Bump version to v1.0.0rc0 (#464)
* update requirement * update readme * update readme * update link * update version * update zh_cn readme * update links * update get started * update dockerfile * fix lint * add mmengine * refine * fix typo * refine * fix lint * update * update * fix lint * update version * fix lint * fix indent Co-authored-by: Jiahao Xie <52497952+Jiahao000@users.noreply.github.com>pull/467/head v1.0.0rc0
Yixiao Fang
GitHub
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README.md
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README.md
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@ -19,16 +19,16 @@
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<div> </div>
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[](https://pypi.org/project/mmselfsup)
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[](https://mmselfsup.readthedocs.io/en/latest/)
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[](https://mmselfsup.readthedocs.io/en/dev-1.x/)
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[](https://github.com/open-mmlab/mmselfsup/actions)
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[](https://codecov.io/gh/open-mmlab/mmselfsup)
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[](https://github.com/open-mmlab/mmselfsup/blob/master/LICENSE)
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[](https://github.com/open-mmlab/mmselfsup/issues)
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[📘Documentation](https://mmselfsup.readthedocs.io/en/latest/) |
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[🛠️Installation](https://mmselfsup.readthedocs.io/en/latest/install.html) |
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[👀Model Zoo](https://github.com/open-mmlab/mmselfsup/blob/master/docs/en/model_zoo.md) |
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[🆕Update News](https://mmselfsup.readthedocs.io/en/latest/changelog.html) |
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[📘Documentation](https://mmselfsup.readthedocs.io/en/dev-1.x/) |
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[🛠️Installation](https://mmselfsup.readthedocs.io/en/dev-1.x/get_started.html) |
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[👀Model Zoo](https://mmselfsup.readthedocs.io/en/dev-1.x/model_zoo.html) |
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[🆕Update News](https://mmselfsup.readthedocs.io/en/dev-1.x/notes/changelog.html) |
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[🤔Reporting Issues](https://github.com/open-mmlab/mmselfsup/issues/new/choose)
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</div>
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@ -43,7 +43,7 @@ English | [简体中文](README_zh-CN.md)
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MMSelfSup is an open source self-supervised representation learning toolbox based on PyTorch. It is a part of the [OpenMMLab](https://openmmlab.com/) project.
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The master branch works with **PyTorch 1.5** or higher.
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The master branch works with **PyTorch 1.6** or higher.
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### Major features
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@ -65,64 +65,71 @@ The master branch works with **PyTorch 1.5** or higher.
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## What's New
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MMSelfSup **v0.9.1** was released in 31/05/2022.
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MMSelfSup **v1.0.0rc0** was released in 01/09/2022.
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Highlights of the new version:
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- Based on MMEngine and MMCV.
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- Released with refactor.
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- Refine all documents.
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- Refactor the data pipeline, which is more powerful.
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- Update **BYOL** model and results
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- Refine some documentation
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Please refer to [Changelog](https://mmselfsup.readthedocs.io/en/dev-1.x/notes/changelog.html) for details and release history.
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Please refer to [changelog.md](docs/en/changelog.md) for details and release history.
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Differences between MMSelfSup and OpenSelfSup codebases can be found in [compatibility.md](docs/en/compatibility.md).
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Differences between MMSelfSup 1.x and 0.x can be found in [Migration](https://mmselfsup.readthedocs.io/en/dev-1.x/migration.html).
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## Installation
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MMSelfSup depends on [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv) and [MMClassification](https://github.com/open-mmlab/mmclassification).
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MMSelfSup depends on [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv), [MMEngine](https://github.com/open-mmlab/mmengine) and [MMClassification](https://github.com/open-mmlab/mmclassification).
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Please refer to [install.md](docs/en/install.md) for more detailed instruction.
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Please refer to [Installation](https://mmselfsup.readthedocs.io/en/dev-1.x/get_started.html) for more detailed instruction.
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## Get Started
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Please refer to [prepare_data.md](docs/en/prepare_data.md) for dataset preparation and [get_started.md](docs/en/get_started.md) for the basic usage of MMSelfSup.
