最简单的tensorflow将ckpt转换成pb

ckpt转化为pb并进行测试运行

利用tf.graph_util.convert_variables_to_constants进行模型固化

1.导出pb文件：export.py

2.利用pb文件进行预测

from __future__ import absolute_import, unicode_literals
import tensorflow as tf
import os
from PIL import Image
import numpy as np

os.environ["CUDA_VISIBLE_DEVICES"] = "0"

readImage = Image.open("./test/517.jpg")
    #readImage = Image.open("cat.9.jpg")
    # readImage.show()
    # matrix = np.asarray(readImage).astype("float32")
readImage = readImage.resize([100, 100])
npmatrix = np.array(readImage)

with tf.Graph().as_default():
        output_graph_def = tf.GraphDef()
        output_graph_path = '/data/lyk/lyk/FaceFeature/output_model/pb_model/SecModel.pb'
        #    sess.graph.add_to_collection("input", mnist.test.images)

        with open(output_graph_path, "rb") as f:
            output_graph_def.ParseFromString(f.read())
            tf.import_graph_def(output_graph_def, name="")

        with tf.Session() as sess:
            tf.initialize_all_variables().run()
            input_x = sess.graph.get_tensor_by_name("inputdata:0")

            output = sess.graph.get_tensor_by_name("outputdata:0")

            y_conv_2 = sess.run(output, {input_x: image})
            print("y_conv_2", y_conv_2)

测试结果：

参考资料：链接