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.

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.

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-0.10.21.post20250125-cp312-cp312-manylinux_2_28_x86_64.whl (35.6 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

mediapipe_nightly-0.10.21.post20250125-cp311-cp311-manylinux_2_28_x86_64.whl (35.6 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

mediapipe_nightly-0.10.21.post20250125-cp310-cp310-manylinux_2_28_x86_64.whl (35.6 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

mediapipe_nightly-0.10.21.post20250125-cp39-cp39-manylinux_2_28_x86_64.whl (35.6 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.28+ x86-64

File details

Details for the file mediapipe_nightly-0.10.21.post20250125-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250125-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 e85598ba8428998943263bc73108b80483c05233e8242cb9ee08d31485d2342f
MD5 cc118641d7f8f12a46f793a46c026960
BLAKE2b-256 14821a5d32a31a443424fb4c6dc96a2138f339aeeeef55449811d4aa9f37ffdb

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.21.post20250125-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250125-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 110eedc9461b708442bc910870d753a3d84839f68254b16c76edc6668663daa5
MD5 5c74821016745588722d7020426794d9
BLAKE2b-256 1a1cb2005da1cf8cf921a1ecc85bf17b441ceec868835de1ecc969bdb8919689

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.21.post20250125-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250125-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 9c9d48e8c6ca1dc4d913e267da470983543bb4d19384dda508edde2a08964401
MD5 6cad2aaf988bf0f7ea4e314e5da88e60
BLAKE2b-256 159958f2a5ee8fbe9467df24397277af10628a8faafd3e4f584e70024a75ea26

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.21.post20250125-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250125-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 033e739056dacbdf99405b72d6788ff63382ca52aa0e7aa6f7f4899c11348089
MD5 2513518ddf6fd8df9576cfbedcebb79b
BLAKE2b-256 2e15505f8e414132a16270e22155c27564ff05d07d7d7f0cd92602c887a5ab38

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