text: import io
  import json
  import os
  
  import numpy as np
  import tensorflow as tf
  import tensorflow.contrib.slim as slim
  from flask import Flask, request
  from PIL import Image
  from werkzeug import secure_filename
  
  import inception_v1
  
  app = Flask(__name__)
  with open("real-label.json", "r") as fopen:
      labels = json.load(fopen)
  sess = tf.InteractiveSession()
  X = tf.placeholder(tf.float32, [None, None, 3])
  image = X / 128.0 - 1
  image = tf.expand_dims(image, 0)
  image = tf.image.resize_images(image, (224, 224))
  with slim.arg_scope(inception_v1.inception_v1_arg_scope()):
      logits, endpoints = inception_v1.inception_v1(image, num_classes=1001, is_training=False)
  sess.run(tf.global_variables_initializer())
  var_lists = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope="InceptionV1")
  saver = tf.train.Saver(var_list=var_lists)
  saver.restore(sess, "inception_v1.ckpt")
  
  
  @app.route("/inception", methods=["POST"])
  def inception():
      img = np.array(Image.open(io.BytesIO(request.files["file"].read())))
      return json.dumps({"label": labels[str(np.argmax(sess.run(logits, feed_dict={X: img})[0]))]})
  
  
  if __name__ == "__main__":
      app.run(host="0.0.0.0", port=5000, debug=True)
  