MediaPipe offers cross-platform, customizable ML solutions for live and streaming media.
|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|
|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|
|Face Detection||Face Mesh||Iris||Hands||Pose||Holistic|
|Hair Segmentation||Object Detection||Box Tracking||Instant Motion Tracking||Objectron||KNIFT|
|Instant Motion Tracking||✅|
See also MediaPipe Models and Model Cards for ML models released in MediaPipe.
To use MediaPipe in C++, Android and iOS, which allow further customization of the solutions as well as building your own, learn how to install MediaPipe and start building example applications in C++, Android and iOS.
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.
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