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For tutorials, we provide [User Guides](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/index.html) for basic usage:
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We also provides tutorials for more details:
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Pretrain
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- [config](docs/en/tutorials/0_config.md)
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- [add new dataset](docs/en/tutorials/1_new_dataset.md)
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- [data pipeline](docs/en/tutorials/2_data_pipeline.md)
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- [add new module](docs/en/tutorials/3_new_module.md)
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- [customize schedules](docs/en/tutorials/4_schedule.md)
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- [customize runtime](docs/en/tutorials/5_runtime.md)
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- [benchmarks](docs/en/tutorials/6_benchmarks.md)
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- [Config](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/1_config.html)
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- [Prepare Dataset](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/2_dataset_prepare.html)
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- [Pretrain with Existing Models](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/3_pretrain.html)
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Besides, we provide [colab tutorial](https://github.com/open-mmlab/mmselfsup/blob/master/demo/mmselfsup_colab_tutorial.ipynb) for basic usage.
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Downetream Tasks
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Please refer to [FAQ](docs/en/faq.md) for frequently asked questions.
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- [Classification](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/classification.html)
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- [Detection](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/detection.html)
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- [Segmentation](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/segmentation.html)
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Useful Tools
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- [Visualization](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/visualization.html)
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- [Analysis Tools](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/analysis_tools.html)
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[Advanced Guides](https://mmselfsup.readthedocs.io/en/dev-1.x/advanced_guides/index.html) and [Colab Tutorials](https://github.com/open-mmlab/mmselfsup/blob/dev-1.x/demo/mmselfsup_colab_tutorial.ipynb) are also provided.
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Please refer to [FAQ](https://mmselfsup.readthedocs.io/en/dev-1.x/notes/faq.html) for frequently asked questions.
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## Model Zoo
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Please refer to [model_zoo.md](docs/en/model_zoo.md) for a comprehensive set of pre-trained models and benchmarks.
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Please refer to [Model Zoo.md](https://mmselfsup.readthedocs.io/en/dev-1.x/model_zoo.html) for a comprehensive set of pre-trained models and benchmarks.
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Supported algorithms:
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- [x] [Relative Location (ICCV'2015)](https://arxiv.org/abs/1505.05192)
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- [x] [Rotation Prediction (ICLR'2018)](https://arxiv.org/abs/1803.07728)
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- [x] [DeepCluster (ECCV'2018)](https://arxiv.org/abs/1807.05520)
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- [x] [NPID (CVPR'2018)](https://arxiv.org/abs/1805.01978)
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- [x] [ODC (CVPR'2020)](https://arxiv.org/abs/2006.10645)
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- [x] [MoCo v1 (CVPR'2020)](https://arxiv.org/abs/1911.05722)
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- [x] [SimCLR (ICML'2020)](https://arxiv.org/abs/2002.05709)
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- [x] [MoCo v2 (ArXiv'2020)](https://arxiv.org/abs/2003.04297)
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- [x] [BYOL (NeurIPS'2020)](https://arxiv.org/abs/2006.07733)
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- [x] [SwAV (NeurIPS'2020)](https://arxiv.org/abs/2006.09882)
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- [x] [DenseCL (CVPR'2021)](https://arxiv.org/abs/2011.09157)
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- [x] [SimSiam (CVPR'2021)](https://arxiv.org/abs/2011.10566)
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- [x] [Barlow Twins (ICML'2021)](https://arxiv.org/abs/2103.03230)
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- [x] [MoCo v3 (ICCV'2021)](https://arxiv.org/abs/2104.02057)
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- [x] [MAE](https://arxiv.org/abs/2111.06377)
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- [x] [SimMIM](https://arxiv.org/abs/2111.09886)
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- [x] [CAE](https://arxiv.org/abs/2202.03026)
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- [x] [Relative Location (ICCV'2015)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/relavive_loc)
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- [x] [Rotation Prediction (ICLR'2018)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/rotation_pred)
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- [x] [DeepCluster (ECCV'2018)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/deepcluster)
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- [x] [NPID (CVPR'2018)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/npid)
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- [x] [ODC (CVPR'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/odc)
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- [x] [MoCo v1 (CVPR'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/mocov1)
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- [x] [SimCLR (ICML'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/simclr)
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- [x] [MoCo v2 (ArXiv'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/byol)
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- [x] [BYOL (NeurIPS'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/mocov2)
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- [x] [SwAV (NeurIPS'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/swav)
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- [x] [DenseCL (CVPR'2021)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/densecl)
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- [x] [SimSiam (CVPR'2021)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/simsiam)
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- [x] [Barlow Twins (ICML'2021)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/barlowtwins)
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- [x] [MoCo v3 (ICCV'2021)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/mocov3)
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- [x] [MAE (CVPR'2022)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/mae)
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- [x] [SimMIM (CVPR'2022)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/simmim)
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- [x] [CAE (ArXiv'2022)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/cae)
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More algorithms are in our plan.
