| --- |
| title: Hard Intersection Multimodal Sample |
| emoji: 🚦 |
| colorFrom: blue |
| colorTo: indigo |
| sdk: docker |
| app_port: 7860 |
| startup_duration_timeout: 30m |
| pinned: false |
| short_description: Multimodal AV dataset of a hard Tokyo intersection |
| --- |
| |
| # Hard Intersection Multimodal Sample |
|
|
| This Space runs the open source FiftyOne App in a Hugging Face Docker Space. |
|
|
| The Space loads |
| [`Voxel51/hard-intersection-multimodal-sample`](https://huggingface.co/datasets/Voxel51/hard-intersection-multimodal-sample) |
| into local ephemeral storage before FiftyOne starts. The dataset is |
| downloaded again whenever Hugging Face provisions a fresh container. |
|
|
| This is a **grouped** dataset: each of the 4 groups is one driving episode |
| through the Takanawadai intersection in Tokyo, Japan, with 6 synchronized |
| camera video slices and 1 3D point cloud slice per group. Frame-level labels |
| include COCO semantic detections, Lanelet2 HD map overlays, and the vehicle |
| trajectory projected onto the front camera. |
|
|
| Each browser receives a temporary clone of the dataset records while all |
| clones share the same read-only media. Filters, modal selection, playback, |
| tags, fields, and saved views therefore remain isolated between visitors. |
| Inactive clones expire after 30 minutes, cleanup runs every five minutes, |
| and the Space allows at most 20 active browser sessions. |
|
|
| ## Use your own datasets |
|
|
| Duplicate this Space and edit [`datasets.json`](./datasets.json) to replace or |
| extend the dataset list. Each entry must point to a FiftyOne-formatted Hub |
| dataset and an absolute local download path, then rebuild. |
|
|
