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-1.0.0rc20260625-py3-none-win_arm64.whl (28.7 MB view details)

Uploaded Python 3Windows ARM64

mediapipe_nightly-1.0.0rc20260625-py3-none-win_amd64.whl (29.5 MB view details)

Uploaded Python 3Windows x86-64

mediapipe_nightly-1.0.0rc20260625-py3-none-manylinux_2_28_x86_64.whl (22.5 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ x86-64

mediapipe_nightly-1.0.0rc20260625-py3-none-manylinux_2_28_aarch64.whl (21.1 MB view details)

Uploaded Python 3manylinux: glibc 2.28+ ARM64

mediapipe_nightly-1.0.0rc20260625-py3-none-macosx_11_0_arm64.whl (35.4 MB view details)

Uploaded Python 3macOS 11.0+ ARM64

File details

Details for the file mediapipe_nightly-1.0.0rc20260625-py3-none-win_arm64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.0rc20260625-py3-none-win_arm64.whl
Algorithm Hash digest
SHA256 9ed37f4fcda674bd2a6522bb554c5b89790a4f31b64165856787424640088511
MD5 a54ef443fb850d6b57c5ef63d319dcdb
BLAKE2b-256 b3713eff366251f3cb2ef3343c3ae4427478fa34a9a4c45f7177ced90503a6be

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-1.0.0rc20260625-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.0rc20260625-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 ad01d368a7022963cae809412156d4ce30c50509eb4c3289d76cc6b03e0caf72
MD5 5b36dddda863104533e71d05062a7d76
BLAKE2b-256 3cf92a2951f5c2755fec01d3fcfb5403df3bbf6689f45c53be1faf00c6f250d3

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-1.0.0rc20260625-py3-none-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.0rc20260625-py3-none-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 05199f17cd08fdbc7dfb2bf02abceffbaade43faa29fd6d946abea9439d56ff3
MD5 3d5d16f507243500eac2920b6ff42d10
BLAKE2b-256 b23527b6f704d3b0c022ea3d4276cd37e40b559eaf2efd4029e36f9b3116b8fc

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-1.0.0rc20260625-py3-none-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.0rc20260625-py3-none-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 49c23ec7dc23ecf9d4e2a54021d65d949041e5ddb79cb1d21c33dfd7c78554d2
MD5 18e8bd4656b51941aa91e8eeb6f9d7ae
BLAKE2b-256 efdc9dc54d9eb16f243b2e276a0a68330441bad2a0aaa29836bf20dc21cb9eae

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-1.0.0rc20260625-py3-none-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-1.0.0rc20260625-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 590f9ec1fc4930ef6e2040e62edc00df9475ca53dc2c05063ca15333b496b526
MD5 e32545ebc2a74e8e600710c9e535a426
BLAKE2b-256 e130eea50fe2842a60f37a7c7f72d3128e905ca12d21b5d38e83eee293a8b4e4

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