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谢昕辰MengzhangLI
谢昕辰
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MengzhangLI
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[Feature] Support dark dataset test (open-mmlab#815)
* rewrite init function * support dark_zurich test * reset image size * add night * add train_pipeline * init function parameters * remove base dataset config * remove fcn config * update doc * add datasets to README * update doc * fix table of PSPNet config * fix table of PSPNet config * change 'model' tp 'evaluation checkpoint' * fix typos in README_zh-CN Co-authored-by: MengzhangLI <[email protected]>
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‎README.md

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- [x] [SETR (CVPR'2021)](configs/setr)
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- [x] [SegFormer (ArXiv'2021)](configs/segformer)
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Supported datasets:
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- [x] [Cityscapes](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#cityscapes)
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- [x] [PASCAL VOC](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#pascal-voc)
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- [x] [ADE20K](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#ade20k)
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- [x] [Pascal Context](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#pascal-context)
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- [x] [CHASE_DB1](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#chase-db1)
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- [x] [DRIVE](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#drive)
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- [x] [HRF](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#hrf)
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- [x] [STARE](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#stare)
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- [x] [Dark Zurich](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#dark-zurich)
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- [x] [Nighttime Driving](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#nighttime-driving)
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## Installation
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Please refer to [get_started.md](docs/get_started.md#installation) for installation and [dataset_prepare.md](docs/dataset_prepare.md#prepare-datasets) for dataset preparation.

‎README_zh-CN.md

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- [x] [SETR (CVPR'2021)](configs/setr)
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- [x] [SegFormer (ArXiv'2021)](configs/segformer)
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已支持的数据集：
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- [x] [Cityscapes](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#cityscapes)
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- [x] [PASCAL VOC](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#pascal-voc)
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- [x] [ADE20K](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#ade20k)
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- [x] [Pascal Context](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#pascal-context)
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- [x] [CHASE_DB1](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#chase-db1)
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- [x] [DRIVE](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#drive)
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- [x] [HRF](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#hrf)
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- [x] [STARE](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#stare)
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- [x] [Dark Zurich](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#dark-zurich)
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- [x] [Nighttime Driving](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md#nighttime-driving)
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## 安装
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请参考[快速入门文档](docs_zh-CN/get_started.md#installation)进行安装和数据集准备。
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请参考[快速入门文档](docs_zh-CN/get_started.md#installation)进行安装，参考[数据集准备](docs_zh-CN/dataset_prepare.md)处理数据。
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## 快速入门
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‎configs/pspnet/README.md

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| ------ | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | ------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| PSPNet | R-101-D8 | 480x480 | 40000 | - | - | 52.02 | 53.54 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_480x480_40k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_480x480_40k_pascal_context_59/pspnet_r101-d8_480x480_40k_pascal_context_59_20210416_114524-86d44cd4.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_480x480_40k_pascal_context_59/pspnet_r101-d8_480x480_40k_pascal_context_59-20210416_114524.log.json) |
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| PSPNet | R-101-D8 | 480x480 | 80000 | - | - | 52.47 | 53.99 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_480x480_80k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_480x480_80k_pascal_context_59/pspnet_r101-d8_480x480_80k_pascal_context_59_20210416_114418-fa6caaa2.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_480x480_80k_pascal_context_59/pspnet_r101-d8_480x480_80k_pascal_context_59-20210416_114418.log.json) |
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### Dark Zurich and Nighttime Driving
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We support evaluation results on these two datasets using models above trained on Cityscapes training set.
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|Method|Backbone |Training Dataset |Test Dataset |mIoU |config| evaluation checkpoint|
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|------ |------ |------ |----- |-----|-----|-----|
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|PSPNet|R-50-D8 |Cityscapes Training set |Dark Zurich |10.91|[config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r50-d8_512x1024_40k_dark.py)|[model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338.log.json) |
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|PSPNet|R-50-D8 |Cityscapes Training set |Nighttime Driving|23.02|[config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r50-d8_512x1024_40k_night_driving.py)| [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338.log.json) |
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|PSPNet|R-50-D8 |Cityscapes Training set |Cityscapes Validation set|77.85 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338.log.json) |
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|PSPNet|R-101-D8 |Cityscapes Training set |Dark Zurich |10.16|[config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_512x1024_40k_dark.py)| [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_40k_cityscapes/pspnet_r101-d8_512x1024_40k_cityscapes_20200604_232751-467e7cf4.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_40k_cityscapes/pspnet_r101-d8_512x1024_40k_cityscapes_20200604_232751.log.json) |
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|PSPNet|R-101-D8 |Cityscapes Training set |Nighttime Driving|20.25|[config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_512x1024_40k_night_driving.py)| [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_40k_cityscapes/pspnet_r101-d8_512x1024_40k_cityscapes_20200604_232751-467e7cf4.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_40k_cityscapes/pspnet_r101-d8_512x1024_40k_cityscapes_20200604_232751.log.json) |
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|PSPNet|R-101-D8 |Cityscapes Training set |Cityscapes Validation set|78.34|[config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_512x1024_40k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_40k_cityscapes/pspnet_r101-d8_512x1024_40k_cityscapes_20200604_232751-467e7cf4.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_40k_cityscapes/pspnet_r101-d8_512x1024_40k_cityscapes_20200604_232751.log.json) |
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|PSPNet|R-101b-D8|Cityscapes Training set |Dark Zurich |15.54|[config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101b-d8_512x1024_80k_dark.py)| [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101b-d8_512x1024_80k_cityscapes/pspnet_r101b-d8_512x1024_80k_cityscapes_20201226_170012-3a4d38ab.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101b-d8_512x1024_80k_cityscapes/pspnet_r101b-d8_512x1024_80k_cityscapes-20201226_170012.log.json) |
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|PSPNet|R-101b-D8|Cityscapes Training set |Nighttime Driving|22.25|[config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101b-d8_512x1024_80k_night_driving.py)| [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101b-d8_512x1024_80k_cityscapes/pspnet_r101b-d8_512x1024_80k_cityscapes_20201226_170012-3a4d38ab.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101b-d8_512x1024_80k_cityscapes/pspnet_r101b-d8_512x1024_80k_cityscapes-20201226_170012.log.json) |
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|PSPNet|R-101b-D8|Cityscapes Training set |Cityscapes Validation set|79.69|[config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101b-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101b-d8_512x1024_80k_cityscapes/pspnet_r101b-d8_512x1024_80k_cityscapes_20201226_170012-3a4d38ab.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101b-d8_512x1024_80k_cityscapes/pspnet_r101b-d8_512x1024_80k_cityscapes-20201226_170012.log.json) |

