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- # Copyright (c) 2021 PaddlePaddle Authors. 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 __future__ import print_function
- import numpy as np
- import os
- from .common_dataset import CommonDataset
- class ImageNetDataset(CommonDataset):
- def _load_anno(self, seed=None):
- assert os.path.exists(self._cls_path)
- assert os.path.exists(self._img_root)
- self.images = []
- self.labels = []
- with open(self._cls_path) as fd:
- lines = fd.readlines()
- if seed is not None:
- np.random.RandomState(seed).shuffle(lines)
- for l in lines:
- l = l.strip().split(" ")
- self.images.append(os.path.join(self._img_root, l[0]))
- self.labels.append(np.int64(l[1]))
- assert os.path.exists(self.images[-1])
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