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53 lines
1.8 KiB
53 lines
1.8 KiB
# Copyright 2021 Zilliz. 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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from typing import NamedTuple
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import numpy
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from towhee.operator import Operator
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class ImageEmbeddingOperatorTemplate(Operator):
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"""
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An operator class that implements image embedding.
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Args:
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model_name (`str`):
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Embedding the image withe the specific model.
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"""
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def __init__(self, model_name: str, framework: str = 'pytorch') -> None:
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"""
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Initialize some parameters and load the model.
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"""
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super().__init__()
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# please define Model class and declare model object, and initialize with the model_name
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# if framework == 'pytorch':
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# from pytorch import Model
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self.model = Model(model_name)
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def __call__(self, img_path: str) -> NamedTuple('Outputs', [('feature_vector', numpy.ndarray)]):
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"""
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Call it when use this class.
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Args:
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img_tensor (`torch.Tensor`):
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The image tensor, you can generate it with TransformImageOperatorClass.
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Returns:
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(`numpy.ndarray`)
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The image embedding.
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"""
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# call model with the img_tensor parameter
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result = self.model(img_path)
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Outputs = NamedTuple('Outputs', [('feature_vector', numpy.ndarray)])
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return Outputs(result)
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