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test_client.py
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test_client.py
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import sys
import numpy as np
from paddle_serving_client import Client
from paddle_serving_app.reader import *
import cv2
preprocess = DetectionSequential([
DetectionFile2Image(),
DetectionResize((300, 300), False, interpolation=cv2.INTER_LINEAR),
DetectionNormalize([104.0, 117.0, 123.0], [1.0, 1.0, 1.0], False),
DetectionTranspose((2, 0, 1)),
])
postprocess = RCNNPostprocess("label_list.txt", "output")
client = Client()
client.load_client_config("serving_client/serving_client_conf.prototxt")
client.connect(['127.0.0.1:9494'])
im, im_info = preprocess(sys.argv[1])
fetch_map = client.predict(
feed={
"image": im,
"im_shape": np.array(list(im.shape[1:])).reshape(-1),
"scale_factor": im_info['scale_factor'],
},
fetch=["save_infer_model/scale_0.tmp_1"],
batch=False)
print(fetch_map)
fetch_map["image"] = sys.argv[1]
postprocess(fetch_map)