retinaface
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48 lines
1.5 KiB
48 lines
1.5 KiB
# Copyright 2022 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 sys
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import os
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from typing import NamedTuple, List
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from PIL import Image
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import torch
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from torchvision import transforms
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from pathlib import Path
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import numpy
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from towhee import register
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from towhee.operator import Operator
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from towhee.types.image_utils import to_pil
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from towhee._types import Image
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from towhee.types.arg import arg, to_image_color
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@register(output_schema=['bbox', 'score'])
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class Retinaface(Operator):
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"""
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Retinaface
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"""
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def __init__(self) -> None:
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super().__init__()
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sys.path.append(str(Path(__file__).parent))
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from retinaface_impl import Model
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self.model = Model()
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@arg(1, to_image_color('RGB') )
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def __call__(self, image: Image):
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img = torch.FloatTensor(numpy.asarray(to_pil(image)))
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bboxes, keypoints = self.model(img)
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bboxes = bboxes.cpu().detach().numpy()
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return bboxes[:,:4].astype(int), bboxes[:,4]
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