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Cross-platform ML solutions made simple

MediaPipe is the simplest way for researchers and developers to build world-class ML solutions and applications for mobile, desktop/cloud, web and IoT devices.

End-to-End acceleration: built-in fast ML inference and processing accelerated even on common hardware	Build one, deploy anywhere: Unified solution works across Android, iOS, desktop/cloud, web and IoT
Ready-to-use solutions: Cutting-edge ML solutions demonstrating full power of the framework	Free and open source: Framework and solutions both under Apache 2.0, fully extensible and customizable

ML solutions in MediaPipe

Face Detection	Face Mesh	Iris 🆕	Hands	Pose 🆕

Hair Segmentation	Object Detection	Box Tracking	Objectron	KNIFT

	Android	iOS	Desktop	Python	Web	Coral
Face Detection	✅	✅	✅		✅	✅
Face Mesh	✅	✅	✅
Iris 🆕	✅	✅	✅		✅
Hands	✅	✅	✅		✅
Pose 🆕	✅	✅	✅	✅	✅
Hair Segmentation	✅		✅		✅
Object Detection	✅	✅	✅			✅
Box Tracking	✅	✅	✅
Objectron	✅
KNIFT	✅
AutoFlip			✅
MediaSequence			✅
YouTube 8M			✅

MediaPipe on the Web

MediaPipe on the Web is an effort to run the same ML solutions built for mobile and desktop also in web browsers. The official API is under construction, but the core technology has been proven effective. Please see MediaPipe on the Web in Google Developers Blog for details.

You can use the following links to load a demo in the MediaPipe Visualizer, and over there click the "Runner" icon in the top bar like shown below. The demos use your webcam video as input, which is processed all locally in real-time and never leaves your device.

• MediaPipe Face Detection
• MediaPipe Iris
• MediaPipe Iris: Depth-from-Iris
• MediaPipe Hands
• MediaPipe Hands (palm/hand detection only)
• MediaPipe Pose
• MediaPipe Hair Segmentation

Getting started

Learn how to install MediaPipe and build example applications, and start exploring our ready-to-use solutions that you can further extend and customize.

The source code is hosted in the MediaPipe Github repository, and you can run code search using Google Open Source Code Search.

Publications

• BlazePose - On-device Real-time Body Pose Tracking in Google AI Blog
• MediaPipe Iris: Real-time Eye Tracking and Depth Estimation in Google AI Blog
• MediaPipe KNIFT: Template-based feature matching in Google Developers Blog
• Alfred Camera: Smart camera features using MediaPipe in Google Developers Blog
• Real-Time 3D Object Detection on Mobile Devices with MediaPipe in Google AI Blog
• AutoFlip: An Open Source Framework for Intelligent Video Reframing in Google AI Blog
• MediaPipe on the Web in Google Developers Blog
• Object Detection and Tracking using MediaPipe in Google Developers Blog
• On-Device, Real-Time Hand Tracking with MediaPipe in Google AI Blog
• MediaPipe: A Framework for Building Perception Pipelines

Videos

• YouTube Channel

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, 10 Oct 2019, San Jose, CA
• Google Industry Workshop at ICIP 2019, 24 Sept 2019, Taipei, Taiwan (presentation)
• Open sourced at CVPR 2019, 17~20 June, Long Beach, CA

Community

• Awesome MediaPipe - A curated list of awesome MediaPipe related frameworks, libraries and software
• Slack community for MediaPipe users
• Discuss - General community discussion around MediaPipe

Alpha disclaimer

MediaPipe is currently in alpha at v0.7. We may be still making breaking API changes and expect to get to stable APIs 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.