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Easy & Modular Computer Vision Detectors, Trackers & SAM - Run YOLOv9,v8,v7,v6,v5,R,X in under 10 lines of code.
| Date | Stars |
|---|---|
| 2026-07-24 | 612 |
| 2026-07-25 | 612 |
| 2026-07-28 | 611 |
| 2026-07-30 | 611 |
| 2026-07-31 | 611 |
| 2026-08-06 | 611 |
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# AS-One v2 : A Modular Library for YOLO Object Detection, Segmentation, Tracking & Pose
<div align="center">
<p>
<a align="center" href="" target="https://badge.fury.io/py/asone">
<img
width="100%"
src="https://kajabi-storefronts-production.kajabi-cdn.com/kajabi-storefronts-production/file-uploads/themes/2151400015/settings_images/747367e-1d78-eead-2a2-7e5b336a775_Screenshot_2024-05-08_at_13.48.08.jpg" width="100%">
<a href="https://www.youtube.com/watch?v=K-VcpPwcM8k" style="display:inline-block;padding:10px 20px;background-color:red;color:white;text-decoration:none;font-size:16px;font-weight:bold;border-radius:5px;transition:background-color 0.3s;" target="_blank">Watch Video</a>
</p>
<br>
<br>
[](https://badge.fury.io/py/asone)
[](https://badge.fury.io/py/asone)
[](https://drive.google.com/file/d/1xy5P9WGI19-PzRH3ceOmoCgp63K6J_Ls/view?usp=sharing)
[](https://github.com/augmentedstartups/AS-One)
[](https://opensource.org/licenses/)
</div>
## 👋 Hello
==UPDATE: ASOne v2 is now out! We've updated with YOLOV9 and SAM==
AS-One is a python wrapper for multiple detection and tracking algorithms all at one place. Different trackers such as `ByteTrack`, `DeepSORT` or `NorFair` can be integrated with different versions of `YOLO` with minimum lines of code.
This python wrapper provides YOLO models in `ONNX`, `PyTorch` & `CoreML` flavors. We plan to offer support for future versions of YOLO when they get released.
This is One Library for most of your computer vision needs.
If you would like to dive deeper into YOLO Object Detection and Tracking, then check out our [courses](https://www.augmentedstartups.com/store) and [projects](https://store.augmentedstartups.com)
[<img src="https://s3.amazonaws.com/kajabi-storefronts-production/blogs/22606/images/0FDx83VXSYOY0NAO2kMc_ASOne_Windows_Play.jpg" width="50%">](https://www.youtube.com/watch?v=K-VcpPwcM8k)
Watch the step-by-step tutorial 🤝
## 💻 Install
<details><summary> 🔥 Prerequisites</summary>
- Make sure to install `GPU` drivers in your system if you want to use `GPU` . Follow [driver installation](asone/linux/Instructions/Driver-Installations.md) for further instructions.
- Make sure you have [MS Build tools](https://aka.ms/vs/17/release/vs_BuildTools.exe) installed in system if using windows.
- [Download git for windows](https://git-scm.com/download/win) if not installed.
</details>
```bash
pip install asone
```
For windows machine, you will need to install from source to run `asone` library. Check out instructions in `👉 Install from Source` section below to install on windows.
<details>
<summary> 👉 Install from Source</summary>
### 💾 Clone the Repository
Navigate to an empty folder of your choice.
`git clone https://github.com/augmentedstartups/AS-One.git`
Change Directory to AS-One
`cd AS-One`
<details open>
<summary> 👉 For Linux</summary>
```shell
python3 -m venv .env
source .env/bin/activate
pip install -r requirements.txt
# for CPU
pip install torch torchvision
# for GPU
pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/cu113
```
</details>
<details>
<summary> 👉 For Windows 10/11</summary>
```shell
python -m venv .env
.env\Scripts\activate
pip install numpy Cython
pip install lap
pip install -e git+https://github.com/samson-wang/cython_bbox.git#egg=cython-bbox
pip install asone onnxruntime-gpu==1.12.1
pip install typing_extensions==4.7.1
pip install super-gradients==3.1.3
# for CPU
pip install torch torchvision
# for GPU
pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/cu113
or
pip install torch==1.10.1+cu113 torchvisExcerpt of 12,399 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:52bc5de82451109f, topic:computer-vision, topic:object-detection, topic:opencv
matched fp:52bc5de82451109f, topic:deep-learning, topic:pytorch