Forked from masroorhasan/optimized_tf_serving_client.py
Created
July 7, 2019 03:29
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#!/usr/bin/env python | |
from __future__ import print_function | |
import argparse | |
import numpy as np | |
import time | |
tt = time.time() | |
import cv2 | |
from grpc.beta import implementations | |
from protos.tensorflow.core.framework import tensor_pb2 | |
from protos.tensorflow.core.framework import tensor_shape_pb2 | |
from protos.tensorflow.core.framework import types_pb2 | |
from protos.tensorflow_serving.apis import predict_pb2 | |
from protos.tensorflow_serving.apis import prediction_service_pb2 | |
parser = argparse.ArgumentParser(description='incetion grpc client flags.') | |
parser.add_argument('--host', default='0.0.0.0', help='inception serving host') | |
parser.add_argument('--port', default='9000', help='inception serving port') | |
parser.add_argument('--image', default='', help='path to JPEG image file') | |
FLAGS = parser.parse_args() | |
def main(): | |
# create prediction service client stub | |
channel = implementations.insecure_channel(FLAGS.host, int(FLAGS.port)) | |
stub = prediction_service_pb2.beta_create_PredictionService_stub(channel) | |
# create request | |
request = predict_pb2.PredictRequest() | |
request.model_spec.name = 'resnet' | |
request.model_spec.signature_name = 'serving_default' | |
# read image into numpy array | |
img = cv2.imread(FLAGS.image).astype(np.float32) | |
# convert to tensor proto and make request | |
# shape is in NHWC (num_samples x height x width x channels) format | |
dims = [tensor_shape_pb2.TensorShapeProto.Dim(size=dim) for dim in [1]+list(img.shape)] | |
tensor = tensor_pb2.TensorProto( | |
dtype=types_pb2.DT_FLOAT, | |
tensor_shape=tensor_shape_pb2.TensorShapeProto(dim=dims), | |
float_val=list(img.reshape(-1))) | |
request.inputs['input'].CopyFrom(tensor) | |
resp = stub.Predict(request, 30.0) | |
print('total time: {}s'.format(time.time() - tt)) | |
if __name__ == '__main__': | |
main() |
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