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Datasets:
mengqz9
/
deva_libero

Tasks:
Robotics
Video Classification
Modalities:
Text
Video
Formats:
text
Size:
1K - 10K
Tags:
robotics
world-model
video-prediction
imitation-learning
depth-estimation
affordance
Libraries:
Datasets
License:
Dataset card Data Studio Files
xet
 Community
Dataset Viewer
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40 values
turn on the stove and put the moka pot on it.
turn on the stove and put the moka pot on it.
turn on the stove and put the moka pot on it.
put the yellow and white mug in the microwave and close it.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
put the yellow and white mug in the microwave and close it.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
put the yellow and white mug in the microwave and close it.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
put the yellow and white mug in the microwave and close it.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
put the yellow and white mug in the microwave and close it.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
pick up the milk and place it in the basket.
put the yellow and white mug in the microwave and close it.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
put the yellow and white mug in the microwave and close it.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
put the yellow and white mug in the microwave and close it.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
put the yellow and white mug in the microwave and close it.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
pick up the salad dressing and place it in the basket.
End of preview. Expand in Data Studio

DeVA — LIBERO (processed)

Processed LIBERO data for DeVA, a robot video-world model with affordance + depth physical guidance. Derived from Lifelong-Robot-Learning/LIBERO — please cite the original benchmark as well.

Episodes 2,000
Frames 338,575
Video 432 × 768, 16 fps (2 views tiled side by side)
Views agentview, eye_in_hand
Action dim 7 (absolute)
Proprio state not included
Size 9.6 GB

Download 

hf download mengqz9/deva_libero --repo-type dataset --local-dir datasets/deva_libero

Layout 

deva_libero/
├── dataset_info.json   # view names, tile grid, affordance/depth encodings
├── videos/             # <episode>.mp4   tiled multi-view RGB
├── metas/              # <episode>.txt   language instruction
├── t5_xxl/             # <episode>.pickle  precomputed T5-XXL embedding [n_tok, 1024]
├── action.json         # {episode: [[a_0..a_6], ...]}  len == video frames
├── data_mapping.json   # episode -> source task
├── norm_stats.json     # action normalization statistics
├── affordance/         # <episode>.npz   physical guidance (optional at train time)
└── depth/              # <episode>.npz   physical guidance (optional at train time)

videos/ tiles the views on the grid given by dataset_info.json::tile:

[[agentview, eye_in_hand]]

Affordance / depth .npz

Both are keyed by canonical view name (never by tile position), one array per view:

affordance depth
key <view> <view>
dtype float16 float16
shape [T, 128, 128] [T, 128, 128]
range raw, un-normalized [0, 1]
note loader resizes to 128×128, then per-frame max-normalizes per-view per-clip min-max applied at export

T equals the episode's video frame count, so aux arrays index by absolute frame. The validity mask is derived from the tile grid (null cells are invalid) and is not stored.

Depth source — DepthAnything (ViT-L) disparity, converted as depth = 1 / disparity; higher value = farther. The far tail is clipped at the 98th percentile before per-view min-max, so ~2% of pixels saturate at 1.0.

Affordance source — simulator oracle contacts rendered as Gaussian heatmaps.

Citation

If you use this data, please cite DeVA and LIBERO:

@article{liu2023libero,
  title   = {LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning},
  author  = {Liu, Bo and Zhu, Yifeng and Gao, Chongkai and Feng, Yihao and
             Liu, Qiang and Zhu, Yuke and Stone, Peter},
  journal = {NeurIPS Datasets and Benchmarks},
  year    = {2023}
}
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