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## Contributing
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We appreciate all contributions improving MMSelfSup. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for more details about the contributing guideline.
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We appreciate all contributions improving MMSelfSup. Please refer to [Contribution Guides](https://mmselfsup.readthedocs.io/en/dev-1.x/notes/contribution_guide.html) for more details about the contributing guideline.
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## Acknowledgement
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@ -172,6 +179,7 @@ This project is released under the [Apache 2.0 license](LICENSE).
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## Projects in OpenMMLab
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- [MMEngine](https://github.com/open-mmlab/mmengine): OpenMMLab foundational library for training deep learning models.
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- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision.
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- [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages.
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- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark.
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<div> </div>
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[](https://pypi.org/project/mmselfsup)
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[](https://mmselfsup.readthedocs.io/en/latest/)
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[](https://mmselfsup.readthedocs.io/en/dev-1.x/)
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[](https://github.com/open-mmlab/mmselfsup/actions)
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[](https://codecov.io/gh/open-mmlab/mmselfsup)
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[](https://github.com/open-mmlab/mmselfsup/blob/master/LICENSE)
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[](https://github.com/open-mmlab/mmselfsup/issues)
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[📘使用文档](https://mmselfsup.readthedocs.io/zh_CN/latest/) |
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[🛠️安装教程](https://mmselfsup.readthedocs.io/zh_CN/latest/install.html) |
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[👀模型库](https://github.com/open-mmlab/mmselfsup/blob/master/docs/zh_cn/model_zoo.md) |
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[🆕更新日志](https://mmselfsup.readthedocs.io/zh_CN/latest/changelog.html) |
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[📘使用文档](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/) |
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[🛠️安装教程](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/get_started.html) |
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[👀模型库](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/model_zoo.html) |
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[🆕更新日志](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/notes/changelog.html) |
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[🤔报告问题](https://github.com/open-mmlab/mmselfsup/issues/new/choose)
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</div>
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MMSelfSup 是一个基于 PyTorch 实现的开源自监督表征学习工具箱，是 [OpenMMLab](https://openmmlab.com/) 项目成员之一。
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主分支代码支持 **PyTorch 1.5** 及以上的版本。
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主分支代码支持 **PyTorch 1.6** 及以上的版本。
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### 主要特性
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@ -65,64 +65,73 @@ MMSelfSup 是一个基于 PyTorch 实现的开源自监督表征学习工具箱
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## 更新
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最新的 **v0.9.1** 版本已经在 2022.05.31 发布。
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最新的 **v1.0.0rc0** 版本已经在 2022.09.01 发布。
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新版本亮点：
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- 更新 **BYOL** 模型和结果
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- 更新优化部分文档
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- 基于 MMEngine 和 MMCV
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- 全面代码重构
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- 文档更新
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- 更强大的数据流
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请参考 [更新日志](docs/zh_cn/changelog.md) 获取更多细节和历史版本信息。
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请参考 [更新日志](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/notes/changelog.html) 获取更多细节和历史版本信息。
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MMSelfSup 和 OpenSelfSup 的不同点写在 [对比文档](docs/en/compatibility.md) 中。
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MMSelfSup 1.x 和 0.x 的不同点写在 [迁移文档](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/migration.html) 中。
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## 安装
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MMSelfSup 依赖 [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv) 和 [MMClassification](https://github.com/open-mmlab/mmclassification).
