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https://github.com/sat-mtl/livepose

Pose, blob and object detection software
https://github.com/sat-mtl/livepose

blob-detection pose-detection yolo

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Pose, blob and object detection software

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SAT


LivePose offers a simple way to run computer vision models on live video and send the results to any [OSC](https://en.wikipedia.org/wiki/Open_Sound_Control)-compatible application. With no programming required, load a model, select your camera, and start streaming data. This release uses [ONNX](https://github.com/onnx/onnx), an open standard for machine learning models, providing a lightweight, cross-platform GUI application.

## Features

- 🧠 Load `.onnx` models (BlazePose, YOLOv8 Pose, ResNet)
- 📷 Automatic camera detection (plug and play)
- 🎬 Live video preview
- 📡 Configurable OSC output

## Use Cases

Connect your output data to **[Pure Data](https://puredata.info/)**, **[Max/MSP](https://cycling74.com/downloads)**, **[Processing](https://processing.org/)**, **[p5.js](https://p5js.org/)**, **[TouchDesigner](https://derivative.ca/UserGuide/TouchDesigner)**, **[SuperCollider](https://supercollider.github.io/)**, **[openFrameworks](https://openframeworks.cc/)**, or any software that receives [OSC](https://en.wikipedia.org/wiki/Open_Sound_Control). Useful for interactive installations, live performance, prototyping, and experimentation. Check [awesome-creative-coding](https://github.com/terkelg/awesome-creative-coding) for more tools and resources.

## Credits

Developed by the [Société des Arts Technologiques](https://sat.qc.ca), built on [ossia score](https://ossia.io).