36 lines
1.3 KiB
Python
36 lines
1.3 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import sys
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__dir__ = os.path.dirname(os.path.abspath(__file__))
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sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../')))
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import argparse
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import numpy as np
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import cv2
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import paddlehub as hub
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from tools.infer.utils import preprocess
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args = argparse.Namespace(resize_short=256, resize=224, normalize=True)
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img_path_list = ["./deploy/hubserving/ILSVRC2012_val_00006666.JPEG", ]
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module = hub.Module(name="clas_system")
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for i, img_path in enumerate(img_path_list):
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img = cv2.imread(img_path)[:, :, ::-1]
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img = preprocess(img, args)
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batch_input_data = np.expand_dims(img, axis=0)
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res = module.predict(batch_input_data)
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print("The returned result of {}: {}".format(img_path, res))
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