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

Project description


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MediaPipe


Live ML anywhere

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

accelerated.png cross_platform.png
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
Selfie Segmentation
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.

Getting started

To start using MediaPipe solutions with only a few lines code, see example code and demos in MediaPipe in Python and MediaPipe in JavaScript.

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.

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.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for mediapipe, version 0.8.8.1
Filename, size File type Python version Upload date Hashes
Filename, size mediapipe-0.8.8.1-cp37-cp37m-macosx_10_15_x86_64.whl (34.6 MB) File type Wheel Python version cp37 Upload date Hashes View
Filename, size mediapipe-0.8.8.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (34.0 MB) File type Wheel Python version cp37 Upload date Hashes View
Filename, size mediapipe-0.8.8.1-cp37-cp37m-win_amd64.whl (49.7 MB) File type Wheel Python version cp37 Upload date Hashes View
Filename, size mediapipe-0.8.8.1-cp38-cp38-macosx_10_15_x86_64.whl (34.6 MB) File type Wheel Python version cp38 Upload date Hashes View
Filename, size mediapipe-0.8.8.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (34.0 MB) File type Wheel Python version cp38 Upload date Hashes View
Filename, size mediapipe-0.8.8.1-cp38-cp38-win_amd64.whl (49.7 MB) File type Wheel Python version cp38 Upload date Hashes View
Filename, size mediapipe-0.8.8.1-cp39-cp39-macosx_10_15_x86_64.whl (34.6 MB) File type Wheel Python version cp39 Upload date Hashes View
Filename, size mediapipe-0.8.8.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (34.0 MB) File type Wheel Python version cp39 Upload date Hashes View
Filename, size mediapipe-0.8.8.1-cp39-cp39-win_amd64.whl (49.7 MB) File type Wheel Python version cp39 Upload date Hashes View

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