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.post20250131-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.post20250131-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.post20250131-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.post20250131-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.post20250131-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250131-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f95132d9c414468dad2d94101c326c56aa577e879b619c1aeb3839e0960d79f9
MD5 4f5885b6da77f339e2af347436d2cba6
BLAKE2b-256 71a94537460ab96278a12b81d696964fe14c2479137b64a6cd1f59f0c095c531

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.21.post20250131-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250131-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 561dbdac31a63a2630be78e1a98a929b13a93d154bf9d2eeca305e1b15d62895
MD5 4b58b8ca99308de1707463eb2d5bd5cb
BLAKE2b-256 c5bd701d90130f4c5a999c3ce45207ce1608a45a105a5abed4c16bf67d3efe16

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.21.post20250131-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250131-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 353de1912f4d5f20300590433e9f1528899435a8b16d3500500c5cc606f010d1
MD5 5f90ef9a02effc653de91b8fdb413f7a
BLAKE2b-256 8141c82942a7ac2946b378e3675a6ca234da63f64a2eb105d97f3434f1658119

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.21.post20250131-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250131-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 2eadc74c26447a0e38cf82a410f41929dbb30cb868e1ecbf70d823a6d2b977a1
MD5 cde99e0a6de8ff89574e98925ca92f88
BLAKE2b-256 84555e536e2a4d2b08c6a6b6c869fa4f524b4c738f93e08e8bc9b12e9c784e60

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