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PySOT

PySOT is a software system designed by SenseTime Video Intelligence Research team. It 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: SiamRPNDaSiamRPNSiamRPN++, and SiamMask.

Example SiamFC, SiamRPN and SiamMask outputs.

Introduction

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

Model Zoo and Baselines

We provide a large set of baseline results and trained models available for download in the PySOT Model Zoo.

Installation

Please find installation instructions for PyTorch and PySOT in INSTALL.md.

Quick Start: Using PySOT

After installation, please see GETTING_STARTED.md for brief tutorials covering inference and training with PySOT.

References

Contributors

License

PySOT is released under the Apache 2.0 license.

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