52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
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# Copyright (c) 2021 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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from __future__ import print_function
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import io
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import tarfile
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import numpy as np
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from PIL import Image #all use default backend
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import paddle
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from paddle.io import Dataset
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import pickle
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import os
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import cv2
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import random
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from .common_dataset import CommonDataset
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class ImageNetDataset(CommonDataset):
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def _load_anno(self, seed=None):
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assert os.path.exists(self._cls_path)
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assert os.path.exists(self._img_root)
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self.images = []
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self.labels = []
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with open(self._cls_path) as fd:
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lines = fd.readlines()
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if seed is not None:
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np.random.RandomState(seed).shuffle(lines)
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else:
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np.random.shuffle(lines)
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for l in lines:
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l = l.strip().split(" ")
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self.images.append(os.path.join(self._img_root, l[0]))
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self.labels.append(int(l[1]))
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assert os.path.exists(self.images[-1])
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