THULab/sergiov2000_test_yellow_50_episodes

Sergiov2000 Test Yellow 50 Episodes TsFile

This dataset is an Apache TsFile representation of sergiov2000/test_yellow_50_episodes, a LeRobot v2.1 SO100 robot-manipulation dataset containing 50 demonstrations of the task Pick the yellow lego block and put it in the box.

This repository contains numeric robot states, actions, frame timing, and episode/task tags. The two camera streams remain in the original Hugging Face dataset and are linked below.

Source Dataset and Provenance

• Original dataset: sergiov2000/test_yellow_50_episodes
• Original repository creator and uploader: sergiov2000
• License: Apache-2.0
• Robot type: so100
• LeRobot codebase version: v2.1
• Task: Pick the yellow lego block and put it in the box. (task_index = 0)
• Split: train
• Sampling rate: 30 fps
• Scale: 50 episodes, 42,802 frame rows, 1 task, 50 source Parquet files, 100 source videos
• Source frame layout: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet
• Source video layout: videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4

The source dataset card provides no paper or completed citation.

TsFile Data

• TsFile: data/sergiov2000_test_yellow_50_episodes.tsfile
• Table: sergiov2000_test_yellow_50_episodes
• Rows: 42,802
• Episodes/devices: 50
• TsFile size: 0.53 MiB
• Numeric source Parquet size: 1.75 MiB
• TsFile/Parquet size ratio: 0.3018
• Time precision: milliseconds
• Metadata: the source JSON and JSONL files under meta/ are retained, and meta/info.json points data_path to the TsFile.

TsFile Schema

Time is an INT64 millisecond timestamp computed as round(timestamp * 1000) and restarts at zero for each episode.

TAG columns, stored through the TsFile table-model device/tag mechanism:

• episode_index
• task_index

FIELD columns:

• frame_index
• sample_index
• action_0
• action_1
• action_2
• action_3
• action_4
• action_5
• observation_state_0
• observation_state_1
• observation_state_2
• observation_state_3
• observation_state_4
• observation_state_5

Flattened vector groups:

• action -> action_0 ... action_5 (6 FLOAT fields)
• observation.state -> observation_state_0 ... observation_state_5 (6 FLOAT fields)

Conversion Notes

• The train split is merged into one table-model TsFile. Filter by episode_index and task_index to select an episode or task.
• Storage profile: Time uses TS_2DIFF + LZ4; FLOAT/DOUBLE use GORILLA + LZ4; INT32/INT64 use TS_2DIFF + LZ4; BOOLEAN, if present, uses RLE + LZ4. Physical codecs were checked from the generated TsFile.
• episode_index and task_index are TsFile TAG/device columns.
• action[6] and observation.state[6] are flattened to scalar FLOAT fields; the full source prefix is retained and . is replaced with _.
• The source timestamp column is dropped after Time synthesis because it is redundant with Time / 1000 seconds.
• The source index column is retained as sample_index; frame_index is retained unchanged.
• No rows or numeric trajectory dimensions are dropped.
• Source video features are intentionally omitted from the TsFile because they are external MP4 assets.

Videos

Videos are not duplicated in this repository. The original dataset contains two frame-aligned camera streams:

• observation.images.above - 50 per-episode MP4 files, 805,243,265 bytes
• observation.images.side - 50 per-episode MP4 files, 758,692,739 bytes

Together the 100 MP4 files occupy 1,563,936,004 bytes. Numeric rows remain aligned with the original videos through episode_index, frame_index, and the source per-episode metadata.

Minimal Read Example

from tsfile import TsFileReader

reader = TsFileReader("data/sergiov2000_test_yellow_50_episodes.tsfile")
columns = [
    "episode_index",
    "task_index",
    "frame_index",
    "sample_index",
    "action_0",
    "observation_state_0",
]

with reader.query_table("sergiov2000_test_yellow_50_episodes", columns, batch_size=65536) as result:
    batch = result.read_arrow_batch()
    print(batch.to_pandas().head())
reader.close()

Citation

The source dataset card provides no paper or completed BibTeX citation. Cite the original Hugging Face dataset and its repository creator, sergiov2000, when using this TsFile dataset.