工具介绍
Track-Anything 是一款基于 Segment Anything、XMem 和 E2FGVI 的灵活、交互式视频对象跟踪和分割工具。
> **Note:** :fire: If you are interested in **human mesh generation from videos** (beyond video segmentation), please check out **[SAM-Body4D](https://github.com/gaomingqi/sam-body4d)**.
***Track-Anything*** is a flexible and interactive tool for video object tracking and segmentation. It is developed upon [Segment Anything](https://github.com/facebookresearch/segment-anything), can specify anything to track and segment via user clicks only. During tracking, users can flexibly change the objects they wanna track or correct the region of interest if there are any ambiguities. These characteristics enable ***Track-Anything*** to be suitable for:
- Video object tracking and segmentation with shot changes.
- Visualized development and data annotation for video object tracking and segmentation.
- Object-centric downstream video tasks, such as video inpainting and editing.
## :rocket: Updates
- 2023/05/02: We uploaded tutorials in steps :world_map:. Check [HERE](./doc/tutorials.md) for more details.
- 2023/04/29: We improved inpainting by decoupling GPU memory usage and video length. Now Track-Anything can inpaint videos with any length! :smiley_cat: Check [HERE](https://github.com/gaomingqi/Track-Anything/issues/4#issuecomment-1528198165) for our GPU memory requirements.
- 2023/04/25: We are delighted to introduce [Caption-Anything](https://github.com/ttengwang/Caption-Anything) :writing_hand:, an inventive project from our lab that combines the capabilities of Segment Anything, Visual Captioning, and ChatGPT.
- 2023/04/20: We deployed [DEMO](https://huggingface.co/spaces/VIPLab/Track-Anything?duplicate=true) on Hugging Face :hugs:!
- 2023/04/14: We made Track-Anything public!
## :world_map: Video Tutorials ([Track-Anything Tutorials in Steps](./doc/tutorials.md))
https://user-images.githubusercontent.com/30309970/234902447-a4c59718-fcfe-443a-bd18-2f3f775cfc13.mp4
---
### :joystick: Example - Multiple Object Tracking and Segmentation (with [XMem](https://github.com/hkchengrex/XMem))
https://user-images.githubusercontent.com/39208339/233035206-0a151004-6461-4deb-b782-d1dbfe691493.mp4
---
### :joystick: Example - Video Object Tracking and Segmentation with Shot Changes (with [XMem](https://github.com/hkchengrex/XMem))
https://user-images.githubusercontent.com/30309970/232848349-f5e29e71-2ea4-4529-ac9a-94b9ca1e7055.mp4
---
### :joystick: Example - Video Inpainting (with [E2FGVI](https://github.com/MCG-NKU/E2FGVI))
https://user-images.githubusercontent.com/28050374/232959816-07f2826f-d267-4dda-8ae5-a5132173b8f4.mp4
## :computer: Get Started
#### Linux & Windows
```shell
# Clone the repository:
git clone https://github.com/gaomingqi/Track-Anything.git
cd Track-Anything
# Install dependencies:
pip install -r requirements.txt
# Run the Track-Anything gradio demo.
python app.py --device cuda:0
# python app.py --device cuda:0 --sam_model_type vit_b # for lower memory usage
```
## :book: Citation
If you find this work useful for your research or applications, please cite using this BibTeX:
```bibtex
@misc{yang2023track,
title={Track Anything: Segment Anything Meets Videos},
author={Jinyu Yang and Mingqi Gao and Zhe Li and Shang Gao and Fangjing Wang and Feng Zheng},
year={2023},
eprint={2304.11968},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```
## :clap: Acknowledgements
The project is based on [Segment Anything](https://github.com/facebookresearch/segment-anything), [XMem](https://github.com/hkchengrex/XMem), and [E2FGVI](https://github.com/MCG-NKU/E2FGVI). Thanks for the authors for their efforts.