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.post20250208-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.post20250208-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.post20250208-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.post20250208-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.post20250208-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250208-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 ccdfbea0e4aa9fe9b97228f56fc05cdca185d26dfbd31b1760f76a46cdd4ceac
MD5 2f77136f2a12d333ec0ab04f02985126
BLAKE2b-256 ac50333912718d92be801b31d13bfbe2c9176582d038b004328becafa1e4fba4

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.21.post20250208-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250208-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c046e2e501aee3f10b1cfd73b4fec7b714af45285d063c55f7dcd427f9205457
MD5 ab82fce3954c8ad6d0bb4028d5e29eba
BLAKE2b-256 a69d82838d9b68af2fe738f891c3681f907f5e651167ccbee9e69f939e3be236

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.21.post20250208-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250208-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f86d48d017a8df32e22285a2a07914735bad5dd738199b664dadb5bf63fd108b
MD5 8877f413f272e179a1088b151ef458bc
BLAKE2b-256 42d65782417007049f2e2d4ed508277c3ee930653773b4b49b1cb4b69dfdda1d

See more details on using hashes here.

File details

Details for the file mediapipe_nightly-0.10.21.post20250208-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for mediapipe_nightly-0.10.21.post20250208-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 8db0b9ed85090855ed362a24a0edade4c2d060ee7b81c2786d41f347e7034b67
MD5 ff123434d1250d4c48470e2611494e81
BLAKE2b-256 0a8f0bb3d1755f126f1dbce29621b4fdc4bdebb333c9278fc9e77ba9ee38aeea

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