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---
emoji: "\U0001F440"
sdk: static
pinned: false
license: mit
title: Realtime YOLOv9 Object Detection WebGPU (Vue)
colorFrom: blue
colorTo: green
models:
- Xenova/yolos-tiny
- Xenova/gelan-c_all
short_description: Yet another Realtime YOLOv9 Object Detection WebGPU
---
<h1 align="center">Realtime YOLOv9 Object Detection WebGPU (Vue)</h1>
<p align="center">
[<a href="https://yolov9-od-realtime-webgpu-vue.netlify.app/">Try it</a>]
</p>
> Heavily inspired by [WebGPU Video Object Detection - a Hugging Face Space by Xenova](https://huggingface.co/spaces/Xenova/webgpu-video-object-detection)
# Realtime YOLOv9 Object Detection WebGPU
## Getting Started
Follow the steps below to set up and run the application.
### 1. Clone the Repository
Clone the examples repository from GitHub:
```sh
git clone https://github.com/proj-airi/webai-examples.git
```
### 2. Navigate to the Project Directory
Change your working directory to the `yolov9-od-realtime-webgpu` folder:
```sh
cd apps/yolov9-od-realtime-webgpu
```
### 3. Install Dependencies
Install the necessary dependencies using npm:
```sh
npm i
```
### 4. Run the Development Server
Start the development server:
```sh
npm run dev
```
The application should now be running locally. Open your browser and go to `http://localhost:5175` to see it in action.
## Acknowledgements
Great thanks to what Xenova have done.
> [Source code](https://github.com/huggingface/transformers.js-examples/tree/2720e7daedb9304756105d1c7eb30dd14830fd15/video-object-detection)
>
> [Reference code](https://github.com/huggingface/transformers.js/blob/a8413a99e1636c04c872f263017373ce045ec998/tests/pipelines/test_pipelines_object_detection.js#L9)
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