meta', clear_devices=True)

with tf.Session() as sess:
    saver.restore(sess, input_checkpoint) 
    output_graph_def = graph_util.convert_variables_to_constants(  
        sess=sess,
        input_graph_def=sess.graph_def,
        output_node_names=output_node_names.split(","))

    with tf.gfile.GFile(output_graph, "wb") as f: 
        f.write(output_graph_def.SerializeToString()) 
    print("%d ops in the final graph." % len(output_graph_def.node)) 

if name == "main":
input_checkpoint='netvlad/vd16_pitts30k_conv5_3_vlad_preL2_intra_white'
out_pb_path="./frozen_model.pb"
freeze_graph(input_checkpoint,out_pb_path)

any suggestions?
thanks!