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https://github.com/open-mmlab/mmsegmentation.git
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## Motivation Based on the ImageNet dataset, we propose the ImageNet-S dataset has 1.2 million training images and 50k high-quality semantic segmentation annotations to support unsupervised/semi-supervised semantic segmentation on the ImageNet dataset. paper: Large-scale Unsupervised Semantic Segmentation (TPAMI 2022) [Paper link](https://arxiv.org/abs/2106.03149) ## Modification 1. Support imagenet-s dataset and its' configuration 2. Add the dataset preparation in the documentation
36 lines
1.6 KiB
Python
36 lines
1.6 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from .ade import ADE20KDataset
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from .builder import DATASETS, PIPELINES, build_dataloader, build_dataset
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from .chase_db1 import ChaseDB1Dataset
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from .cityscapes import CityscapesDataset
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from .coco_stuff import COCOStuffDataset
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from .custom import CustomDataset
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from .dark_zurich import DarkZurichDataset
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from .dataset_wrappers import (ConcatDataset, MultiImageMixDataset,
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RepeatDataset)
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from .drive import DRIVEDataset
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from .face import FaceOccludedDataset
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from .hrf import HRFDataset
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from .imagenets import (ImageNetSDataset, LoadImageNetSAnnotations,
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LoadImageNetSImageFromFile)
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from .isaid import iSAIDDataset
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from .isprs import ISPRSDataset
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from .loveda import LoveDADataset
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from .night_driving import NightDrivingDataset
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from .pascal_context import PascalContextDataset, PascalContextDataset59
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from .potsdam import PotsdamDataset
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from .stare import STAREDataset
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from .voc import PascalVOCDataset
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__all__ = [
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'CustomDataset', 'build_dataloader', 'ConcatDataset', 'RepeatDataset',
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'DATASETS', 'build_dataset', 'PIPELINES', 'CityscapesDataset',
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'PascalVOCDataset', 'ADE20KDataset', 'PascalContextDataset',
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'PascalContextDataset59', 'ChaseDB1Dataset', 'DRIVEDataset', 'HRFDataset',
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'STAREDataset', 'DarkZurichDataset', 'NightDrivingDataset',
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'COCOStuffDataset', 'LoveDADataset', 'MultiImageMixDataset',
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'iSAIDDataset', 'ISPRSDataset', 'PotsdamDataset', 'FaceOccludedDataset',
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'ImageNetSDataset', 'LoadImageNetSAnnotations',
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'LoadImageNetSImageFromFile'
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]
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