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88 lines
3.1 KiB
88 lines
3.1 KiB
# Copyright (c) 2020 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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import os |
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import glob |
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from paddlers_slim.models.ppseg.datasets import Dataset |
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from paddlers_slim.models.ppseg.cvlibs import manager |
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from paddlers_slim.models.ppseg.transforms import Compose |
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@manager.DATASETS.add_component |
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class Cityscapes(Dataset): |
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""" |
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Cityscapes dataset `https://www.cityscapes-dataset.com/`. |
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The folder structure is as follow: |
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cityscapes |
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|--leftImg8bit |
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| |--train |
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| |--val |
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| |--test |
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|--gtFine |
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| |--train |
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| |--val |
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| |--test |
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Make sure there are **labelTrainIds.png in gtFine directory. If not, please run the conver_cityscapes.py in tools. |
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Args: |
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transforms (list): Transforms for image. |
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dataset_root (str): Cityscapes dataset directory. |
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mode (str, optional): Which part of dataset to use. it is one of ('train', 'val', 'test'). Default: 'train'. |
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edge (bool, optional): Whether to compute edge while training. Default: False |
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""" |
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NUM_CLASSES = 19 |
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def __init__(self, transforms, dataset_root, mode='train', edge=False): |
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self.dataset_root = dataset_root |
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self.transforms = Compose(transforms) |
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self.file_list = list() |
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mode = mode.lower() |
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self.mode = mode |
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self.num_classes = self.NUM_CLASSES |
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self.ignore_index = 255 |
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self.edge = edge |
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if mode not in ['train', 'val', 'test']: |
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raise ValueError( |
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"mode should be 'train', 'val' or 'test', but got {}.".format( |
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mode)) |
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if self.transforms is None: |
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raise ValueError("`transforms` is necessary, but it is None.") |
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img_dir = os.path.join(self.dataset_root, 'leftImg8bit') |
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label_dir = os.path.join(self.dataset_root, 'gtFine') |
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if self.dataset_root is None or not os.path.isdir( |
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self.dataset_root) or not os.path.isdir( |
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img_dir) or not os.path.isdir(label_dir): |
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raise ValueError( |
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"The dataset is not Found or the folder structure is nonconfoumance." |
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) |
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label_files = sorted( |
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glob.glob( |
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os.path.join(label_dir, mode, '*', |
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'*_gtFine_labelTrainIds.png'))) |
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img_files = sorted( |
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glob.glob(os.path.join(img_dir, mode, '*', '*_leftImg8bit.png'))) |
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self.file_list = [ |
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[img_path, label_path] |
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for img_path, label_path in zip(img_files, label_files) |
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]
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