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Bump to v0.9.0 (#389)
* Bump to v0.9.0 * Update runtime.txt * Update runtime.txt * Update runtime.txt * Update runtime.txt * Update build.yml * Update build.yml * Update build.yml * Update runtime.txt
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‎.dev_scripts/benchmark/batch_train_list.txt

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@@ -7,6 +7,7 @@ configs/vid/temporal_roi_align/selsa_troialign_faster_rcnn_r50_dc5_7e_imagenetvi
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# MOT
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configs/mot/deepsort/deepsort_faster-rcnn_fpn_4e_mot17-private-half.py
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configs/mot/tracktor/tracktor_faster-rcnn_r50_fpn_4e_mot17-private-half.py
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configs/mot/bytetrack/bytetrack_yolox_x_crowdhuman_mot17-private-half.py
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# SOT
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configs/sot/siamese_rpn/siamese_rpn_r50_1x_lasot.py

‎.dev_scripts/benchmark/gather_train_benchmark_metric.py

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@@ -130,14 +130,13 @@ def parse_args():
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0]] < result_dict[epoch][eval_metrics[0]]:
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best_epoch_results = result_dict[epoch]
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for metric in best_epoch_results:
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if 'success' in best_epoch_results:
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performance = round(best_epoch_results[metric],
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1)
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else:
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performance = round(
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best_epoch_results[metric] * 100, 1)
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best_epoch_results[metric] = performance
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for metric in best_epoch_results:
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if 'success' in best_epoch_results:
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performance = round(best_epoch_results[metric], 1)
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else:
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performance = round(
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best_epoch_results[metric] * 100, 1)
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best_epoch_results[metric] = performance
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all_results_dict[config] = best_epoch_results
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# update and append excel content

‎.dev_scripts/benchmark/train_benchmark.sh

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@@ -22,6 +22,18 @@ WORK_DIR=selsa_troialign_faster_rcnn_r50_dc5_7e_imagenetvid
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echo ${CONFIG} &
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./tools/slurm_train.sh ${PARTITION} ${WORK_DIR} ${CONFIG} ${ROOT_DIR}/${WORK_DIR} 8 --cfg-options checkpoint_config.max_keep_ckpts=1 >/dev/null &
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# MOT
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CONFIG=configs/mot/bytetrack/bytetrack_yolox_x_crowdhuman_mot17-private-half.py
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WORK_DIR=bytetrack_yolox_x_crowdhuman_mot17-private-half
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echo ${CONFIG} &
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./tools/slurm_train.sh ${PARTITION} ${WORK_DIR} ${CONFIG} ${ROOT_DIR}/${WORK_DIR} 8 --cfg-options checkpoint_config.max_keep_ckpts=1 >/dev/null &
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# VIS
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CONFIG=configs/vis/masktrack_rcnn/masktrack_rcnn_r50_fpn_12e_youtubevis2019.py
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WORK_DIR=masktrack_rcnn_r50_fpn_12e_youtubevis2019
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echo ${CONFIG} &
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./tools/slurm_train.sh ${PARTITION} ${WORK_DIR} ${CONFIG} ${ROOT_DIR}/${WORK_DIR} 8 --cfg-options checkpoint_config.max_keep_ckpts=1 >/dev/null &
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# SOT
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CONFIG=configs/sot/siamese_rpn/siamese_rpn_r50_1x_lasot.py
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WORK_DIR=siamese_rpn_r50_1x_lasot
@@ -48,3 +60,9 @@ CONFIG=configs/mot/tracktor/tracktor_faster-rcnn_r50_fpn_4e_mot17-private-half.p
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WORK_DIR=tracktor_faster-rcnn_r50_fpn_4e_mot17-private-half
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echo ${CONFIG}
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./tools/slurm_test.sh ${PARTITION} ${WORK_DIR} ${CONFIG} 8 --work-dir ${ROOT_DIR}/${WORK_DIR} --eval track --cfg-options model.detector.init_cfg.checkpoint=${ROOT_DIR}/${DET_WORK_DIR}/epoch_4.pth model.reid.init_cfg.checkpoint=${ROOT_DIR}/${REID_WORK_DIR}/epoch_6.pth
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# VIS
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CONFIG=configs/vis/masktrack_rcnn/masktrack_rcnn_r50_fpn_12e_youtubevis2019.py
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WORK_DIR=masktrack_rcnn_r50_fpn_12e_youtubevis2019
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echo ${CONFIG}
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./tools/slurm_test.sh ${PARTITION} ${WORK_DIR} ${CONFIG} 8 --eval-options resfile_path=${ROOT_DIR}/${WORK_DIR} --format-only --checkpoint ${ROOT_DIR}/${WORK_DIR}/epoch_12.pth

