基于python与孪生网络实现单目标跟踪算法

:trophy:News: **We won the VOT-18 real-time challenge** :trophy:News: **We won the second place in the VOT-18 long-term challenge** # DaSiamRPN This repository includes PyTorch code for reproducing the results on VOT2018. [**Distractor-aware Siamese Networks for Visual Object Tracking**](https://arxiv.org/pdf/1808.06048.pdf) Zheng Zhu^\*, Qiang Wang^\*, Bo Li^\*, Wei Wu, Junjie Yan, and Weiming Hu *European Conference on Computer Vision (ECCV), 2018* ## Introduction **SiamRPN** formulates the task of visual tracking as a task of localization and identification simultaneously, initially described in an [CVPR2018 spotlight paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_High_Performance_Visual_CVPR_2018_paper.pdf). (Slides at [CVPR 2018 Spotlight](https://drive.google.com/open?id=1OGIOUqANvYfZjRoQfpiDqhPQtOvPCpdq)) **DaSiamRPN** improves the performances of SiamRPN by (1) introducing an effective sampling strategy to control the imbalanced sample distribution, (2) designing a novel distractor-aware module to perform incremental learning, (3) making a long-term tracking extension. [ECCV2018](https://arxiv.org/pdf/1808.06048.pdf). (Slides at [VOT-18 Real-time challenge winners talk](https://drive.google.com/open?id=1dsEI2uYHDfELK0CW2xgv7R4QdCs6lwfr)) <div align="center"> <img src="votresult.png" width="700px" /> </div> ## Prerequisites CPU: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz GPU: NVIDIA GTX1070 - python 3.6 - pytorch == 1.0.0 (This is my pytorch version, The original pytorch version is 0.3.1) - numpy - opencv ## Pretrained model for SiamRPN In our tracker, we use an AlexNet variant as our backbone, which is end-to-end trained for visual tracking. The pretrained model can be downloaded from google drive: [SiamRPNBIG.model](https://drive.google.com/file/d/1-vNVZxfbIplXHrqMHiJJYWXYWsOIvGsf/view?usp=sharing). Then, you should copy the pretrained model file `SiamRPNBIG.model` to the subfolder './code', so that the tracker can find and load the pretrained_model. :zap: 原文给出的三个模型均在Google Drive中，你也可以在百度网盘中下载 [[SiamRPN_Model](https://pan.baidu.com/s/1WY6_cdjR2_I_36LjfE7Rwg)] 提取码：me52 ## Detailed steps to install the prerequisites - install pytorch, numpy, opencv following the instructions in the `run_install.sh`. Please do **not** use conda to install. - you can alternatively modify `/PATH/TO/CODE/FOLDER/` in `tracker_SiamRPN.m` If the tracker is ready, you will see the tracking results. (EAO: 0.3827) ## Results All results can be downloaded from [Google Drive](https://drive.google.com/drive/folders/1HJOvl_irX3KFbtfj88_FVLtukMI1GTCR?usp=sharing). | | _{VOT2015</br>A / R / EAO} | _{VOT2016</br>A / R / EAO} | _{VOT2017 & VOT2018</br>A / R / EAO} | _{OTB2015</br>OP / DP} | _{UAV123</br>AUC / DP} | _{UAV20L</br>AUC / DP} | | :-: | :-: | :-: | :-: | :-: | :-: | :-: | | _{**SiamRPN** </br> CVPR2017} | <sub>0.58 / 1.13 / 0.349<sub> | <sub>0.56 / 0.26 / 0.344<sub> | <sub>0.49 / 0.46 / 0.244<sub> | <sub>81.9 / 85.0<sub> | <sub>0.527 / 0.748<sub> | <sub>0.454 / 0.617<sub> | | _{**DaSiamRPN** </br> ECCV2018} | <sub>**0.63** / **0.66** / **0.446**<sub> | <sub>**0.61** / **0.22** / **0.411**<sub> | <sub>0.56 / 0.34 / 0.326<sub> | <sub>**86.5** / **88.0**<sub> | <sub>**0.586** / **0.796**<sub> | <sub>**0.617** / **0.838**<sub> | | _{**DaSiamRPN** </br> VOT2018} | <sub>-<sub> | <sub>-<sub> | <sub>**0.59** / **0.28** / **0.383**<sub> | <sub>-<sub> | <sub>-<sub> | <sub>-<sub> | # Demo and Test on OTB2015 <div align="center"> <img src="code/data/bag.gif" width="400px" /> </div> - To reproduce the reuslts on paper, the pretrained model can be downloaded from [Google Drive](https://drive.google.com/open?id=1BtIkp5pB6aqePQGlMb2_Z7bfPy6XEj6H): `SiamRPNOTB.model`. <br /> :zap: :zap: This model is the **fastest** (~200fps) Siamese Tracker with AUC of 0.655 on OTB2015. :zap: :zap: - You must download OTB2015 dataset (download [script](code/data/get_otb_data.sh)) at first. A simple test example. ``` cd code python demo.py ``` If you want to test the performance on OTB2015, please using the follwing command. ``` cd code python test_otb.py python eval_otb.py OTB2015 "Siam*" 0 1 ``` # License Licensed under an MIT license. ## Citing DaSiamRPN If you find **DaSiamRPN** and **SiamRPN** useful in your research, please consider citing: ``` @inproceedings{Zhu_2018_ECCV, title={Distractor-aware Siamese Networks for Visual Object Tracking}, author={Zhu, Zheng and Wang, Qiang and Bo, Li and Wu, Wei and Yan, Junjie and Hu, Weiming}, booktitle={European Conference on Computer Vision}, year={2018} } @InProceedings{Li_2018_CVPR, title = {High Performance Visual Tracking With Siamese Region Proposal Network}, author = {Li, Bo and Yan, Junjie and Wu, Wei and Zhu, Zheng and Hu, Xiaolin}, booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2018} } ```