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://developers.google.com/edge/mediapipe/solutions/tasks#mediapipe_tasks_privacy_notice.

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-0.10.36rc20260609-py3-none-win_arm64.whl (30.1 MB view details)

Uploaded Python 3Windows ARM64

mediapipe_nightly-0.10.36rc20260609-py3-none-win_amd64.whl (30.9 MB view details)

Uploaded Python 3Windows x86-64

mediapipe_nightly-0.10.36rc20260609-py3-none-manylinux_2_28_x86_64.whl (22.5 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ x86-64

mediapipe_nightly-0.10.36rc20260609-py3-none-manylinux_2_28_aarch64.whl (21.0 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ ARM64

mediapipe_nightly-0.10.36rc20260609-py3-none-macosx_11_0_arm64.whl (36.7 MB view details)

Uploaded Python 3macOS 11.0+ ARM64

File details

Details for the file mediapipe_nightly-0.10.36rc20260609-py3-none-win_arm64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260609-py3-none-win_arm64.whl
Algorithm Hash digest
SHA256 ba26cb588d7f5da14d6036fd7269036715325e52bec82ea0e88e992c5e5c8ad7
MD5 829608caf08eb97698f717ff4ba4fe58
BLAKE2b-256 9b977547f80bfe4b4d5b7526b2dd016a55d6d09bb7c2015c154fb6573c9ecdcf

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.36rc20260609-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260609-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 fa23b9c5c27cfcc66995b7c19f6b822fc2878b76ff5e21180c97bfb36f58ce0f
MD5 0597df77ca02ec30d3f730f5b91f5d3c
BLAKE2b-256 b9cc1dd1b6561c4643469a49484546fbc6adf6bb549de222ad27254fe1cb3f3d

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.36rc20260609-py3-none-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260609-py3-none-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 370382004cf8bb80d351696175648cf71dea58d5680240e6560298dd094124b3
MD5 286c22b076f3b67c40590f5208154dad
BLAKE2b-256 54a63e77939f243689b1bf34808a8a9afc0030f1e628d793320ebbaf242209f0

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.36rc20260609-py3-none-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260609-py3-none-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 656688889863626630169d8a6d48807bfbccdb25a3ddec2c3c37579e088f6184
MD5 ff81d01354e8dd57c40996d328752756
BLAKE2b-256 f5a012920ad9f1aae27d552f51028144eef1ac985496e7c90c406315b6049535

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.36rc20260609-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.36rc20260609-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d4fa2d4b224b2ec3f72fb1d85392d4fe92f30f34c248c0558b9eb686919713e1
MD5 4d9f76d34de25a6fdb115861afa98c55
BLAKE2b-256 2285ba1ccd4e0f28f6d43269deeb35071adb3a19dfff6b30ae11abc34fe1ee5a

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