def init_request():
print('正在连接Tensorflow Serving...')
channel = grpc.insecure_channel('192.168.10.100:8500')
stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)
request = predict_pb2.PredictRequest()
request.model_spec.name = "catdog"
# request.model_spec.signature_name = tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY # 'predict_images'
request.model_spec.signature_name = "catdog_classification"
print('完成连接Tensorflow Serving...')
return request, stub
def make_prediction(self, input_data, input_tensor_name, timeout=10.0, model_name=None):
request = predict_pb2.PredictRequest()
request.model_spec.name = model_name or 'model'
copy_message(tf.make_tensor_proto(input_data.astype(dtype=np.uint8), dtype='uint8'), request.inputs[input_tensor_name])
response = self.execute(request, timeout=timeout)
results = {}
for key in response.outputs:
tensor_proto = response.outputs[key]
nd_array = tf.make_ndarray(tensor_proto)
results[key] = nd_array
return results
def main():
host = FLAGS.host
port = FLAGS.port
model_name = FLAGS.model_name
model_version = FLAGS.model_version
request_timeout = FLAGS.request_timeout
filename="example3.bmp"
fullpath = os.path.join("/ts/", filename)
src_img = Image.open(fullpath, 'r')
print('TF Processing source/reference image %dx%d - %s.' % (src_img.size[0], src_img.size[1], src_img.format))
src_img.show()
# Create gRPC client and request
channel = grpc.insecure_channel('%s:%s' % (host, port))
stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)
request = predict_pb2.PredictRequest()
request.model_spec.name = model_name
request.model_spec.version.value = 1
request.model_spec.signature_name = 'serving_default'
raw=cv2.imread(fullpath,0)
data = numpy.asarray(raw, dtype=numpy.float32) / 255.
flat = data.reshape(28,28)
print((flat))
copy_message(tf.contrib.util.make_tensor_proto(flat), request.inputs['image'])
print((request))
# Send request
result = stub.Predict(request, request_timeout)
print('waiting response....')
print(' response received \r\n %s ' % (result))
response = numpy.array(result.outputs['classes'].int64_val)
print('prediction is %s ' % (response))
# @Author : RIO
# @desc: 生成调起文件：（需要自行生成/Data/muc/serving/tensorflow_serving/test文件夹）
from grpc.beta import implementations
import numpy as np
import tensorflow as tf
from tensorflow.python.platform import flags
from tensorflow_serving_client.protos import predict_pb2
from tensorflow_serving_client.protos import prediction_service_pb2
from tensorflow.python.framework import dtypes
flags.DEFINE_string('server', '127.0.0.1:9005', 'PredictionService host:port')
FLAGS = flags.FLAGS
n_samples = 100
host, port = FLAGS.server.split(':')
channel = implementations.insecure_channel(host, int(port))
stub = prediction_service_pb2.beta_create_PredictionService_stub(channel)
# Generate deprecate data
x_data = np.arange(n_samples, step=1, dtype=np.float32)
x_data = np.reshape(x_data, (n_samples, 1))
# Send request
request = predict_pb2.PredictRequest()
request.model_spec.name = 'deprecate'
request.inputs['x'].ParseFromString(
tf.contrib.util.make_tensor_proto(x_data,
dtype=dtypes.float32,
shape=[100, 1]).SerializeToString())
result = stub.Predict(request, 10.0) # 10 secs timeout