Rerun

Rerun 0.17: defaults and overrides, streaming in notebooks, and better website embeddings The release brings a huge increase in explicit control over your visualizations. You can now use blueprints to both set default component values on a view, and to override components on specific entities in the view. You can do this both from code and in the UI. In the video, we use a default to bulk edit the size of all camera frustums and an override to edit just the front-facing frustum size. With the introduction of blueprint overrides and defaults, Rerun 0.17 gives you direct control over what visualizers are applied to what entities and makes all of this easy to inspect in the UI. Together, these features increase the amount of flexibility and control you have over exactly how your data is visualized in Rerun. Beyond defaults and overrides, this release also comes with: 🔸 Improved notebook and website embedding support 👉 You can now stream data from the notebook cell to the embedded viewer. 👉 There is improved support for having multiple viewers on the same web page. 👉 And you have more more configuration options to control the visibility of the Menu bar, time controls, etc. 🔸 Additional configurability from code, for example: 👉 ImagePlaneDistance(size of the Pinhole frustum visualization) 👉 AxisLength(axis length of the transform visualization) 👉 and all settings on TensorViews 🔸 New examples: 👉 PaddleOCR 👉 Vista, a generative driving world model 👉 Stereo Vision SLAM And much more 🚀🚀🚀 Check out the blog post on overrides and defaults, and the full change log in the links in the comments 👇

Rerun 0.17 is out and it’s truly a big one! It makes it much easier to embed Rerun views in your web-apps, brings a big upgrase to the notebook experience, and enables a massive expansion of the control you can have over visualizations from blueprint, Rerun’s language for describing multimodal visualizations from code or UI interactions. The ability to set defaults or override any data from blueprint, together with the notion that all possible inputs to visualizations are data, is super powerful and a key piece of the multimodal visualization system that we’ve been designing and building towards for a long time. We believe teams building robotics and embodied AI products should be able to unify their visualization and data debugging stack and have been going too extreme lengths over the last two years to make that possible. That includes everything from a custom code generation framework, our own in-memory multimodal time series database, a cross platform renderer, and a new kind of system for describing visualizations and feeding them with streaming data. We have a lot more coming in the next months but in the meantime I’m incredibly proud of everything we’ve achieved so far and excited to hear what everyone in the community does with this last release!

The upcoming Rerun 0.17 brings a huge increase in explicit control you have over your visualizations 🚀 In this video for example we dynamically change the visualizer that is applied on an entity from Mesh3D to Points3D and then edit the radius of the points. Because this mesh has vertex colors, the point cloud automatically becomes colored as well. All of this can be done either from UI or from code. We’ll release 0.17 next week. Stay tuned.

The upcoming Rerun 0.17 brings a huge increase in explicit control you have over your visualizations 🚀 In this video for example we dynamically change the visualizer that is applied on an entity from Mesh3D to Points3D and then edit the radius of the points. Because this mesh has vertex colors, the point cloud automatically becomes colored as well. All of this can be done either from UI or from code. We’ll release 0.17 next week. Stay tuned.

We couldn't be more excited to welcome Katerina Gavrilo to team Rerun as our first full-time Designer 🥳🦾👩🎨

Precise box measurement 📦 using AI and Time-of-Flight (ToF) technology! In his article, Erik Kokalj examines the implementation of the ToF camera OAK-D-SR-PoE to achieve accurate and efficient volumetric measurements. AI model from Roboflow is applied, data are processed by OpenCV & Open3D and Rerun is used for visualization. More details and source code are included in Erik's blog post. ⏬ https://lnkd.in/emDuUtjp #OAKCamera #ToF #AI

Box Dimensioning 📦📏 with RGB-D from a ToF sensor and edge #AI inferencing! Utilizing Luxonis' OAK-D-SR-POE camera, Roboflow's AI model, OpenCV & Open3D for processing, and Rerun for visualization. I also wrote a blog post (with #Python source code) on the step-by-step logic and processing: https://lnkd.in/gcrD56v5 #ComputerVision #3D #Cameras #Robotics #Warehouse #Manufacturing #Programming #OpenSource

Vista is a generative driving world model by Gao et al. Built on Stable Video Diffusion it can generate driving scenes conditioned on a single input image and optional, additional control inputs. In this example we visualize the latent diffusion steps and the generated, decoded image sequence. Check out the code on the link below, or try the example with your own street images on the Hugging Face space (links in the comments).

A Rerun Viewer for the DROID Dataset! 🦾 DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset is a robot manipulation dataset with 76k demonstration trajectories or 350h of interaction data collected across 564 scenes and 86 tasks. In the Rerun Viewer, you see a URDF of the robot arm, 2D and 3D from the Zed stereo cameras, and 2D from the wrist-mounted Zed Mini stereo camera. In addition, you get time series for torques and velocities. You can find the code for the Viewer in the link in the comments! 👇

We turned the #PaddleOCR example into a Hugging Face Space! Just drag in your images and PDFs to experiment with OCR visualized with Rerun. PP-Structure is an intelligent document analysis system developed by the PaddleOCR team. It helps developers better complete tasks related to document understanding, such as text recognition, layout analysis, and table recognition. The Space is built using the custom rerun-gradio component by Radamés Ajna 💐 Happy Midsommar to all of you! 💐 Check it out (link in the comments)👇