‎configs/pspnet/pspnet.yml

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- Pascal VOC 2012 + Aug
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- Pascal Context
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- Pascal Context 59
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- Dark Zurich and Nighttime Driving
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Name: pspnet
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Models:
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- Config: configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py

‎configs/pspnet/pspnet_r101-d8_512x1024_40k_dark.py

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_base_ = './pspnet_r50-d8_512x1024_40k_dark.py'
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model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))

‎configs/pspnet/pspnet_r101-d8_512x1024_40k_night_driving.py

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_base_ = './pspnet_r50-d8_512x1024_40k_night_driving.py'
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model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))

‎configs/pspnet/pspnet_r101b-d8_512x1024_80k_dark.py

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_base_ = './pspnet_r50-d8_512x1024_80k_dark.py'
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model = dict(
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pretrained='torchvision://resnet101',
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backbone=dict(type='ResNet', depth=101))

‎configs/pspnet/pspnet_r101b-d8_512x1024_80k_night_driving.py

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_base_ = './pspnet_r50-d8_512x1024_80k_night_driving.py'
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model = dict(
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pretrained='torchvision://resnet101',
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backbone=dict(type='ResNet', depth=101))

‎configs/pspnet/pspnet_r50-d8_512x1024_40k_dark.py

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_base_ = [
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'../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
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'../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
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]
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img_norm_cfg = dict(
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mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(
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type='MultiScaleFlipAug',
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img_scale=(1920, 1080),
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# img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
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flip=False,
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transforms=[
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dict(type='Resize', keep_ratio=True),
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dict(type='RandomFlip'),
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dict(type='Normalize', **img_norm_cfg),
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dict(type='ImageToTensor', keys=['img']),
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dict(type='Collect', keys=['img']),
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])
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]
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data = dict(
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test=dict(
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type='DarkZurichDataset',
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data_root='data/dark_zurich/',
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img_dir='rgb_anon/val/night/GOPR0356',
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ann_dir='gt/val/night/GOPR0356',
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pipeline=test_pipeline))

‎configs/pspnet/pspnet_r50-d8_512x1024_40k_night_driving.py

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_base_ = [
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'../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
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'../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
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]
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img_norm_cfg = dict(
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mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(
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type='MultiScaleFlipAug',
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img_scale=(1920, 1080),
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# img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
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flip=False,
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transforms=[
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dict(type='Resize', keep_ratio=True),
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dict(type='RandomFlip'),
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dict(type='Normalize', **img_norm_cfg),
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dict(type='ImageToTensor', keys=['img']),
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dict(type='Collect', keys=['img']),
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])
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]
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data = dict(
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test=dict(
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type='NightDrivingDataset',
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data_root='data/NighttimeDrivingTest/',
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img_dir='leftImg8bit/test/night',
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ann_dir='gtCoarse_daytime_trainvaltest/test/night',
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pipeline=test_pipeline))

‎configs/pspnet/pspnet_r50-d8_512x1024_80k_dark.py

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_base_ = [
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'../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
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'../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
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]
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img_norm_cfg = dict(
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mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(
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type='MultiScaleFlipAug',
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img_scale=(1920, 1080),
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# img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
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flip=False,
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transforms=[
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dict(type='Resize', keep_ratio=True),
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dict(type='RandomFlip'),
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dict(type='Normalize', **img_norm_cfg),
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dict(type='ImageToTensor', keys=['img']),
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dict(type='Collect', keys=['img']),
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])
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]
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data = dict(
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test=dict(
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type='DarkZurichDataset',
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data_root='data/dark_zurich/',
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img_dir='rgb_anon/val/night/GOPR0356',
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ann_dir='gt/val/night/GOPR0356',
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pipeline=test_pipeline))

