def main(_):
host, port = FLAGS.server.split(':')
channel = implementations.insecure_channel(host, int(port))
stub = inception_inference_pb2.beta_create_InceptionService_stub(channel)
# Create label->synset mapping
synsets = []
with open(SYNSET_FILE) as f:
synsets = f.read().splitlines()
# Create synset->metadata mapping
texts = {}
with open(METADATA_FILE) as f:
for line in f.read().splitlines():
parts = line.split('\t')
assert len(parts) == 2
texts[parts[0]] = parts[1]
# Send request
with open(FLAGS.image, 'rb') as f:
# See inception_inference.proto for gRPC request/response details.
data = f.read()
request = inception_inference_pb2.InceptionRequest()
request.jpeg_encoded = data
result = stub.Classify(request, 10.0) # 10 secs timeout
for i in range(NUM_CLASSES):
index = result.classes[i]
score = result.scores[i]
print '%f : %s' % (score, texts[synsets[index - 1]])
def main(_):
host, port = FLAGS.server.split(':')
channel = implementations.insecure_channel(host, int(port))
stub = inception_inference_pb2.beta_create_InceptionService_stub(channel)
# Create label->synset mapping
synsets = []
with open(SYNSET_FILE) as f:
synsets = f.read().splitlines()
# Create synset->metadata mapping
texts = {}
with open(METADATA_FILE) as f:
for line in f.read().splitlines():
parts = line.split('\t')
assert len(parts) == 2
texts[parts[0]] = parts[1]
# Send request
with open(FLAGS.image, 'rb') as f:
# See inception_inference.proto for gRPC request/response details.
data = f.read()
request = inception_inference_pb2.InceptionRequest()
request.jpeg_encoded = data
result = stub.Classify(request, 10.0) # 10 secs timeout
for i in range(NUM_CLASSES):
index = result.classes[i]
score = result.scores[i]
print '%f : %s' % (score, texts[synsets[index - 1]])
def main(_):
host, port = FLAGS.server.split(':')
channel = implementations.insecure_channel(host, int(port))
stub = inception_inference_pb2.beta_create_InceptionService_stub(channel)
# Send request
with open(FLAGS.image, 'rb') as f:
# See inception_inference.proto for gRPC request/response details.
data = f.read()
request = inception_inference_pb2.InceptionRequest()
request.jpeg_encoded = data
result = stub.Classify(request, 10.0) # 10 secs timeout
print result
def main(_):
host, port = FLAGS.server.split(':')
channel = implementations.insecure_channel(host, int(port))
stub = inception_inference_pb2.beta_create_InceptionService_stub(channel)
# Send request
with open(FLAGS.image, 'rb') as f:
# See inception_inference.proto for gRPC request/response details.
data = f.read()
request = inception_inference_pb2.InceptionRequest()
request.jpeg_encoded = data
result = stub.Classify(request, 10.0) # 10 secs timeout
print result
#!/usr/bin/env python
from flask import render_template, redirect, request, abort, jsonify
import base64
from PIL import Image
from io import BytesIO
root_name = '/home/zhangxs/serving/project_0810'
# inception client
from grpc.beta import implementations
import tensorflow as tf
import numpy as np
import os, sys, time
sys.path.append(os.path.join(os.path.dirname(__file__), "../../../"))
from tensorflow_serving.example import inception_inference_pb2
channel = implementations.insecure_channel('localhost', int(9000))
stub = inception_inference_pb2.beta_create_InceptionService_stub(channel)
# client end
# for annoy
from annoy import AnnoyIndex
t = AnnoyIndex(2048)
t.load(root_name + '/test.ann')
with open(root_name + '/names.lst', 'r') as f:
lst = f.readlines()
# end
def index():
return render_template('index.html')
def home():
payload = {'gae_mode': False}