Rerun

What is Rerun?

Rerun is a powerful data platform designed specifically for robotics learning, enabling users to ingest, visualize, annotate, query, and transform data from collection to training seamlessly. It provides a unified infrastructure that accelerates the process of building and iterating on robotics applications by allowing users to visualize their robot logs and convert them into training datasets. Rerun supports multiple programming languages, including Python, C++, and Rust, making it accessible for a wide range of developers in the robotics field.

How to use Rerun?

1. Install the Rerun SDK: Use the command `pip install rerun-sdk` for Python, or follow the installation instructions for C++ or Rust on the website.
2. Initialize Rerun: Start your data-generating application by initializing Rerun with `import rerun as rr` and `rr.init("my_data_generating_application")`.
3. Connect to Viewer: Establish a connection to the Rerun viewer using `rr.connect()` to visualize your logs in real-time.
4. Log Data: Use the logging functions like `rr.log("points", rr.Points3D(positions))` to send your data to Rerun for visualization.
5. Visualize and Analyze: Access the Rerun viewer to explore, analyze, and debug your logged data effectively.

What are the main features of Rerun?

• Multi-format Data Ingestion: Supports ingestion of various robotics log formats for comprehensive data management.
• Powerful Visualization Tools: Offers advanced visualization capabilities to explore and debug robotics data interactively.
• Flexible Data Transformation: Provides pipelines to transform raw logs into training-ready datasets efficiently.
• Fast Query Engine: Features optimized dataframe queries specifically designed for robotics data, allowing quick analysis.
• Collaboration Features: Enables easy sharing of data and visualizations with team members for collaborative debugging and development.

Who is Rerun for?

Rerun is targeted at robotics developers, researchers, and engineers who are looking to enhance their workflows in data visualization and machine learning. It is particularly beneficial for teams working on robotics applications in industries such as automation, AI research, and real-time localization and mapping. Organizations that require a streamlined process for managing and transforming large datasets will find Rerun invaluable in accelerating their development cycles.

What are the use cases of Rerun?

1. Robotics Data Visualization: Use Rerun to visualize robot performance logs, enabling teams to quickly identify anomalies and improve models.
2. Training Data Preparation: Transform raw robotics logs into structured datasets suitable for machine learning training, enhancing the quality of AI models.
3. Collaborative Debugging: Facilitate team collaboration by sharing visualizations and data insights, helping teams debug issues collectively in real-time.