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