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MMSelfSup 依赖 [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv), [MMEngine](https://github.com/open-mmlab/mmengine) 和 [MMClassification](https://github.com/open-mmlab/mmclassification)。
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请参考 [安装文档](docs/zh_cn/install.md) 获取更详细的安装指南。
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请参考 [安装文档](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/get_started.html) 获取更详细的安装指南。
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## 快速入门
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请参考 [准备数据](docs/zh_cn/prepare_data.md) 准备数据集和 [入门指南](docs/zh_cn/get_started.md) 获取 MMSelfSup 的基本使用方法.
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我们针对基础使用和进阶用法提供了 [用户指引](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/user_guides/index.html)：
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我们也提供了更加全面的教程，包括:
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Pretrain
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- [配置文件](docs/zh_cn/tutorials/0_config.md)
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- [添加数据集](docs/zh_cn/tutorials/1_new_dataset.md)
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- [数据处理流](docs/zh_cn/tutorials/2_data_pipeline.md)
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- [添加新模块](docs/zh_cn/tutorials/3_new_module.md)
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- [自定义流程](docs/zh_cn/tutorials/4_schedule.md)
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- [自定义运行](docs/zh_cn/tutorials/5_runtime.md)
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- [基准测试](docs/zh_cn/tutorials/6_benchmarks.md)
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- [Config](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/user_guides/1_config.html)
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- [Prepare Dataset](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/user_guides/2_dataset_prepare.html)
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- [Pretrain with Existing Models](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/user_guides/3_pretrain.html)
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另外，我们提供了 [colab 教程](https://github.com/open-mmlab/mmselfsup/blob/master/demo/mmselfsup_colab_tutorial.ipynb)。
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Downetream Tasks
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如果遇到问题，请参考 [常见问题解答](docs/zh_cn/faq.md)。
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- [Classification](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/user_guides/classification.html)
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- [Detection](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/user_guides/detection.html)
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- [Segmentation](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/user_guides/segmentation.html)
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Useful Tools
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- [Visualization](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/user_guides/visualization.html)
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- [Analysis Tools](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/user_guides/analysis_tools.html)
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我们也提供了 [进阶指引](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/advanced_guides/index.html) 和 [Colab 教程](https://github.com/open-mmlab/mmselfsup/blob/master/demo/mmselfsup_colab_tutorial.ipynb)。
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如果遇到问题，请参考 [常见问题解答](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/notes/faq.html)。
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## 模型库
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请参考 [模型库](docs/zh_cn/model_zoo.md) 查看我们更加全面的模型基准结果。
|
||||
请参考 [模型库](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/model_zoo.html) 查看我们更加全面的模型基准结果。
|
||||
|
||||
目前已支持的算法:
|
||||
|
||||
- [x] [Relative Location (ICCV'2015)](https://arxiv.org/abs/1505.05192)
|
||||
- [x] [Rotation Prediction (ICLR'2018)](https://arxiv.org/abs/1803.07728)
|
||||
