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Bump to v0.13.0 (#536)
* bump to v0.13.0 * fix ci * fix docker
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.github/workflows/build.yml

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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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- name: Fetch GPG keys
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run: |
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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# Add ppa source repo for python3.9.
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- name: Add python3.9 source
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run: |
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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- name: Fetch GPG keys
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run: |
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
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apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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# Add ppa source repo for python3.9.
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- name: Add python3.9 source
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run: |

README.md

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Release [QDTrack](configs/mot/qdtrack) pretrained models.
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v0.12.0 was released in 01/04/2022.
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v0.13.0 was released in 29/04/2022.
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Please refer to [changelog.md](docs/en/changelog.md) for details and release history.
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## Benchmark and model zoo
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## Getting Started
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Please see [dataset.md](docs/en/dataset.md) and [quick_run.md](docs/en/quick_run.md) for the basic usage of MMTracking.
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We also provide usage [tutorials](docs/en/tutorials/), such as [learning about configs](docs/en/tutorials/config.md), [an example about detailed description of vid config](docs/en/tutorials/config_vid.md), [an example about detailed description of mot config](docs/en/tutorials/config_mot.md), [an example about detailed description of sot config](docs/en/tutorials/config_sot.md), [customizing dataset](docs/en/tutorials/customize_dataset.md), [customizing data pipeline](docs/en/tutorials/customize_data_pipeline.md), [customizing vid model](docs/en/tutorials/customize_vid_model.md), [customizing mot model](docs/en/tutorials/customize_mot_model.md), [customizing sot model](docs/en/tutorials/customize_sot_model.md), [customizing runtime settings](docs/en/tutorials/customize_runtime.md) and [useful tools](docs/en/useful_tools_scripts.md).
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Please see [dataset.md](docs/en/dataset.md) and [quick_run.md](docs/en/quick_run.md) for the basic usage of MMTracking. We also provide [tracking colab tutorial](./demo/MMTracking_Tutorial.ipynb).
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There are also usage [tutorials](docs/en/tutorials/), such as [learning about configs](docs/en/tutorials/config.md), [an example about detailed description of vid config](docs/en/tutorials/config_vid.md), [an example about detailed description of mot config](docs/en/tutorials/config_mot.md), [an example about detailed description of sot config](docs/en/tutorials/config_sot.md), [customizing dataset](docs/en/tutorials/customize_dataset.md), [customizing data pipeline](docs/en/tutorials/customize_data_pipeline.md), [customizing vid model](docs/en/tutorials/customize_vid_model.md), [customizing mot model](docs/en/tutorials/customize_mot_model.md), [customizing sot model](docs/en/tutorials/customize_sot_model.md), [customizing runtime settings](docs/en/tutorials/customize_runtime.md) and [useful tools](docs/en/useful_tools_scripts.md).
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## Contributing
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README_zh-CN.md

