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?

1. Installation:

   pip install rerun-sdk
   

2. Quick 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.