google-ai-edge / mediapipe
- четверг, 17 октября 2024 г. в 00:00:01
Cross-platform, customizable ML solutions for live and streaming media.
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Attention: We have moved to https://developers.google.com/mediapipe as the primary developer documentation site for MediaPipe as of April 3, 2023.
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.
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.
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:
These tools let you customize and evaluate 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.
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:
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.