MediaPipe
MediaPipe is an open-source, cross-platform framework for building and deploying on-device machine learning pipelines. It provides ready-to-use solutions for vision, text, and audio tasks, along with tools for customization and evaluation. It is intended for developers who want to integrate ML features into mobile, web, desktop, edge, and IoT applications.
✨ Key features
- Cross-platform APIs for vision, text, and audio tasks
- Pre-trained models ready to run on device
- Model Maker for customizing models with your data
- Studio for visualizing, evaluating, and benchmarking solutions
- Low-level framework for building custom ML pipelines
- On-device processing keeps input data private
🎯 Use cases
- Object detection in mobile apps
- Text classification for content moderation
- Audio classification for sound recognition
- Hand tracking for AR applications
- Pose estimation for fitness apps
📦 Installation
🧰 Requirements: Supports Android, iOS, web, desktop, edge devices, and IoT. Requires setting up a development environment for your target platform (e.g., Android, web, Python).
For installation instructions, refer to the setup guides for Android, web apps, and Python. For the MediaPipe Framework, see the install guide.
🚀 Usage
# Example from MediaPipe Python setup guide (simplified)
import mediapipe as mp
# Initialize a solution (e.g., Hands)
mp_hands = mp.solutions.hands
hands = mp_hands.Hands()
# Process an image
results = hands.process(image)
For full examples, see the developer guides for vision, text, and audio tasks.
⚠️ Good to know
MediaPipe Solutions Preview is an early release, and legacy solutions are no longer supported as of March 1, 2023, though their code and binaries remain available as-is.
❓ FAQ
Does MediaPipe send my data to Google servers?
No, when using MediaPipe Tasks, input data is processed on device and is not sent to Google servers. However, performance and utilization metrics are sent to Google.
What platforms does MediaPipe support?
MediaPipe supports mobile (Android, iOS), web, desktop, edge devices, and IoT.
Can I customize the pre-trained models?
Yes, MediaPipe Model Maker allows you to customize models for solutions with your own data.
What is the difference between MediaPipe Solutions and MediaPipe Framework?
MediaPipe Solutions provides ready-to-use libraries and tools for common ML tasks, while MediaPipe Framework is the low-level component for building custom on-device ML pipelines.
📊 Repository
🤖 Overview, features, install steps and FAQ were generated from the project's README on Sep 4, 2026. Always check the original source before running commands.