47 lines
1.4 KiB
Python
47 lines
1.4 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 requests
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import base64
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import json
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import sys
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import numpy as np
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py_version = sys.version_info[0]
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def predict(image_path, server):
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with open(image_path, "rb") as f:
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image = base64.b64encode(f.read()).decode("utf-8")
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req = json.dumps({"feed": [{"image": image}], "fetch": ["prediction"]})
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r = requests.post(
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server, data=req, headers={"Content-Type": "application/json"})
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try:
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pred = r.json()["result"]["prediction"][0]
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cls_id = np.argmax(pred)
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score = pred[cls_id]
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pred = {"cls_id": cls_id, "score": score}
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return pred
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except ValueError:
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print(r.text)
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return r
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if __name__ == "__main__":
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server = "http://127.0.0.1:{}/image/prediction".format(sys.argv[1])
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image_file = sys.argv[2]
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res = predict(image_file, server)
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print("res:", res)
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