mediapipe README

The project's README from github.com/google-ai-edge/mediapipe. As one markdown file: README.md.


layout: forward target: https://developers.google.com/mediapipe title: Home nav_order: 1


Attention: We have moved to https://developers.google.com/mediapipe as the primary developer documentation site for MediaPipe as of April 3, 2023.

MediaPipe

Attention: MediaPipe Solutions Preview is an early release. Learn more.

On-device machine learning for everyone

Delight your customers with innovative machine learning features. MediaPipe contains everything that you need to customize and deploy to mobile (Android, iOS), web, desktop, edge devices, and IoT, effortlessly.

Get started

You can get started with MediaPipe Solutions by by checking out any of the developer guides for vision, text, and audio tasks. If you need help setting up a development environment for use with MediaPipe Tasks, check out the setup guides for Android, web apps, and Python.

Solutions

MediaPipe Solutions provides a suite of libraries and tools for you to quickly apply artificial intelligence (AI) and machine learning (ML) techniques in your applications. You can plug these solutions into your applications immediately, customize them to your needs, and use them across multiple development platforms. MediaPipe Solutions is part of the MediaPipe open source project, so you can further customize the solutions code to meet your application needs.

These libraries and resources provide the core functionality for each MediaPipe Solution:

These tools let you customize and evaluate solutions:

Legacy solutions

We have ended support for these MediaPipe Legacy Solutions as of March 1, 2023. All other MediaPipe Legacy Solutions will be upgraded to a new MediaPipe Solution. See the Solutions guide for details. The code repository and prebuilt binaries for all MediaPipe Legacy Solutions will continue to be provided on an as-is basis.

For more on the legacy solutions, see the documentation.

Framework

To start using MediaPipe Framework, install MediaPipe Framework and start building example applications in C++, Android, and iOS.

MediaPipe Framework is the low-level component used to build efficient on-device machine learning pipelines, similar to the premade MediaPipe Solutions.

Before using MediaPipe Framework, familiarize yourself with the following key Framework concepts:

Community

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.

Privacy Notice

Last modified: June 5, 2026

When you use MediaPipe Tasks, processing of the input data (e.g. images, video, text) takes place on device, and MediaPipe does not send that input data to Google servers. As a result, you can use our MediaPipe Tasks APIs for processing data that should not leave the device.

MediaPipe Tasks APIs send metrics about the performance and utilization of the APIs in your app to Google. Google uses this metrics data to measure performance, usage, debug, maintain and improve the MediaPipe Tasks, as further described in our Privacy Policy.

You are responsible for obtaining informed consent from your app users about Google's processing of MediaPipe metrics data as required by applicable law.

Resources

Publications

Videos

mediapipe (google-ai-edge/mediapipe)

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What is this?Google's open-source, cross-platform toolkit for on-device machine learning in live and streaming media: ready-made libraries and pre-trained models you plug straight into your own app.
Is it one library or a whole toolbox?A toolbox. MediaPipe Solutions bundles cross-platform Task APIs and libraries with pre-trained, ready-to-run models, while the low-level MediaPipe Framework lets you build your own efficient on-device ML pipelines.
How do I get started with it?Pick a developer guide for the vision, text or audio task you want, then follow the setup guide for your platform: Android, web apps or Python. For the low-level Framework, you install it and start building the example apps in C++, Android and iOS.
Do I need to write C++ to use it?Not for the premade Solutions — you use them through the cross-platform MediaPipe Tasks APIs, with guides for Android, web and Python. C++ matters only if you build custom pipelines on the low-level Framework.
Is everything in the repo still actively supported?No. Support for the old MediaPipe Legacy Solutions ended on March 1, 2023 — their code and prebuilt binaries remain available as-is while they get replaced by the new MediaPipe Solutions.
Where can apps built with it run?Mobile (Android and iOS), web, desktop, edge devices and IoT — the same solutions plug into apps across all of these development platforms.
Does my users' data leave the device?No — input data like images, video and text is processed on device and never sent to Google servers. One caveat: the Tasks APIs do send performance and usage metrics to Google, so you may need user consent for that.
What can I actually build with it?The project's publication list points at real-time hand tracking, full-body pose tracking with BlazePose, face and eye tracking with depth estimation, 3D object detection, instant motion tracking, and intelligent video reframing with AutoFlip — the same family of tech behind background features in Google Meet.
Can I adapt the models to my own data?Yes. MediaPipe Model Maker customizes solution models with your data, MediaPipe Studio lets you visualize, evaluate and benchmark them in the browser, and since the solutions are part of the open-source project you can also modify the solution code itself.
Is it free to use in my own product?Yes — it is open source under the Apache-2.0 license, and it is designed exactly for plugging these solutions into your applications across mobile, web and desktop.
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