Find file
7440ab6 Jan 5, 2017
63 lines (51 sloc) 1.93 KB
from flask import Flask, jsonify, request
import tensorflow as tf
import base64
import urllib.request
import os
import json
FLAGS ='model_path', '/tmp/model.pb',
"""Directory where to read model data.""")'port', 5000,
"""Application port.""")'top_k', 5,
"""Finds the k largest entries""")'input_size', 96,
"""Size of input image""")
sess = tf.Session()
# load model data, get top_k
if not os.path.isfile(FLAGS.model_path):
print('No model data file found')
urllib.request.urlretrieve(os.environ['MODEL_DOWNLOAD_URL'], FLAGS.model_path)
graph_def = tf.GraphDef()
with tf.gfile.FastGFile(FLAGS.model_path, 'rb') as f:
tf.import_graph_def(graph_def, name='')
fc7 = sess.graph.get_tensor_by_name('fc7/fc7:0')
top_values, top_indices = tf.nn.top_k(tf.nn.softmax(fc7), k=FLAGS.top_k)
# retrieve labels
labels = json.loads('labels:0')).decode())
print('{} labels loaded.'.format(len(labels)))
# Flask setup
app = Flask(__name__)
app.debug = True
def label():
return jsonify(labels=labels)
@app.route('/', methods=['POST'])
def api():
results = []
ops = [top_values, top_indices]
for image in request.form.getlist('images'):
values, indices =, feed_dict={'contents:0': base64.b64decode(image.split(',')[1])})
top_k = []
for i in range(FLAGS.top_k):
'label': labels.get(str(indices.flatten().tolist()[i]), {}),
'value': values.flatten().tolist()[i],
results.append({'top': top_k})
return jsonify(results=results)
if __name__ == '__main__':'', port=FLAGS.port)