Visualize the LiDAR data from the [nuScenes dataset](https://www.nuscenes.org/). ## Used Rerun types [`Points3D`](https://www.rerun.io/docs/reference/types/archetypes/points3d) ## Background This example demonstrates the ability to read and visualize LiDAR data from the nuScenes dataset, which is a public large-scale dataset specifically designed for autonomous driving. The scenes in this dataset encompass data collected from a comprehensive suite of sensors on autonomous vehicles, including 6 cameras, 1 LIDAR, 5 RADAR, GPS and IMU sensors. It's important to note that in this example, only the LiDAR data is visualized. For a more extensive example including other sensors and annotations check out the [nuScenes example](https://www.rerun.io/examples/robotics/nuscenes_dataset). ## Logging and visualizing with Rerun The visualization in this example was created with just the following lines. ```python rr.set_time("timestamp", timestamp=sample_data["timestamp"] * 1e-6) # Setting the time rr.log("world/lidar", rr.Points3D(points, colors=point_colors)) # Log the 3D data ``` When logging data to Rerun, it's possible to associate it with specific time by using the Rerun's [`timelines`](https://www.rerun.io/docs/concepts/logging-and-ingestion/timelines). In the following code, we first establish the desired time frame and then proceed to log the 3D data points. ## Run the code To run this example, make sure you have the Rerun repository checked out and the latest SDK installed: ```bash pip install --upgrade rerun-sdk # install the latest Rerun SDK git clone git@github.com:rerun-io/rerun.git # Clone the repository cd rerun git checkout latest # Check out the commit matching the latest SDK release ``` Install the necessary libraries specified in the requirements file: ```bash pip install -e examples/python/lidar ``` To experiment with the provided example, simply execute the main Python script: ```bash python -m lidar # run the example ``` If you wish to customize it, explore additional features, or save it use the CLI with the `--help` option for guidance: ```bash python -m lidar --help ```