Rerun
@rerundotio • 7,623 subscribers
The data layer for physical AI. ⭐ GitHub https://t.co/yf1KZN7DBI 👾 Discord https://t.co/7PIlvsZO9n
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We're releasing XDOF s ABC-130k dataset converted to RRD on a Hugging Face bucket, along with the conversion code. ABC-130k is the largest open-source bi-manual teleoperation dataset published to date. With Rerun, you can view all the episodes, query for insights, and use them in training workflows. One interesting finding is that annotators use varying levels of granularity for subtask labeling. Take the chess task in this video, for example: One episode uses language like 'place the chess piece', while another uses a fine-grained description like 'place the queen/pawn at E8'. This distinction is clearly visualized in Rerun through the colors in the state view! Our repo also includes a "mistake" query example and other interesting observations about the dataset, complementing the official ABC-130k dataset card. Download a subset and explore it yourself!! What other open datasets would you like to see in RRD?
Rerun21,430 görüntüleme • 1 ay önce
🚀 Rerun 0.23 is out! The highlights: 🔸Backwards-compatible .rrd – open today’s recordings with tomorrow’s viewer. 🔸 Viewer callbacks – wire the viewer into your notebooks or web apps and react to selections and time-scrubs in real-time, e.g., to build annotation tools. 👇
Rerun55,438 görüntüleme • 1 yıl önce
We recently crossed 10,000 GitHub stars on Rerun 😍 That's great and all, but something bigger is happening in robotics and Physical AI right now: The open-source ecosystem has seen real acceleration over the last few years. More teams are sharing real infrastructure: datasets, models, simulators, tooling, and the unglamorous plumbing that makes iteration possible. Jan Florian Maas, Physical Intelligence, Hugging Face are just some of the names driving this forward. Visualization and data infra belong in that category. If your entire data loop depends on being able to query and inspect what your robots are doing, that layer can’t be fragile or vendor-controlled. It needs to be something you can introspect, build on, extend, and trust long-term. Huge thanks to everyone building open-source robotics. The next decade of Physical AI will be built in the open.
Rerun29,684 görüntüleme • 8 ay önce
Debug ROS 2 transforms in Rerun 💡 ROS 2’s tf2 gives robotics teams a shared language for tracking coordinate frames over time — transforming data between things like camera_link and base_link. Rerun supports the same idea with named transforms, letting you decouple spatial relationships from your entity hierarchy. This example skips the basics of transforms in Rerun (you can find that in our docs) and instead shows how to debug broken/missing transforms in practice, using the JKK dataset. Check out the how-to 👇
Rerun15,982 görüntüleme • 8 ay önce
Rerun 0.22 is out! 🔎🟡🔜🔵 The release brings long-requested entity filtering for finding data faster in the Viewer, significantly simplified APIs for partial & columnar updates, and many other enhancements. At Rerun we’re building the multimodal data stack for physical AI. Our open-source visualization tools help you model and visualize your data over time.
Rerun15,092 görüntüleme • 1 yıl önce
Check out the Neural Graph Mapping for Dense SLAM with Efficient Loop Closure paper by Leonard Bruns, Jun Zhang, and Patric Jensfelt, visualized with Rerun. “Existing neural field-based SLAM methods typically employ a single monolithic field as their scene representation. This prevents efficient incorporation of loop closure constraints and limits scalability. To address these shortcomings, we propose a neural mapping framework which anchors lightweight neural fields to the pose graph of a sparse visual SLAM system.”
Rerun12,865 görüntüleme • 2 yıl önce
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