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