61 lines
2.1 KiB
Python
61 lines
2.1 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 sys
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import base64
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from paddle_serving_server.web_service import WebService
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import utils
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class ImageService(WebService):
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def __init__(self, name):
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super(ImageService, self).__init__(name=name)
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self.operators = self.create_operators()
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def create_operators(self):
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size = 224
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img_mean = [0.485, 0.456, 0.406]
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img_std = [0.229, 0.224, 0.225]
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img_scale = 1.0 / 255.0
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decode_op = utils.DecodeImage()
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resize_op = utils.ResizeImage(resize_short=256)
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crop_op = utils.CropImage(size=(size, size))
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normalize_op = utils.NormalizeImage(
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scale=img_scale, mean=img_mean, std=img_std)
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totensor_op = utils.ToTensor()
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return [decode_op, resize_op, crop_op, normalize_op, totensor_op]
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def _process_image(self, data, ops):
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for op in ops:
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data = op(data)
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return data
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def preprocess(self, feed={}, fetch=[]):
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feed_batch = []
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for ins in feed:
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if "image" not in ins:
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raise ("feed data error!")
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sample = base64.b64decode(ins["image"])
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img = self._process_image(sample, self.operators)
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feed_batch.append({"image": img})
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return feed_batch, fetch
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image_service = ImageService(name="image")
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image_service.load_model_config(sys.argv[1])
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image_service.prepare_server(
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workdir=sys.argv[2], port=int(sys.argv[3]), device="cpu")
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image_service.run_server()
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image_service.run_flask()
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