‎.github/workflows/build.yml

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@@ -50,10 +50,10 @@ jobs:
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run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
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- name: Install mmtrack dependencies
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run: |
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pip install git+https://github.com/votchallenge/toolkit.git
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pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cpu/${{matrix.torch_version}}/index.html
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pip install mmdet
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pip install -r requirements.txt
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pip install git+https://github.com/votchallenge/toolkit.git
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- name: Build and install
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run: rm -rf .eggs && pip install -e .
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- name: Run unittests and generate coverage report
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run: python -m pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
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- name: Install mmtrack dependencies
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run: |
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python -m pip install git+https://github.com/votchallenge/toolkit.git
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python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/${{matrix.torch_version}}/index.html
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python -m pip install mmdet
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python -m pip install -r requirements.txt
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python -m pip install git+https://github.com/votchallenge/toolkit.git
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- name: Build and install
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run: |
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rm -rf .eggs
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run: python -m pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
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- name: Install mmtrack dependencies
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run: |
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python -m pip install git+https://github.com/votchallenge/toolkit.git
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python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu102/${{matrix.torch_version}}/index.html
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python -m pip install mmdet
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python -m pip install -r requirements.txt
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python -m pip install git+https://github.com/votchallenge/toolkit.git
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- name: Build and install
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run: |
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rm -rf .eggs

‎README.md

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@@ -50,7 +50,7 @@ This project is released under the [Apache 2.0 license](LICENSE).
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Release [ByteTrack](configs/mot/bytetrack) pretrained models.
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v0.8.0 was released in 03/10/2021.
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v0.9.0 was released in 05/01/2022.
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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

‎README_zh-CN.md

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@@ -47,7 +47,7 @@ MMTracking是一款基于PyTorch的视频目标感知开源工具箱，是[OpenM
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## 更新记录
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v0.8.0版本已于2021年10月03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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v0.9.0版本已于2022年01月05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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‎docs/en/changelog.md

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## Changelog
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### v0.9.0 (05/01/2022)
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#### Highlights
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- Support arXiv 2021 manuscript 'ByteTrack: Multi-Object Tracking by Associating Every Detection Box' ([#385](https://github.com/open-mmlab/mmtracking/pull/385)), ([#383](https://github.com/open-mmlab/mmtracking/pull/383)), ([#372](https://github.com/open-mmlab/mmtracking/pull/372))
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- Support ICCV 2019 paper 'Video Instance Segmentation' ([#304](https://github.com/open-mmlab/mmtracking/pull/304)), ([#303](https://github.com/open-mmlab/mmtracking/pull/303)), ([#298](https://github.com/open-mmlab/mmtracking/pull/298)), ([#292](https://github.com/open-mmlab/mmtracking/pull/292))
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#### New Features
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- Support CrowdHuman dataset for MOT ([#366](https://github.com/open-mmlab/mmtracking/pull/366))
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- Support VOT2018 dataset for SOT ([#305](https://github.com/open-mmlab/mmtracking/pull/305))
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- Support YouTube-VIS dataset for VIS ([#290](https://github.com/open-mmlab/mmtracking/pull/290))
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#### Bug Fixes
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- Fix two significant bugs in SOT and provide new SOT pretrained models ([#349](https://github.com/open-mmlab/mmtracking/pull/349))
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#### Improvements
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- Refactor LaSOT, TrackingNet dataset and support GOT-10K datasets ([#296](https://github.com/open-mmlab/mmtracking/pull/296))
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- Support persisitent workers ([#348](https://github.com/open-mmlab/mmtracking/pull/348))
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### v0.8.0 (03/10/2021)
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#### New Features

‎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>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| 0.6.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| 0.7.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| master | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| 0.9.0 | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| 0.8.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| 0.7.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| 0.6.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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## Installation
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cd ..
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```
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Or directly run
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```shell
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pip install mmcv-full
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```
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4. Install MMDetection
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```shell

‎docs/zh_cn/install.md

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| MMTracking version | MMCV version | MMDetection version |
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|:-------------------:|:------------------------:|:-----------------------------:|
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| master | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| 0.6.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| 0.7.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| master | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| 0.9.0 | mmcv-full>=1.3.17, <1.5.0 | MMDetection>=2.19.1 |
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| 0.8.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| 0.7.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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| 0.6.0 | mmcv-full>=1.3.8, <1.4.0 | MMDetection>=2.14.0 |
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## 安装
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cd ..
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```
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或者，可以直接使用命令行安装：
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```shell
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pip install mmcv-full
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```
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4. 安装 MMDetection：
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```shell

‎mmtrack/version.py

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# Copyright (c) Open-MMLab. All rights reserved.
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__version__ = '0.8.0'
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__version__ = '0.9.0'
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def parse_version_info(version_str):

‎requirements/runtime.txt

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mmcls>=0.16.0
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motmetrics
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packaging
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pycocotools
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pycocotools<=2.0.2
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seaborn
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six
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terminaltables

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