- [x] [DeepCLuster (ECCV'2018)](https://arxiv.org/abs/1807.05520)
|
||||
- [x] [NPID (CVPR'2018)](https://arxiv.org/abs/1805.01978)
|
||||
- [x] [ODC (CVPR'2020)](https://arxiv.org/abs/2006.10645)
|
||||
- [x] [MoCo v1 (CVPR'2020)](https://arxiv.org/abs/1911.05722)
|
||||
- [x] [SimCLR (ICML'2020)](https://arxiv.org/abs/2002.05709)
|
||||
- [x] [MoCo v2 (ArXiv'2020)](https://arxiv.org/abs/2003.04297)
|
||||
- [x] [BYOL (NeurIPS'2020)](https://arxiv.org/abs/2006.07733)
|
||||
- [x] [SwAV (NeurIPS'2020)](https://arxiv.org/abs/2006.09882)
|
||||
- [x] [DenseCL (CVPR'2021)](https://arxiv.org/abs/2011.09157)
|
||||
- [x] [SimSiam (CVPR'2021)](https://arxiv.org/abs/2011.10566)
|
||||
- [x] [Barlow Twins (ICML'2021)](https://arxiv.org/abs/2103.03230)
|
||||
- [x] [MoCo v3 (ICCV'2021)](https://arxiv.org/abs/2104.02057)
|
||||
- [x] [MAE](https://arxiv.org/abs/2111.06377)
|
||||
- [x] [SimMIM](https://arxiv.org/abs/2111.09886)
|
||||
- [x] [CAE](https://arxiv.org/abs/2202.03026)
|
||||
- [x] [Relative Location (ICCV'2015)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/relavive_loc)
|
||||
- [x] [Rotation Prediction (ICLR'2018)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/rotation_pred)
|
||||
- [x] [DeepCluster (ECCV'2018)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/deepcluster)
|
||||
- [x] [NPID (CVPR'2018)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/npid)
|
||||
- [x] [ODC (CVPR'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/odc)
|
||||
- [x] [MoCo v1 (CVPR'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/mocov1)
|
||||
- [x] [SimCLR (ICML'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/simclr)
|
||||
- [x] [MoCo v2 (ArXiv'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/byol)
|
||||
- [x] [BYOL (NeurIPS'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/mocov2)
|
||||
- [x] [SwAV (NeurIPS'2020)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/swav)
|
||||
- [x] [DenseCL (CVPR'2021)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/densecl)
|
||||
- [x] [SimSiam (CVPR'2021)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/simsiam)
|
||||
- [x] [Barlow Twins (ICML'2021)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/barlowtwins)
|
||||
- [x] [MoCo v3 (ICCV'2021)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/mocov3)
|
||||
- [x] [MAE (CVPR'2022)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/mae)
|
||||
- [x] [SimMIM (CVPR'2022)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/simmim)
|
||||
- [x] [CAE (ArXiv'2022)](https://github.com/open-mmlab/mmselfsup/tree/dev-1.x/configs/selfsup/cae)
|
||||
|
||||
更多的算法实现已经在我们的计划中。
|
||||
|
||||
|
|
@ -144,7 +153,7 @@ MMSelfSup 依赖 [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open
|
|||
|
||||
## 参与贡献
|
||||
|
||||
我们非常欢迎任何有助于提升 MMSelfSup 的贡献，请参考 [贡献指南](.github/CONTRIBUTING.md) 来了解如何参与贡献。
|
||||
我们非常欢迎任何有助于提升 MMSelfSup 的贡献，请参考 [贡献指南](https://mmselfsup.readthedocs.io/zh_CN/dev-1.x/notes/contribution_guide.html) 来了解如何参与贡献。
|
||||
|
||||
## 致谢
|
||||
|
||||
|
|
@ -171,6 +180,7 @@ MMSelfSup 是一款由不同学校和公司共同贡献的开源项目，我们
|
|||
|
||||
## OpenMMLab 的其他项目
|
||||
|
||||
- [MMEngine](https://github.com/open-mmlab/mmengine): OpenMMLab 深度学习模型训练基础库
|
||||
- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab 计算机视觉基础库
|
||||
- [MIM](https://github.com/open-mmlab/mim): MIM 是 OpenMMlab 项目、算法、模型的统一入口
|
||||
- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab 图像分类工具箱
|
||||
|
|
|
|||
|
|
@ -12,12 +12,15 @@ RUN apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build
|
|||
&& apt-get clean \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# Install MMCV MMDetection MMSegmentation
|
||||
RUN pip install mmcv-full==1.3.16 -f https://download.openmmlab.com/mmcv/dist/cu113/torch1.10.0/index.html
|
||||
RUN pip install mmsegmentation mmdet
|
||||
# Install MMEngine and MMCV
|
||||
RUN pip install openmim
|
||||
RUN mim install mmengine "mmcv>=2.0.0rc1"
|
||||
RUN mim install mmsegmentation mmdet
|
||||
|
||||
# Install MMSelfSup
|
||||
RUN conda clean --all
|
||||
RUN git clone https://github.com/open-mmlab/mmselfsup.git /mmselfsup
|
||||
WORKDIR /mmselfsup
|
||||
ENV FORCE_CUDA="1"
|
||||
RUN git checkout 1.x
|
||||
RUN pip install --no-cache-dir -e .
