data2vec
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37 lines
1.5 KiB
37 lines
1.5 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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import numpy
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import torch
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import towhee
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from PIL import Image as PILImage
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from transformers import BeitFeatureExtractor, Data2VecVisionForImageClassification
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from towhee.operator.base import NNOperator
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from towhee.types.arg import arg, to_image_color
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class Data2VecVision(NNOperator):
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def __init__(self, model_name='facebook/data2vec-vision-base'):
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self.model = Data2VecVisionForImageClassification.from_pretrained(model_name)
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self.feature_extractor = BeitFeatureExtractor.from_pretrained(model_name)
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@arg(1, to_image_color('RGB'))
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def __call__(self, img: 'towhee.types.Image') -> numpy.ndarray:
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img = PILImage.fromarray(img.astype('uint8'), 'RGB')
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inputs = self.feature_extractor(img, return_tensors="pt")
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with torch.no_grad():
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outputs = self.model.data2vec_vision(**inputs).pooler_output
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return outputs.detach().cpu().numpy().flatten()
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