‎configs/pspnet/pspnet_r50-d8_512x1024_80k_night_driving.py

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_base_ = [
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'../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
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'../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
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]
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img_norm_cfg = dict(
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mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(
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type='MultiScaleFlipAug',
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img_scale=(1920, 1080),
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# img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
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flip=False,
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transforms=[
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dict(type='Resize', keep_ratio=True),
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dict(type='RandomFlip'),
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dict(type='Normalize', **img_norm_cfg),
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dict(type='ImageToTensor', keys=['img']),
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dict(type='Collect', keys=['img']),
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])
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]
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data = dict(
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test=dict(
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type='NightDrivingDataset',
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data_root='data/NighttimeDrivingTest/',
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img_dir='leftImg8bit/test/night',
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ann_dir='gtCoarse_daytime_trainvaltest/test/night',
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pipeline=test_pipeline))

‎docs/dataset_prepare.md

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│ │ ├── annotations
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│ │ │ ├── training
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│ │ │ ├── validation
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| ├── dark_zurich
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| │   ├── gps
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| │   │   ├── val
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| │   │   └── val_ref
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| │   ├── gt
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| │   │   └── val
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| │   ├── LICENSE.txt
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| │   ├── lists_file_names
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| │   │   ├── val_filenames.txt
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| │   │   └── val_ref_filenames.txt
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| │   ├── README.md
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| │   └── rgb_anon
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| │   | ├── val
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| │   | └── val_ref
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| ├── NighttimeDrivingTest
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| | ├── gtCoarse_daytime_trainvaltest
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| | │   └── test
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| | │   └── night
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| | └── leftImg8bit
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| | | └── test
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| | | └── night
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```
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### Cityscapes
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```
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The script will make directory structure automatically.
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### Dark Zurich
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Since we only support test models on this dataset, you may only download [the validation set](https://data.vision.ee.ethz.ch/csakarid/shared/GCMA_UIoU/Dark_Zurich_val_anon.zip).
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### Nighttime Driving
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Since we only support test models on this dataset, you may only download [the test set](http://data.vision.ee.ethz.ch/daid/NighttimeDriving/NighttimeDrivingTest.zip).

‎docs_zh-CN/dataset_prepare.md

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@@ -68,7 +68,27 @@ mmsegmentation
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│ │ ├── annotations
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│ │ │ ├── training
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│ │ │ ├── validation
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| ├── dark_zurich
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| │   ├── gps
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| │   │   ├── val
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| │   │   └── val_ref
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| │   ├── gt
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| │   │   └── val
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| │   ├── LICENSE.txt
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| │   ├── lists_file_names
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| │   │   ├── val_filenames.txt
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| │   │   └── val_ref_filenames.txt
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| │   ├── README.md
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| │   └── rgb_anon
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| │   | ├── val
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| │   | └── val_ref
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| ├── NighttimeDrivingTest
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| | ├── gtCoarse_daytime_trainvaltest
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| | │   └── test
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| | │   └── night
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| | └── leftImg8bit
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| | | └── test
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| | | └── night
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```
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### Cityscapes
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```
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这个脚本将自动生成正确的文件夹结构。
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### Dark Zurich
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因为我们只支持在此数据集上测试模型，所以您只需下载[验证集](https://data.vision.ee.ethz.ch/csakarid/shared/GCMA_UIoU/Dark_Zurich_val_anon.zip)。
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### Nighttime Driving
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因为我们只支持在此数据集上测试模型，所以您只需下载[测试集](http://data.vision.ee.ethz.ch/daid/NighttimeDriving/NighttimeDrivingTest.zip)。

‎mmseg/datasets/__init__.py

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from .chase_db1 import ChaseDB1Dataset
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from .cityscapes import CityscapesDataset
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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, RepeatDataset
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from .drive import DRIVEDataset
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from .hrf import HRFDataset
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from .night_driving import NightDrivingDataset
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from .pascal_context import PascalContextDataset, PascalContextDataset59
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from .stare import STAREDataset
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from .voc import PascalVOCDataset
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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'
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'STAREDataset', 'DarkZurichDataset', 'NightDrivingDataset'
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]

‎mmseg/datasets/dark_zurich.py

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from .builder import DATASETS
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from .cityscapes import CityscapesDataset
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@DATASETS.register_module()
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class DarkZurichDataset(CityscapesDataset):
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"""DarkZurichDataset dataset."""
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def __init__(self, **kwargs):
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super().__init__(
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img_suffix='_rgb_anon.png',
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seg_map_suffix='_gt_labelTrainIds.png',
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**kwargs)

‎mmseg/datasets/night_driving.py

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from .builder import DATASETS
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from .cityscapes import CityscapesDataset
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@DATASETS.register_module()
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class NightDrivingDataset(CityscapesDataset):
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"""NightDrivingDataset dataset."""
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def __init__(self, **kwargs):
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super().__init__(
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img_suffix='_leftImg8bit.png',
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seg_map_suffix='_gtCoarse_labelTrainIds.png',
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**kwargs)

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