# ColoRadar Sample A sample of the ColoRadar 3D millimetre-wave radar dataset, as native `.mcap` episodes. A handheld rig carries a TI cascaded imaging radar and a TI single-chip radar beside an Ouster OS1-64 LiDAR and a Microstrain inertial unit, through hallways, a lab, a motion-capture space, outdoor built environments, the narrow and the large passages of an underground mine, and a fast ride along paths and roads. Each episode carries both radars’ point clouds, a top-down render of each cascaded radar heatmap, the LiDAR scans, the inertial unit and the release’s LiDAR-inertial ground truth. 7 sequences, one from each of the seven places the release records, 13 minutes 46 seconds of recording, 8,263 LiDAR scans holding 382.6 million points, 4,145 cascaded radar frames and 8,340 single-chip radar scans. **Details** - Dataset name: `coloradar-sample` - Dataset source: [https://huggingface.co/datasets/Voxel51/ColoRadar-Sample](https://huggingface.co/datasets/Voxel51/ColoRadar-Sample) - Dataset size: 6.47 GB - Dataset license: Apache-2.0 - Tags: `multimodal, mcap, radar, lidar, robotics` - Supported splits: `N/A` - ZooDataset class: [`ColoRadarSampleDataset`](../../api/fiftyone.zoo.datasets.base.md#fiftyone.zoo.datasets.base.ColoRadarSampleDataset) **Example usage** Python CLI ```python import fiftyone as fo import fiftyone.zoo as foz dataset = foz.load_zoo_dataset("coloradar-sample") # The sequences that covered the most ground view = dataset.sort_by("ground_truth_path_m", reverse=True) session = fo.launch_app(dataset, view=view) ``` ```shell fiftyone zoo datasets load coloradar-sample fiftyone app launch coloradar-sample ```