Awesome
<div align="center"> <img align="left" width="100" height="100" src="https://github.com/user-attachments/assets/1834fc25-42ef-4237-9feb-53a01c137e83" alt="">SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory
Cheng-Yen Yang, Hsiang-Wei Huang, Wenhao Chai, Zhongyu Jiang, Jenq-Neng Hwang
Information Processing Lab, University of Washington
</div>[Arxiv] [Project Page] [Raw Results]
This repository is the official implementation of SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory
https://github.com/user-attachments/assets/9d368ca7-2e9b-4fed-9da0-d2efbf620d88
Getting Started
SAMURAI Installation
SAM 2 needs to be installed first before use. The code requires python>=3.10
, as well as torch>=2.3.1
and torchvision>=0.18.1
. Please follow the instructions here to install both PyTorch and TorchVision dependencies. You can install the SAMURAI version of SAM 2 on a GPU machine using:
cd sam2
pip install -e .
pip install -e ".[notebooks]"
Please see INSTALL.md from the original SAM 2 repository for FAQs on potential issues and solutions.
pip install matplotlib==3.7 tikzplotlib jpeg4py opencv-python lmdb pandas scipy
SAM 2.1 Checkpoint Download
cd checkpoints && \
./download_ckpts.sh && \
cd ..
Data Preparation
Please prepare the data in the following format:
data/LaSOT
├── airplane/
│ ├── airplane-1/
│ │ ├── full_occlusion.txt
│ │ ├── groundtruth.txt
│ │ ├── img
│ │ ├── nlp.txt
│ │ └── out_of_view.txt
│ ├── airplane-2/
│ ├── airplane-3/
│ ├── ...
├── basketball
├── bear
├── bicycle
...
├── training_set.txt
└── testing_set.txt
Main Inference
python scripts/main_inference.py
Acknowledgment
SAMURAI is built on top of SAM 2 by Meta FAIR.
The VOT evaluation code is modifed from VOT Toolkit by Luka Čehovin Zajc.
Citation
Please consider citing our paper and the wonderful SAM 2
if you found our work interesting and useful.
@article{ravi2024sam2,
title={SAM 2: Segment Anything in Images and Videos},
author={Ravi, Nikhila and Gabeur, Valentin and Hu, Yuan-Ting and Hu, Ronghang and Ryali, Chaitanya and Ma, Tengyu and Khedr, Haitham and R{\"a}dle, Roman and Rolland, Chloe and Gustafson, Laura and Mintun, Eric and Pan, Junting and Alwala, Kalyan Vasudev and Carion, Nicolas and Wu, Chao-Yuan and Girshick, Ross and Doll{\'a}r, Piotr and Feichtenhofer, Christoph},
journal={arXiv preprint arXiv:2408.00714},
url={https://arxiv.org/abs/2408.00714},
year={2024}
}
@misc{yang2024samurai,
title={SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory},
author={Cheng-Yen Yang and Hsiang-Wei Huang and Wenhao Chai and Zhongyu Jiang and Jenq-Neng Hwang},
year={2024},
eprint={2411.11922},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2411.11922},
}