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## 更新记录
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v0.12.0版本已于2022年04月01日发布,可通过查阅[更新日志](docs/en/changelog.md)了解更多细节以及发布历史。
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v0.13.0版本已于2022年04月29日发布,可通过查阅[更新日志](docs/en/changelog.md)了解更多细节以及发布历史。
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## 基准测试与模型库
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## 开始使用MMTracking
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请参考[数据集](docs/en/dataset.md)[快速开始](docs/en/quick_run.md)了解MMTracking的基本使用。MMTracking也提供了更详细的[教程](docs/en/tutorials/),比如[配置文件简介](docs/en/tutorials/config.md), [视频目标检测器配置文件详解](docs/en/tutorials/config_vid.md), [多目标跟踪器配置文件详解](docs/en/tutorials/config_mot.md), [单目标跟踪器配置文件详解](docs/en/tutorials/config_sot.md), [自定义数据集](docs/en/tutorials/customize_dataset.md), [自定义数据预处理流程](docs/en/tutorials/customize_data_pipeline.md), [自定义视频目标检测器](docs/en/tutorials/customize_vid_model.md), [自定义多目标跟踪器](docs/en/tutorials/customize_mot_model.md), [自定义单目标跟踪器](docs/en/tutorials/customize_sot_model.md), [自定义训练配置](docs/en/tutorials/customize_runtime.md) 以及 [有用的工具和脚本](docs/en/useful_tools_scripts.md).
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请参考[数据集](docs/en/dataset.md)[快速开始](docs/en/quick_run.md)了解MMTracking的基本使用。我们也提供了[跟踪的colab教程](./demo/MMTracking_Tutorial.ipynb)
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MMTracking也提供了更详细的[教程](docs/en/tutorials/),比如[配置文件简介](docs/en/tutorials/config.md), [视频目标检测器配置文件详解](docs/en/tutorials/config_vid.md), [多目标跟踪器配置文件详解](docs/en/tutorials/config_mot.md), [单目标跟踪器配置文件详解](docs/en/tutorials/config_sot.md), [自定义数据集](docs/en/tutorials/customize_dataset.md), [自定义数据预处理流程](docs/en/tutorials/customize_data_pipeline.md), [自定义视频目标检测器](docs/en/tutorials/customize_vid_model.md), [自定义多目标跟踪器](docs/en/tutorials/customize_mot_model.md), [自定义单目标跟踪器](docs/en/tutorials/customize_sot_model.md), [自定义训练配置](docs/en/tutorials/customize_runtime.md) 以及 [有用的工具和脚本](docs/en/useful_tools_scripts.md).
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## 参与贡献
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docker/Dockerfile

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ENV TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
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ENV CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"
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# To fix GPG key error when running apt-get update
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
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RUN apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/*

docs/en/changelog.md

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## Changelog
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### v0.13.0 (29/04/2022)
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#### Highlights
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- Support tracking colab tutorial ([#511](https://github.com/open-mmlab/mmtracking/pull/511))
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#### New Features
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- Refactor the training datasets of SiamRPN++ ([#496](https://github.com/open-mmlab/mmtracking/pull/496)), ([#518](https://github.com/open-mmlab/mmtracking/pull/518))
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- Support loading data from ceph for SOT datasets ([#494](https://github.com/open-mmlab/mmtracking/pull/494))
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- Support loading data from ceph for MOT challenge dataset ([#517](https://github.com/open-mmlab/mmtracking/pull/517))
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- Support evaluation metric for VIS task ([#501](https://github.com/open-mmlab/mmtracking/pull/501))
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#### Bug Fixes
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- Fix a bug in the LaSOT datasets and update the pretrained models of STARK ([#483](https://github.com/open-mmlab/mmtracking/pull/483)), ([#503](https://github.com/open-mmlab/mmtracking/pull/503))
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- Fix a bug in the format_results function of VIS task ([#504](https://github.com/open-mmlab/mmtracking/pull/504))
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### v0.12.0 (01/04/2022)
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#### Highlights

docs/en/install.md

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| MMTracking version | MMCV version | MMDetection version |
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|:-------------------:|:------------------------:|:-----------------------------:|
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| master | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| master | mmcv-full>=1.3.17, <1.6.0 | MMDetection>=2.19.1 |
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| 0.13.0 | mmcv-full>=1.3.17, <1.6.0 | MMDetection>=2.19.1 |
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| 0.12.0 | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| 0.11.0 | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| 0.10.0 | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |

docs/zh_cn/install.md

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| MMTracking version | MMCV version | MMDetection version |
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| master | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| master | mmcv-full>=1.3.17, <1.6.0 | MMDetection>=2.19.1 |
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| 0.13.0 | mmcv-full>=1.3.17, <1.6.0 | MMDetection>=2.19.1 |
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| 0.12.0 | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| 0.11.0 | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| 0.10.0 | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |

mmtrack/version.py

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# Copyright (c) Open-MMLab. All rights reserved.
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__version__ = '0.12.0'
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__version__ = '0.13.0'
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def parse_version_info(version_str):

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