## 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
add custom dataset
add face occlusion dataset
add config file for occlusion face
fix format
update prepare.md
formatting
formatting
fix typo error for doc
update downloading process
Update dataset_prepare.md
PR fix version to original repository. change to original repository.
* support iSAID aerial dataset
* Update and rename docs/dataset_prepare.md to 博士/dataset_prepare.md
* Update dataset_prepare.md
* fix typo
* fix typo
* fix typo
* remove imgviz
* fix wrong order in annotation name
* upload models&logs
* upload models&logs
* add load_annotations
* fix unittest coverage
* fix unittest coverage
* fix correct crop size in config
* fix iSAID unit test
* fix iSAID unit test
* fix typos
* fix wrong crop size in readme
* use smaller figure as test data
* add smaller dataset in test data
* add blank in docs
* use 0 bytes pseudo data
* add footnote and comments for crop size
* change iSAID to isaid and add default value in it
* change iSAID to isaid in _base_
Co-authored-by: MengzhangLI <mcmong@pku.edu.cn>
* update LoveDA dataset api
* revised lint errors in dataset_prepare.md
* revised lint errors in loveda.py
* revised lint errors in loveda.py
* revised lint errors in dataset_prepare.md
* revised lint errors in dataset_prepare.md
* checked with isort and yapf
* checked with isort and yapf
* checked with isort and yapf
* Revert "checked with isort and yapf"
This reverts commit 686a51d9
* Revert "checked with isort and yapf"
This reverts commit b877e121bb2935ceefc503c09675019489829feb.
* Revert "revised lint errors in dataset_prepare.md"
This reverts commit 2289e27c
* Revert "checked with isort and yapf"
This reverts commit 159db2f8
* Revert "checked with isort and yapf"
This reverts commit 159db2f8
* add configs & fix bugs
* update new branch
* upload models&logs and add format-only
* change pretraied model path of HRNet
* fix the errors in dataset_prepare.md
* fix the errors in dataset_prepare.md and configs in loveda.py
* change the description in docs_zh-CN/dataset_prepare.md
* use init_cfg
* fix test converage
* adding pseudo loveda dataset
* adding pseudo loveda dataset
* adding pseudo loveda dataset
* adding pseudo loveda dataset
* adding pseudo loveda dataset
* adding pseudo loveda dataset
* Update docs/dataset_prepare.md
Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
* Update docs_zh-CN/dataset_prepare.md
Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
* Update docs_zh-CN/dataset_prepare.md
Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
* Delete unused lines of unittest and Add docs
* add convert .py file
* add downloading links from zenodo
* move place of LoveDA and Cityscapes in doc
* move place of LoveDA and Cityscapes in doc
Co-authored-by: MengzhangLI <mcmong@pku.edu.cn>
Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
* Add support for Pascal Context 59 classes (#459)
* Create PascalContextDataset59 class in mmseg/datasets/pascal_context.py;
* Set reduce_zero_label=True for train_pipeline and PascalContextDataset59;
* Add some configs for Pascal-Context 59 classes training and testing;
* Try to solve the problem about "fence(IoU)=nan grass(IoU)=0";
* Continue(1): Try to solve the problem about "fence(IoU)=nan grass(IoU)=0";
* ignore files and folders named tempxxx;
* Continue(2): Try to solve the problem about "fence(IoU)=nan grass(IoU)=0";
* Modify the calculation of IoU;
* Modify the CLASSES order of PascalContextDataset;
* Add "fcn", "deeplabv3", "deeplabv3+", "pspnet" config file for model training based on PascalContextDataset59;
Add some ignore items in ".gitignore";
* fix the bug "test_cfg specified in both outer field and model field " of pspnet config file;
* * Clean unnecessary codes;
* Add weighs link, config link, log link and evaluation results about PascalContextDataset59 in README.md
* Add command line argument: "-p | --port", this arg can change the transmit port when you transmit data to distributed machine.
* * Remove rebundant config files;
* Remove "-p|--port" command argument;
Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com>
* Add Pascal Context to mmsegmentation
* Add benchmark result to Pascal Context
* fix mmcv version
* fix code syntax
* fix code syntax again
* Update mmseg/models/segmentors/encoder_decoder.py
update hint
Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
* update comment
* fix pascal context model path
* fix model path mistake again
* fix model path mistake again
* fix model path mistakes again
Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
