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README.md
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[MediaPipe](http://g.co/mediapipe) 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. [MediaPipe](http://g.co/mediapipe) 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.
![Real-time Face Detection](mediapipe/docs/images/mobile/face_detection_android_gpu_small.gif) ![Real-time Face Detection](mediapipe/docs/images/realtime_face_detection.gif)
## Installation ## Installation
Follow these [instructions](mediapipe/docs/install.md). Follow these [instructions](mediapipe/docs/install.md).
@ -14,14 +14,14 @@ Follow these [instructions](mediapipe/docs/install.md).
See mobile and desktop [examples](mediapipe/docs/examples.md). See mobile and desktop [examples](mediapipe/docs/examples.md).
## Documentation ## Documentation
On [MediaPipe Read-the-Docs](https://mediapipe.readthedocs.io/). [MediaPipe Read-the-Docs](https://mediapipe.readthedocs.io/).
## Visualizing MediaPipe graphs ## Visualizing MediaPipe graphs
A web-based visualizer is hosted on [MediaPipe Visualizer](https://mediapipe-viz.appspot.com/). Please also see instructions [here](mediapipe/docs/visualizer.md). A web-based visualizer is hosted on [MediaPipe Visualizer](https://mediapipe-viz.appspot.com/). Please also see instructions [here](mediapipe/docs/visualizer.md).
## Publications ## Publications
* [MediaPipe: A Framework for Building Perception Pipelines](https://arxiv.org/) on [arXiv](https://arxiv.org/). * [MediaPipe: A Framework for Perceiving and Augmenting Reality](http://mixedreality.cs.cornell.edu/s/22_crv2_MediaPipe_CVPR_CV4ARVR_Workshop_2019_v2.pdf), extended abstract for [Third Workshop on Computer Vision for AR/VR](https://sites.google.com/corp/view/perception-cv4arvr/mediapipe).
* [MediaPipe: A Framework for Perceiving and Augmenting Reality](http://mixedreality.cs.cornell.edu/s/22_crv2_MediaPipe_CVPR_CV4ARVR_Workshop_2019_v2.pdf), extended abstract for [Third Workshop on Computer Vision for AR/VR](http://mixedreality.cs.cornell.edu/workshop/program). * Full-length draft: [MediaPipe: A Framework for Building Perception Pipelines](https://tiny.cc/mediapipe_paper)
## Contributing ## Contributing
We welcome contributions. Please follow these [guidelines](./CONTRIBUTING.md). We welcome contributions. Please follow these [guidelines](./CONTRIBUTING.md).

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mediapipe/docs/index.rst
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including, for instance, inference models and media processing functions. Sensory including, for instance, inference models and media processing functions. Sensory
data such as audio and video streams enter the graph, and perceived descriptions data such as audio and video streams enter the graph, and perceived descriptions
such as object-localization and face-landmark streams exit the graph. An example such as object-localization and face-landmark streams exit the graph. An example
graph that performs real-time face detection on mobile GPU is shown below. graph that performs real-time hair segmentation on mobile GPU is shown below.
.. image:: images/mobile/face_detection_android_gpu.png .. image:: images/mobile/hair_segmentation_android_gpu.png
:width: 400 :width: 400
:alt: Example MediaPipe graph :alt: Example MediaPipe graph