66 lines
2.3 KiB
Python
66 lines
2.3 KiB
Python
# 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 numpy as np
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import os
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import cv2
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from ppcls.data.preprocess import transform
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from ppcls.utils import logger
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from .common_dataset import CommonDataset
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class MultiLabelDataset(CommonDataset):
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def _load_anno(self, label_ratio=False):
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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.label_ratio = label_ratio
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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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for l in lines:
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l = l.strip().split("\t")
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self.images.append(os.path.join(self._img_root, l[0]))
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labels = l[1].split(',')
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labels = [np.int64(i) for i in labels]
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self.labels.append(labels)
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assert os.path.exists(self.images[-1])
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if self.label_ratio is not False:
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return np.array(self.labels).mean(0).astype("float32")
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def __getitem__(self, idx):
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try:
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with open(self.images[idx], 'rb') as f:
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img = f.read()
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if self._transform_ops:
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img = transform(img, self._transform_ops)
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img = img.transpose((2, 0, 1))
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label = np.array(self.labels[idx]).astype("float32")
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if self.label_ratio is not False:
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return (img, np.array([label, self.label_ratio]))
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else:
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return (img, label)
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except Exception as ex:
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logger.error("Exception occured when parse line: {} with msg: {}".
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format(self.images[idx], ex))
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rnd_idx = np.random.randint(self.__len__())
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return self.__getitem__(rnd_idx)
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