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README

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

Extension points exported contracts — how you extend this code

Core symbols most depended-on inside this repo

Shape

Method 10,926
Function 4,015
Class 3,424
Interface 124
Enum 105
Route 40

Languages

C++68%
Java14%
Python13%
TypeScript4%
Kotlin1%
C1%

Modules by API surface

mediapipe/framework/calculator_graph_test.cc191 symbols
mediapipe/util/tracking/motion_estimation.cc119 symbols
mediapipe/framework/tool/template_parser.cc106 symbols
mediapipe/framework/api2/port.h96 symbols
mediapipe/tasks/java/com/google/mediapipe/tasks/vision/imagegenerator/ImageGenerator.java87 symbols
mediapipe/java/com/google/mediapipe/framework/PacketGetter.java85 symbols
mediapipe/util/tracking/region_flow_computation.cc83 symbols
mediapipe/framework/deps/vector.h82 symbols
mediapipe/util/tracking/motion_models.h77 symbols
mediapipe/gpu/gl_context.cc75 symbols
mediapipe/framework/calculator_graph_bounds_test.cc75 symbols
mediapipe/web/graph_runner/graph_runner.ts73 symbols

For agents

$ claude mcp add mediapipe \
  -- python -m otcore.mcp_server <graph>

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