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ Data flow defines how data should be passed between two isolated modules, e.g. d
|
|||
|
||||
In MMSelfSup, we mainly focus on the data flow between dataloader and model, and between model and visualizer. As for the
|
||||
data flow between model and metric, please refer to the docs in other repos, e.g. [MMClassification](https://github.com/open-mmlab/mmclassification).
|
||||
Also for data flow between model and visualizer, you can refer to [visualization](../user/guides/visualization.md)
|
||||
Also for data flow between model and visualizer, you can refer to [visualization](../user_guides/visualization.md)
|
||||
|
||||
## Data flow between dataloader and model
|
||||
|
||||
|
|
|
|||
|
|
@ -4,6 +4,8 @@
|
|||
- [Prerequisites](#prerequisites)
|
||||
- [Installation](#installation)
|
||||
- [Best practices](#best-practices)
|
||||
- [Install from source](#install-from-source)
|
||||
- [Install as a Python package](#install-as-a-python-package)
|
||||
- [Verify the installation](#verify-the-installation)
|
||||
- [Customize installation](#customize-installation)
|
||||
- [Benchmark](#benchmark)
|
||||
|
|
@ -189,10 +191,10 @@ To install MMCV with pip instead of MIM, please follow [MMCV installation guides
|
|||
For example, the following command installs mmcv-full built for PyTorch 1.12.0 and CUDA 11.6.
|
||||
|
||||
```shell
|
||||
pip install 'mmcv-full>=2.0.0rc1' -f https://download.openmmlab.com/mmcv/dist/cu116/torch1.12.0/index.html
|
||||
pip install 'mmcv>=2.0.0rc1' -f https://download.openmmlab.com/mmcv/dist/cu116/torch1.12.0/index.html
|
||||
```
|
||||
|
||||
### Install on CPU-only platforms
|
||||
#### Install on CPU-only platforms
|
||||
|
||||
MMSelfSup can be built for CPU only environment. In CPU mode, you can train, test or inference a model.
|
||||
|
||||
|
|
|
|||
|
|
@ -5,7 +5,7 @@
|
|||
### v1.0.0rc0 (01/09/2022)
|
||||
|
||||
We are excited to announce the release of MMSelfSup v1.0.0rc0.
|
||||
MMSelfSup v1.0.0rc0 is the first version of MMSelfSup 1.x, a part of the OpenMMLab 2.x projects.
|
||||
MMSelfSup v1.0.0rc0 is the first version of MMSelfSup 1.x, a part of the OpenMMLab 2.x projects.
|
||||
The `master` branch is still 0.x version and we will checkout a new `1.x` branch to release 1.x version. The two versions will be maintained simultaneously in the future.
|
||||
|
||||
We briefly list the major breaking changes here. Please refer to the [migration guide](../migration.md) for details and migration instructions.
|
||||
|
|
|
|||
|
|
@ -8,20 +8,21 @@ We list some common troubles faced by many users and their corresponding solutio
|
|||
|
||||
## Installation
|
||||
|
||||
Compatible MMCV, MMClassification, MMDetection and MMSegmentation versions are shown below. Please install the correct version of them to avoid installation issues.
|
||||
Compatible MMEngine, MMCV, MMClassification, MMDetection and MMSegmentation versions are shown below. Please install the correct version of them to avoid installation issues.
