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
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 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.