# MirrorSentinel Elevator Elevator traversals recorded to study mirror and glass interference, as native `.mcap` episodes. A rig carrying a ZED2 camera, an Ouster 3D LiDAR and the Ouster IMU was walked through elevator cabins. A LiDAR pointed at a mirror reports returns from behind it, so the cabin appears to extend into space that is solid wall. Eight traversals cover seven physical cabins, and each cabin was measured by hand so the real boundary can be compared against what the sensors report. `elevator_02` and `elevator_03` are two runs of one cabin; the `footprint` field groups them. **Details** - Dataset name: `mirror-elevator` - Dataset source: [https://huggingface.co/datasets/Voxel51/MirrorSentinel-Elevator](https://huggingface.co/datasets/Voxel51/MirrorSentinel-Elevator) - Dataset size: 6.18 GB - Dataset license: CC-BY-4.0 - Tags: `multimodal, mcap, slam, lidar, imu` - Supported splits: `N/A` - ZooDataset class: [`MirrorSentinelElevatorDataset`](../../api/fiftyone.zoo.datasets.base.md#fiftyone.zoo.datasets.base.MirrorSentinelElevatorDataset) **Example usage** Python CLI ```python import fiftyone as fo import fiftyone.zoo as foz dataset = foz.load_zoo_dataset("mirror-elevator") # One run per physical cabin view = dataset.match({"sequence": {"$ne": "elevator_03"}}) session = fo.launch_app(dataset, view=view) ``` ```shell fiftyone zoo datasets load mirror-elevator fiftyone app launch mirror-elevator ```