berkus / mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

Home Page:https://mediapipe.dev

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MediaPipe


Live ML anywhere

MediaPipe offers cross-platform, customizable ML solutions for live and streaming media.

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End-to-End acceleration: Built-in fast ML inference and processing accelerated even on common hardware Build once, deploy anywhere: Unified solution works across Android, iOS, desktop/cloud, web and IoT
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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 Holistic
face_detection face_mesh iris hand pose hair_segmentation
Hair Segmentation Object Detection Box Tracking Instant Motion Tracking Objectron KNIFT
hair_segmentation object_detection box_tracking instant_motion_tracking objectron knift
Android iOS C++ Python JS Coral
Face Detection
Face Mesh
Iris
Hands
Pose
Holistic
Hair Segmentation
Object Detection
Box Tracking
Instant Motion Tracking
Objectron
KNIFT
AutoFlip
MediaSequence
YouTube 8M

See also MediaPipe Models and Model Cards for ML models released in MediaPipe.

MediaPipe in Python

MediaPipe offers customizable Python solutions as a prebuilt Python package on PyPI, which can be installed simply with pip install mediapipe. It also provides tools for users to build their own solutions. Please see MediaPipe in Python for more info.

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.

visualizer_runner

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

Videos

Events

Community

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.

About

Cross-platform, customizable ML solutions for live and streaming media.

https://mediapipe.dev

License:Apache License 2.0


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