Fast Online Object Tracking and Segmentation: A Unifying Approach
论文地址:
https://arxiv.org/abs/1812.05050
Github项目地址:
https://github.com/foolwood/SiamMask#environment-setup
这是SiamMask(CVPR2019)的官方参考代码。 有关技术细节,请参阅:
Fast Online Object Tracking and Segmentation: A Unifying Approach
作者:Qiang Wang*, Li Zhang*, Luca Bertinetto*, Weiming Hu, Philip H.S. Torr ( * 表示付出同等贡献)
CVPR2019
[ Paper - 论文 ] [ Video - 视频(油管)] [ Project Page - 项目页面 ]
所有代码都已经在Ubuntu 16.04,Python 3.6,Pytorch 0.4.1,CUDA 9.2,GTX 2080 GPU的环境上进行了测试
git clone https://github.com/foolwood/SiamMask.git && cd SiamMask
export SiamMask=$PWD
conda create -n siammask python=3.6
source activate siammask
pip install -r requirements.txt
bash make.sh
export PYTHONPATH=$PWD:$PYTHONPATH
cd $SiamMask/experiments/siammask
wget -q http://www.robots.ox.ac.uk/~qwang/SiamMask_VOT.pth
wget -q http://www.robots.ox.ac.uk/~qwang/SiamMask_DAVIS.pth
cd $SiamMask/experiments/siammask
export PYTHONPATH=$PWD:$PYTHONPATH
python ../../tools/demo.py --resume SiamMask_DAVIS.pth --config config_davis.json
cd $SiamMask/data
bash get_test_data.sh
cd $SiamMask/experiments/siammask
wget -q http://www.robots.ox.ac.uk/~qwang/SiamMask_VOT.pth
wget -q http://www.robots.ox.ac.uk/~qwang/SiamMask_DAVIS.pth
bash test_mask_refine.sh config_vot.json SiamMask_VOT.pth VOT2016 0
bash test_mask_refine.sh config_vot.json SiamMask_VOT.pth VOT2018 0
python ../../tools/eval.py --dataset VOT2016 --tracker_prefix Cus --result_dir ./test/VOT2016
python ../../tools/eval.py --dataset VOT2018 --tracker_prefix Cus --result_dir ./test/VOT2018
bash test_mask_refine.sh config_davis.json SiamMask_DAVIS.pth DAVIS2016 0
bash test_mask_refine.sh config_davis.json SiamMask_DAVIS.pth DAVIS2017 0
bash test_mask_refine.sh config_davis.json SiamMask_DAVIS.pth ytb_vos 0
以下是在本项目仓库复制的结果。 所有结果都可以从我们的 项目页面 下载。
跟 踪 器 | VOT2016EAO / A / R | VOT2018EAO / A / R | DAVIS2016J / F | DAVIS2017J / F | Youtube-VOSJ_s / J_u / F_s / F_u | 速度 |
---|---|---|---|---|---|---|
SiamMask w/o Mask | 0.412 / 0.623 / 0.233 | 0.363 / 0.584 / 0.300 | - / - | - / - | - / - / - / - | 76.95 FPS |
SiamMask | 0.433 / 0.639 / 0.214 | 0.380 / 0.609 / 0.276 | 0.713 / 0.674 | 0.543 / 0.585 | 0.602 / 0.451 / 0.582 / 0.477 | 56.23 FPS |
注意:速度是在 GTX 2080 上测试的
本项目遵循MIT Licence
如果你需要使用代码,请引用下方的声明代码块:
@article{Wang2019SiamMask,
title={Fast Online Object Tracking and Segmentation: A Unifying Approach},
author={Wang, Qiang and Zhang, Li and Bertinetto, Luca and Hu, Weiming and Torr, Philip HS},
journal={The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2019}
}