PySOT is SenseTime Research's software system that implements state-of-the-art single object tracking algorithms, including SiamRPN and SiamMask. It is written in Python and powered by the PyTorch deep learning framework. This project also contains a Python port of toolkit for evaluating trackers.
PySOT has enabled research projects, including: SiamRPN, DaSiamRPN, SiamRPN++, and SiamMask.
Example SiamFC, SiamRPN and SiamMask outputs.
The goal of PySOT is to provide a high-quality, high-performance codebase for visaul tracking research. It is designed to be flexible in order to support rapid implementation and evaluation of novel research. PySOT includes implementations of the following visaul tracking algorithms:
using the following backbone network architectures:
Additional backbone architectures may be easily implemented. For more details about these models, please see References below.
Evaluation toolkit can support the following datasets:
📎 OTB2015 📎 VOT16/18/19 📎 VOT18-LT 📎 LaSOT 📎 UAV123
We provide a large set of baseline results and trained models available for download in the PySOT Model Zoo.
Please find installation instructions for PyTorch and PySOT in INSTALL.md.
After installation, please see GETTING_STARTED.md for brief tutorials covering inference and training with PySOT.
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Fast Online Object Tracking and Segmentation: A Unifying Approach. Qiang Wang, Li Zhang, Luca Bertinetto, Weiming Hu, Philip H.S. Torr. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
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SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks. Bo Li, Wei Wu, Qiang Wang, Fangyi Zhang, Junliang Xing, Junjie Yan. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
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Distractor-aware Siamese Networks for Visual Object Tracking. Zheng Zhu, Qiang Wang, Bo Li, Wu Wei, Junjie Yan, Weiming Hu. The European Conference on Computer Vision (ECCV), 2018.
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High Performance Visual Tracking with Siamese Region Proposal Network. Bo Li, Wei Wu, Zheng Zhu, Junjie Yan, Xiaolin Hu. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
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Fully-Convolutional Siamese Networks for Object Tracking. Luca Bertinetto, Jack Valmadre, João F. Henriques, Andrea Vedaldi, Philip H. S. Torr. The European Conference on Computer Vision (ECCV) Workshops, 2016.
PySOT is released under the Apache 2.0 license.