Datasets:
File size: 3,948 Bytes
83e0b13 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 | ---
license: apache-2.0
authors:
- "Selinaliu1030"
task_categories:
- robotics
tags:
- tsfile
- timeseries
- tabular
modality:
- timeseries
- tabular
pretty_name: "Egg 0806 TsFile"
configs:
- config_name: default
data_files:
- split: train
path: data/selinaliu1030_egg_0806.tsfile
size_categories:
- 10K<n<100K
---
# Egg 0806 TsFile
This dataset is an Apache TsFile conversion of
[`Selinaliu1030/egg_0806`](https://huggingface.co/datasets/Selinaliu1030/egg_0806), a LeRobot v2.1 SO101 robot-manipulation dataset.
It contains numeric trajectories, timing, episode/task tags, and source
metadata. Videos remain in the original Hugging Face repository.
## Source Dataset and Attribution
- Original dataset: [`Selinaliu1030/egg_0806`](https://huggingface.co/datasets/Selinaliu1030/egg_0806)
- Original author/publisher: [Selinaliu1030](https://huggingface.co/Selinaliu1030)
- Authorship note: the source card names no separate authors; this README
attributes the dataset to its Hugging Face repository publisher.
- License: Apache-2.0
- Task: "Grasp the egg and put it in the red bin."
- Robot: `so101`; LeRobot version: `v2.1`
- Split: `train`; sampling rate: 30 fps
- Scale: 90 episodes, 49,957 frames, 1 task
- Source shards: 90 Parquet files under
`data/chunk-000/episode_{episode_index:06d}.parquet`
- Paper/citation: the source card provides neither a paper nor a completed citation.
## Schema
| TsFile column(s) | Type | Role | Source |
| --- | --- | --- | --- |
| `Time` | INT64 | TIME | `round(timestamp * 1000)` ms |
| `episode_index` | STRING | TAG/device | source `episode_index` |
| `task_index` | STRING | TAG/device | source `task_index` |
| `frame_index` | INT64 | FIELD | source `frame_index` |
| `sample_index` | INT64 | FIELD | source `index` |
| `action_0` ... `action_5` | FLOAT | FIELD | flattened `action[6]` |
| `observation_state_0` ... `observation_state_5` | FLOAT | FIELD | flattened `observation.state[6]` |
The six action/state dimensions are `main_shoulder_pan`,
`main_shoulder_lift`, `main_elbow_flex`, `main_wrist_flex`,
`main_wrist_roll`, and `main_gripper`. Dots in source vector names are replaced
by underscores. Time restarts at zero for every episode.
## Conversion Details
- The 90 train episode shards are merged into one table-model TsFile.
- Source `timestamp` is dropped after Time synthesis because it is exactly
represented by `Time / 1000` seconds.
- Source `index` is retained as `sample_index`; `frame_index` is unchanged.
- No numeric row, episode, task, state dimension, or action dimension is dropped.
- FLOAT/DOUBLE uses GORILLA + LZ4; INT32/INT64 and Time use TS_2DIFF + LZ4;
BOOLEAN uses RLE + LZ4; TAG values use the TsFile table/device mechanism.
## Videos
Videos are not included in this TsFile repository. The original dataset has
180 frame-aligned AV1 MP4 files (301,079,898 bytes, about 287.1 MiB), 640x480,
30 fps, no audio, in two streams:
- [`observation.images.laptop`](https://huggingface.co/datasets/Selinaliu1030/egg_0806/tree/efbe3ca1282a5e128d920c12c2b6c444036e6d17/videos/chunk-000/observation.images.laptop)
- [`observation.images.phone`](https://huggingface.co/datasets/Selinaliu1030/egg_0806/tree/efbe3ca1282a5e128d920c12c2b6c444036e6d17/videos/chunk-000/observation.images.phone)
Each stream contains 90 files matching
`videos/chunk-000/{video_key}/episode_{episode_index:06d}.mp4`.
`episode_index`, `frame_index`, and `meta/episodes.jsonl` preserve alignment.
## Usage
```python
from tsfile import TsFileReader
reader = TsFileReader("data/selinaliu1030_egg_0806.tsfile")
with reader.query_table(
"selinaliu1030_egg_0806",
["episode_index", "task_index", "frame_index", "sample_index",
"action_0", "observation_state_0"],
batch_size=65536,
) as result:
print(result.read_arrow_batch().to_pandas().head())
reader.close()
```
|