Skip to main content

MediaPipe is the simplest way for researchers and developers to build world-class ML solutions and applications for mobile, edge, cloud and the web. See the privacy notice at https://goo.gle/mediapipe-privacy.

Project description


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:

  • MediaPipe Tasks: Cross-platform APIs and libraries for deploying solutions. Learn more.
  • MediaPipe models: Pre-trained, ready-to-run models for use with each solution.

These tools let you customize and evaluate solutions:

  • MediaPipe Model Maker: Customize models for solutions with your data. Learn more.
  • MediaPipe Studio: Visualize, evaluate, and benchmark solutions in your browser. Learn more.

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

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

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

Release history Release notifications | RSS feed

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

mediapipe_nightly-0.10.36rc20260618-py3-none-win_arm64.whl (30.1 MB view details)

Uploaded Python 3Windows ARM64

mediapipe_nightly-0.10.36rc20260618-py3-none-win_amd64.whl (30.9 MB view details)

Uploaded Python 3Windows x86-64

mediapipe_nightly-0.10.36rc20260618-py3-none-manylinux_2_28_x86_64.whl (22.5 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ x86-64

mediapipe_nightly-0.10.36rc20260618-py3-none-manylinux_2_28_aarch64.whl (21.0 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ ARM64

mediapipe_nightly-0.10.36rc20260618-py3-none-macosx_11_0_arm64.whl (36.8 MB view details)

Uploaded Python 3macOS 11.0+ ARM64

File details

Details for the file mediapipe_nightly-0.10.36rc20260618-py3-none-win_arm64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260618-py3-none-win_arm64.whl
Algorithm Hash digest
SHA256 f0a8b9091c710356d8da655e43cc61c9e642a1db1b002e49779efbbd32bbd4b0
MD5 536cd1fe9d0cef78beeceed4343edb25
BLAKE2b-256 793e389dd5dd711f5a469c04dc87d7b1533190a15f5b0f9e1570af55df99316d

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.36rc20260618-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260618-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 8685b331872ab7709bb7591b0691d8724edb7f98c1278776db15d0253a1af116
MD5 12bcdc16300326dc45a6e28d1d17494e
BLAKE2b-256 86959d343b3712d3e0a4f7d55fb3c8d4ca16a165e15f38b3e06b8ee2a9502641

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.36rc20260618-py3-none-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260618-py3-none-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 df1729d1bc60a48efb529ee1d02a7f191bce8c5f5b2f891386fb19214233fd1b
MD5 411d835ab2263bd5d1c3f589064b085a
BLAKE2b-256 3f41b6515ee4c6ecf23b8af4818b4a9c8899fec9e34bdf61a8d60fdf3114f8e8

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.36rc20260618-py3-none-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260618-py3-none-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 3afcf2fce2e9e12d0e445eca716f348597aea4724537de5b72f36388680bd532
MD5 263d620853c0a18ebee22727006e17cf
BLAKE2b-256 d2243275fb9698d9cc44fa611f1bd398a9f8686b7ba91484bfcc2cdbdc750969

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.36rc20260618-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260618-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f16b2f1ad4034d52046cf7d0714f5d40245dea4eacc3833562d54747e9707c58
MD5 648379d2486d8c28c5f9f81137e197b0
BLAKE2b-256 207c48cd35a8c170ba4cce08361053ff1f0b09587dc39e5142f760b77ee634fa

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page