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observation.state list | action list | timestamp float32 0 20 | frame_index int64 0 599 | episode_index int64 0 4 | index int64 0 599 | task_index int64 0 4 |
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End of preview. Expand in Data Studio
EgoStation Smartphone — playable sample
Five short first-person clips of everyday household work, one per task, laid out in LeRobot v2.1 so they can be scrubbed directly in the dataset visualiser.
This is a preview, not the corpus. It exists because
zeno-labs/egostation-smartphone-raw-v1
publishes its samples as loose video.mp4 / pose_keypoints.json files, which
no viewer knows how to open. Same footage, rearranged so it plays.
What is in it
| Episodes | 5 — washing dishes, cooking, folding laundry, tidying shoes, wiping surfaces |
| Length | 20 s each, 600 frames, 30 fps |
| Video | observation.images.head — 640×360 (downscaled from 1920×1080) |
| State | 126 floats per frame: 21 MediaPipe hand landmarks × (x, y, z) × 2 hands |
observation.state is normalised to 0–1 against the source resolution, so the
numbers compare across takes. Frames where a hand was not detected are zeroed;
per-episode detection rates run 90–99%. action is the next frame's state —
there is no robot here, so the thing to imitate is where the hands go next.
Provenance
Each clip is the first 20 seconds of a 15–17 minute recording contributed through the Zen-O app. The full takes, their depth overlays and the complete keypoint tracks live in the raw dataset above; this one is deliberately small.
Hand keypoints are MediaPipe Hands v0.10 output, not human annotation.
Licence
CC BY-NC 4.0 — non-commercial. For the full corpus or commercial terms, contact support@zen-o.xyz.
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