[MediaPipe](http://mediapipe.dev) is a framework for building multimodal (eg. video, audio, any time series data) applied ML pipelines. With MediaPipe, a perception pipeline can be built as a graph of modular components, including, for instance, inference models (e.g., TensorFlow, TFLite) and media processing functions.
> "<em>MediaPipe has made it extremely easy to build our 3D person pose reconstruction demo app, facilitating accelerated neural network inference on device and synchronization of our result visualization with the video capture stream. Highly recommended!</em>" - George Papandreou, CTO, [Ariel AI](https://arielai.com)
Check out the [Examples page](https://mediapipe.readthedocs.io/en/latest/examples.html) for tutorials on how to use MediaPipe. [Concepts page](https://mediapipe.readthedocs.io/en/latest/concepts.html) for basic definitions
A web-based visualizer is hosted on [viz.mediapipe.dev](https://viz.mediapipe.dev/). Please also see instructions [here](mediapipe/docs/visualizer.md).