Rerun
Overview of Rerun
What is Rerun?
Rerun is an open-source data stack designed for Physical AI, providing multimodal log handling and visualization. It offers managed infrastructure to ingest, store, analyze, and stream data at scale with built-in visual debugging, making it fast, flexible, and easy to use.
Key Features:
- Open Source: Dual-licensed under MIT and Apache 2.
- Multimodal Visualization: Supports various data types including 3D, images, and time series.
- Easy to Use: Simple installation and minimal code required to get started.
- Embeddable: Visualizer runs natively, on the web, and can be embedded in notebooks and web apps.
How to Use Rerun?
Installation:
pip install rerun-sdkQuick Start Guide (Python):
import rerun as rr rr.init("my_data_generating_application") rr.connect() # Connect to a remote viewer ... rr.log("points", rr.Points3D(positions)) rr.log("camera", rr.Transform3D(pos, rot)) rr.log("camera/image", rr.Pinhole(intrinsics)) rr.log("camera/image", rr.Image(tensor)) rr.log("reprojection_error", rr.Scalar(err))
Why is Rerun Important?
Rerun simplifies the data engine for physical AI by allowing users to:
- Run and record data for analysis and training.
- Understand behavior and pinpoint issues with the Rerun viewer.
- Visualize training and eval, debug prototypes, and extract time-aligned training samples from messy logs.
Where Can I Use Rerun?
Rerun can be used in various applications, including:
- Robotics
- Autonomous Vehicles
- Computer Vision
- AI research and development
Best Way to Get Started with Rerun?
- Try the Browser Demo: Explore the features without installation.
- Read the Documentation: Understand the capabilities and usage.
- Join the Community: Engage with other users on GitHub and Discord.
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