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Test client for Tensorflow Serving running Darkflow
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#!/usr/bin/env python2.7 | |
# Based on https://github.com/tensorflow/serving/blob/master/tensorflow_serving/example/inception_client.py | |
"""Send JPEG image to tensorflow_model_server loaded with Darkflow model. | |
""" | |
from __future__ import print_function | |
from grpc.beta import implementations | |
import tensorflow as tf | |
from tensorflow_serving.apis import predict_pb2 | |
from tensorflow_serving.apis import prediction_service_pb2 | |
import numpy as np | |
import sys | |
import cv2 | |
tf.app.flags.DEFINE_string('server', 'localhost:11000', | |
'PredictionService host:port') | |
tf.app.flags.DEFINE_string('image', sys.argv[1], sys.argv[1]) | |
FLAGS = tf.app.flags.FLAGS | |
def main(_): | |
host, port = FLAGS.server.split(':') | |
channel = implementations.insecure_channel(host, int(port)) | |
stub = prediction_service_pb2.beta_create_PredictionService_stub(channel) | |
data = cv2.imread(sys.argv[1]) | |
data = cv2.resize(data, (1024, 1024)) | |
data = data.astype(np.float32) | |
data = tf.contrib.util.make_tensor_proto(data, shape=[1, 1024, 1024, 3]) | |
request = predict_pb2.PredictRequest() | |
request.model_spec.name = 'my-model' # Export directory of SavedModel | |
request.model_spec.signature_name = "predict" | |
request.inputs['input'].CopyFrom(data) | |
result = stub.Predict(request, 10.0) # 10 secs timeout | |
print(result) | |
if __name__ == '__main__': | |
tf.app.run() |
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