|
||||
|
||||
| MMSelfSup version | MMCV version | MMClassification version | MMSegmentation version | MMDetection version |
|
||||
| :---------------: | :-----------------: | :-------------------------: | :--------------------: | :-----------------: |
|
||||
| 0.9.1 (master) | mmcv-full >= 1.4.2 | mmcls >= 0.21.0 | mmseg >= 0.20.2 | mmdet >= 2.19.0 |
|
||||
| 0.9.0 | mmcv-full >= 1.4.2 | mmcls >= 0.21.0 | mmseg >= 0.20.2 | mmdet >= 2.19.0 |
|
||||
| 0.8.0 | mmcv-full >= 1.4.2 | mmcls >= 0.21.0 | mmseg >= 0.20.2 | mmdet >= 2.19.0 |
|
||||
| 0.7.1 | mmcv-full >= 1.3.16 | mmcls >= 0.19.0, \<= 0.20.1 | mmseg >= 0.20.2 | mmdet >= 2.16.0 |
|
||||
| 0.6.0 | mmcv-full >= 1.3.16 | mmcls >= 0.19.0 | mmseg >= 0.20.2 | mmdet >= 2.16.0 |
|
||||
| 0.5.0 | mmcv-full >= 1.3.16 | / | mmseg >= 0.20.2 | mmdet >= 2.16.0 |
|
||||
| MMSelfSup version | MMEngine version | MMCV version | MMClassification version | MMSegmentation version | MMDetection version |
|
||||
| :---------------: | :---------------: | :-----------------: | :-------------------------: | :--------------------: | :-----------------: |
|
||||
| 1.0.0rc0 (1.x) | mmengine >= 0.5.0 | mmcv >= 2.0.0rc1 | mmcls >= 1.0.0rc0 | mmseg >= 1.0.0rc0 | mmdet >= 3.0.0rc0 |
|
||||
| 0.9.1 | / | mmcv-full >= 1.4.2 | mmcls >= 0.21.0 | mmseg >= 0.20.2 | mmdet >= 2.19.0 |
|
||||
| 0.9.0 | / | mmcv-full >= 1.4.2 | mmcls >= 0.21.0 | mmseg >= 0.20.2 | mmdet >= 2.19.0 |
|
||||
| 0.8.0 | / | mmcv-full >= 1.4.2 | mmcls >= 0.21.0 | mmseg >= 0.20.2 | mmdet >= 2.19.0 |
|
||||
| 0.7.1 | / | mmcv-full >= 1.3.16 | mmcls >= 0.19.0, \<= 0.20.1 | mmseg >= 0.20.2 | mmdet >= 2.16.0 |
|
||||
| 0.6.0 | / | mmcv-full >= 1.3.16 | mmcls >= 0.19.0 | mmseg >= 0.20.2 | mmdet >= 2.16.0 |
|
||||
| 0.5.0 | / | mmcv-full >= 1.3.16 | / | mmseg >= 0.20.2 | mmdet >= 2.16.0 |
|
||||
|
||||
**Note:**
|
||||
|
||||
- You need to run `pip uninstall mmcv` first if you have mmcv installed. If mmcv and mmcv-full are both installed, there will be `ModuleNotFoundError`.
|
||||
- MMDetection and MMSegmentation are optional.
|
||||
- If you still have version problem, please create an issue and provide your package versions.
|
||||
|
||||
## DeepCluster on A100 GPU
|
||||
|
|
|
|||
|
|
@ -3,7 +3,9 @@
|
|||
- [Overview](#overview)
|
||||
- [Introduction of Self-supervised Learning](#introduction-of-self-supervised-learning)
|
||||
- [Design of MMSelfSup](#design-of-mmselfsup)
|
||||
- [Hands-on Roadmap of MMselfSup](#hands-on-roadmap-of-mmselfsup)
|
||||
- [Hands-on Roadmap of MMSelfSup](#hands-on-roadmap-of-mmselfsup)
|
||||
- [Play with MMSelfSup](#play-with-mmselfsup)
|
||||
- [Learn SSL with MMSelfSup](#learn-ssl-with-mmselfsup)
|
||||
|
||||
In this section, We would like to give a quick review of the open-source library [MMSelfSup](https://github.com/open-mmlab/mmselfsup).
|
||||
|
||||
|
|
@ -38,12 +40,12 @@ Typically, SSL is considered as the pre-training algorithm for various model arc
|
|||
|
||||
- For the user who wants to try MMSelfSup with various SSL algorithms. We first refer the user to [Get Started](./get_started.md) for the **environment setup**.
|
||||
|
||||
- For the pre-training stage, we refer the user to [Pre-train](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/#pretrain) for using various SSL algorithms to obtain the pre-trained model.
|
||||
- For the pre-training stage, we refer the user to [Pre-train](user_guides/3_pretrain.md) for using various SSL algorithms to obtain the pre-trained model.
|
||||
|
||||
- For the benchmark stage, we refer the user to [Benchmark](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/#downstream-tasks) for examples and usage of applying the pre-trained models in many downstream tasks.
