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84 lines
2.5 KiB
84 lines
2.5 KiB
# 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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from paddle.io import Dataset |
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import cv2 |
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from ppcls.data import preprocess |
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from ppcls.data.preprocess import transform |
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from ppcls.utils import logger |
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def create_operators(params): |
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""" |
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create operators based on the config |
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Args: |
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params(list): a dict list, used to create some operators |
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""" |
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assert isinstance(params, list), ('operator config should be a list') |
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ops = [] |
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for operator in params: |
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assert isinstance(operator, |
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dict) and len(operator) == 1, "yaml format error" |
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op_name = list(operator)[0] |
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param = {} if operator[op_name] is None else operator[op_name] |
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op = getattr(preprocess, op_name)(**param) |
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ops.append(op) |
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return ops |
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class CommonDataset(Dataset): |
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def __init__( |
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self, |
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image_root, |
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cls_label_path, |
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transform_ops=None, ): |
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self._img_root = image_root |
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self._cls_path = cls_label_path |
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if transform_ops: |
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self._transform_ops = create_operators(transform_ops) |
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self.images = [] |
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self.labels = [] |
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self._load_anno() |
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def _load_anno(self): |
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pass |
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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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return (img, self.labels[idx]) |
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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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def __len__(self): |
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return len(self.images) |
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@property |
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def class_num(self): |
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return len(set(self.labels))
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