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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 = Sequential([
- File2Image(), BGR2RGB(), Resize(
- (608, 608), interpolation=cv2.INTER_LINEAR), Div(255.0), Transpose(
- (2, 0, 1))
- ])
- postprocess = RCNNPostprocess("label_list.txt", "output", [608, 608])
- client = Client()
- client.load_client_config("serving_client/serving_client_conf.prototxt")
- client.connect(['127.0.0.1:9393'])
- im = preprocess(sys.argv[1])
- fetch_map = client.predict(
- feed={
- "image": im,
- "im_size": np.array(list(im.shape[1:])),
- },
- fetch=["multiclass_nms_0.tmp_0"])
- fetch_map["image"] = sys.argv[1]
- postprocess(fetch_map)
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