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| third_party | ||
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| .gitignore | ||
| BUILD | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| LICENSE | ||
| README.md | ||
| setup_android_sdk_and_ndk.sh | ||
| setup_opencv.sh | ||
| WORKSPACE | ||
MediaPipe is a framework for building multimodal (eg. video, audio, any time series data), cross platform (i.e Android, iOS, web, edge devices) 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 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!" - George Papandreou, CTO, Ariel AI
ML Solutions in MediaPipe
- Face Detection (web demo)
- Face Mesh
- Hand Detection
- Hand Tracking (web demo)
- Multi-hand Tracking
- Hair Segmentation (web demo)
- Object Detection
- Object Detection and Tracking
- Objectron: 3D Object Detection and Tracking
- AutoFlip: Intelligent Video Reframing
- KNIFT: Template Matching with Neural Image Features
Installation
Follow these instructions.
Getting started
See mobile, desktop, web and Google Coral examples.
Check out some web demos [Edge detection] [Face detection] [Hand Tracking]
Documentation
MediaPipe Read-the-Docs or docs.mediapipe.dev
Check out the Examples page for tutorials on how to use MediaPipe. Concepts page for basic definitions
Visualizing MediaPipe graphs
A web-based visualizer is hosted on viz.mediapipe.dev. Please also see instructions here.
Google Open Source Code search
Search MediaPipe Github repository using Google Open Source code search
Videos
Publications
- MediaPipe KNIFT: Template-based Feature Matching
- Alfred Camera: Smart camera features using MediaPipe
- MediaPipe Objectron: Real-time 3D Object Detection on Mobile Devices
- AutoFlip: An Open Source Framework for Intelligent Video Reframing
- Google Developer Blog: MediaPipe on the Web
- Google Developer Blog: Object Detection and Tracking using MediaPipe
- On-Device, Real-Time Hand Tracking with MediaPipe
- MediaPipe: A Framework for Building Perception Pipelines
Events
- MediaPipe Seattle Meetup, Google Building Waterside, 13 Feb 2020
- AI Nextcon 2020, 12-16 Feb 2020, Seattle
- MediaPipe Madrid Meetup, 16 Dec 2019
- MediaPipe London Meetup, Google 123 Building, 12 Dec 2019
- ML Conference, Berlin, 11 Dec 2019
- MediaPipe Berlin Meetup, Google Berlin, 11 Dec 2019
- The 3rd Workshop on YouTube-8M Large Scale Video Understanding Workshop Seoul, Korea ICCV 2019
- AI DevWorld 2019 on Oct 10 in San Jose, California
- Google Industry Workshop at ICIP 2019 Presentation on Sept 24 in Taipei, Taiwan
- Open sourced at CVPR 2019 on June 17~20 in Long Beach, CA
Community forum
- Discuss - General community discussion around MediaPipe
Alpha Disclaimer
MediaPipe is currently in alpha for v0.7. We are still making breaking API changes and expect to get to stable API by v1.0.
Contributing
We welcome contributions. Please follow these guidelines.
We use GitHub issues for tracking requests and bugs. Please post questions to the MediaPipe Stack Overflow with a 'mediapipe' tag.