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## Motivation
Fix uprenet config issue in readme.
## Modification
Fix npu.md.
## BC-breaking (Optional)
None.
## Use cases (Optional)
None.
## Checklist
1. Pre-commit or other linting tools are used to fix the potential lint
issues.
2. The modification is covered by complete unit tests. If not, please
add more unit test to ensure the correctness.
3. If the modification has potential influence on downstream projects,
this PR should be tested with downstream projects, like MMDet or
MMDet3D.
4. The documentation has been modified accordingly, like docstring or
example tutorials.
## 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
* [Feature] Add model ensemble tool
* [Enhance] Add en and zh_cn instructions for model_ensemble
* [Enhance] Add default-value for --out and modify instruction
* [Enhance] Add arg-type for --out
* [Enhance] Delete redundant code
* logger hooks samples updated
* [Docs] Details for WandBLoggerHook Added
* [Docs] lint test pass
* [Enhancement] .dev Python files updated to get better performance and quality
* [Docs] Details for WandBLoggerHook Added
* [Docs] lint test pass
* [Enhancement] .dev Python files updated to get better performance and quality
* [Enhancement] lint test passed
* [Enhancement] Change Some Line from Previous to Support Python<3.9
* Update .dev/gather_models.py
Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com>
* Update Dockerfile
Compatible with the latest version of MMCV and PyTorch for compatibility with Python3.10
* Update Dockerfile for serve
Compatible with the latest version of MMCV and PyTorch for compatibility with Python3.10
* Updating to the last version of supported Python
* Update Dockerfile
* Update get_started.md
* Update docs/zh_cn/get_started.md
Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com>
Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com>
* [Fix] Add avg_non_ignore in cross entropy loss
* [Fix] Add avg_non_ignore in cross entropy loss
* add docstring
* fix ut
* fix docstring and comments
* fix
* fix bce
* fix avg_factor in BCE and add more ut
* add avg_non_ignore
* add more ut
* fix part of ut
* fix part of ut
* test avg_non_ignore would not affect ce/bce when reduction none/sum
* test avg_non_ignore would not affect ce/bce when reduction none/sum/mean
* re-organize ut
* re-organize ut
* re-organize ut
* re-organize hardcode case
* fix parts of comments
* fix another parts of comments
* fix
* change version to v0.22.0
* change version to v0.22.0
* add mmcls version in get_started.md
* add mmcls installation and move PR1299 into enhancement
* add mmcls installation and move PR1299 into enhancement
* remove MMCLS and make mmcv <=1.5.0 version in get_started.md
* fix typo
* 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>
1. Fix img path typo in `useful_tools.md`, `zh_cn/model_zoo.md`, and `zh_cn/train.md`
2. Add missing content in `zh_cn/useful_tools.md` to to match `en/useful_tools.md`
* [Enhance] New-style CPU training and inference.
* assert mmcv version
* SyncBN to BN in training and testing
* SyncBN to BN in training and testing
* upload untracked files to this branch
* delete gpu_ids
* fix bugs
* assert args.gpu_id in train.py
* use cfg.gpu_ids = [args.gpu_id]
* use cfg.gpu_ids = [args.gpu_id]
* fix typo
* fix typo
* fix typos