|
||||
|
||||
- Also, we provide some analysis tools and visualization tools [Useful Tools](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/#downstream-tasks) to help diagnose the algorithm.
|
||||
- Also, we provide some analysis tools and visualization tools [Useful Tools](https://mmselfsup.readthedocs.io/en/dev-1.x/user_guides/#useful-tools) to help diagnose the algorithm.
|
||||
|
||||
### Learn SSL with MMSelfSup
|
||||
|
||||
If you are new to SSL, we recommend using the [Model Zoo](https://mmselfsup.readthedocs.io/en/dev-1.x/model_zoo.html) as a reference to learn the representative SSL algorithms.
|
||||
If you are new to SSL, we recommend using the [Model Zoo](model_zoo.md) as a reference to learn the representative SSL algorithms.
|
||||
|
|
|
|||
|
|
@ -5,11 +5,12 @@ from mmengine.utils import digit_version
|
|||
|
||||
from .version import __version__
|
||||
|
||||
mmcv_minimum_version = '2.0.0rc0'
|
||||
mmcv_minimum_version = '2.0.0rc1'
|
||||
mmcv_maximum_version = '2.1.0'
|
||||
mmcv_version = digit_version(mmcv.__version__)
|
||||
|
||||
mmcls_minimum_version = '1.0.0rc0'
|
||||
mmcls_maximum_version = '1.1.0'
|
||||
mmcls_version = digit_version(mmcls.__version__)
|
||||
|
||||
|
||||
|
|
@ -18,8 +19,9 @@ assert (mmcv_version >= digit_version(mmcv_minimum_version)
|
|||
f'MMCV=={mmcv.__version__} is used but incompatible. ' \
|
||||
f'Please install mmcv>={mmcv_minimum_version}, <{mmcv_maximum_version}.'
|
||||
|
||||
assert mmcls_version >= digit_version(mmcls_minimum_version), \
|
||||
assert (mmcls_version >= digit_version(mmcls_minimum_version)
|
||||
and mmcls_version < digit_version(mmcls_maximum_version)), \
|
||||
f'MMClassification=={mmcls.__version__} is used but incompatible. ' \
|
||||
f'Please install mmcls>={mmcls_minimum_version}.'
|
||||
f'Please install mmcls>={mmcls_minimum_version}, <{mmcls_maximum_version}.'
|
||||
|
||||
__all__ = ['__version__']
|
||||
|
|
|
|||
|
|
@ -2,7 +2,6 @@
|
|||
from typing import Dict, List, Optional, Tuple, Union
|
||||
|
||||
import torch
|
||||
import torch.nn as nn
|
||||
from mmengine.device import get_device
|
||||
from mmengine.structures import LabelData
|
||||
|
||||
|
|
|
|||
|
|
@ -4,7 +4,6 @@ myst_parser
|
|||
-e git+https://github.com/open-mmlab/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
|
||||
recommonmark
|
||||
sphinx==4.0.2
|
||||
sphinx==4.0.2
|
||||
sphinx-copybutton
|
||||
sphinx_markdown_tables>=0.0.16
|
||||
sphinx_rtd_theme==0.5.2
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
mmcls >= 0.21.0
|
||||
mmcv-full>=1.4.2
|
||||
mmdet >= 2.16.0
|
||||
mmsegmentation >= 0.20.2
|
||||
mmcls>=1.0.0rc0,<1.1.0
|
||||
mmcv>=2.0.0rc1,<2.1.0
|
||||
mmdet>=3.0.0rc0,<3.1.0
|
||||
mmengine>=0.1.0
|
||||
mmsegmentation>=1.0.0rc0,<1.1.0
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
faiss-cpu
|
||||
mmcv>=1.4.2
|
||||
mmcls
|
||||
mmcv>=2.0.0rc1
|
||||
mmengine
|
||||
mmselfsup
|
||||
scikit-learn
|
||||
torch
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
attrs
|
||||
future
|
||||
matplotlib
|
||||
mmcls
|
||||
mmcls>=2.0.0rc0
|
||||
numpy
|
||||
packaging
|
||||
scikit-learn
|
||||
|
|
|
|||
Loading…
Reference in New Issue