test_network.py

import sys
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

import tensorflow as tf


label_lines = [line.rstrip() for line
            in tf.gfile.GFile(
			'/tf_files/retrained_labels.txt')]

with tf.gfile.FastGFile('/tf_files/retrained_graph.pb', 'rb') as f:
    graph_def = tf.GraphDef()
    graph_def.ParseFromString(f.read())
    _ = tf.import_graph_def(graph_def, name='')

sess = tf.Session()
softmax_tensor = sess.graph.get_tensor_by_name('final_result:0')

test_dir = '/tf_files/Test'
for img in os.listdir(test_dir):
    image_data = tf.gfile.FastGFile(os.path.join(test_dir, img), 'rb').read()
    predictions = sess.run(softmax_tensor,
            {'DecodeJpeg/contents:0': image_data})

    top_k = predictions[0].argsort()[-len(predictions[0]):][::-1]

    print(img)
    for node_id in top_k[:5]:
        human_string = label_lines[node_id]
        score = predictions[0][node_id]
        print(' %s (score = %.5f)' % (human_string, score))