azithromycin/williamdgomez_SNOW.SB

SNOW.SB TsFile

This repository is an Apache TsFile conversion of the LeRobot dataset `williamdgomez/SNOW.SB`. The original Hugging Face repository and its commit history identify williamdgomez as the dataset author/uploader. The source dataset was created with LeRobot v3.0 for the lekiwi_client robot.

Source Dataset

• —Dataset: `williamdgomez/SNOW.SB`
• —Author/uploader: `williamdgomez`
• —License: Apache-2.0
• —Task: Pick up the block and place it in the bin
• —Split: train (0:91)
• —Sampling rate: 24 fps
• —Scale: 91 episodes, 73,578 frames, 1 task
• —Source data shards: 91 Parquet files under data/chunk-000/file-*.parquet
• —Source video files: 273 MP4 files, 91 per camera stream

The source video streams are stored at `videos/`:

• —videos/observation.images.front/chunk-000/file-{file_index:03d}.mp4
• —videos/observation.images.wrist/chunk-000/file-{file_index:03d}.mp4
• —videos/observation.images.top/chunk-000/file-{file_index:03d}.mp4

Videos are not included in this TsFile repository. They remain available in the original Hugging Face dataset and can be aligned with rows using episode_index, frame_index, and the source meta/episodes offsets.

Converted Files

• —TsFile: data/williamdgomez_snow_sb.tsfile
• —Table: williamdgomez_snow_sb
• —Rows: 73,578
• —Devices: 91 (episode_index x task_index)
• —Time precision: milliseconds
• —Metadata: meta/ mirrors the source metadata; meta/info.json records the TsFile path and conversion mapping.

Schema

Time is round(timestamp * 1000) and is stored in milliseconds. The source timestamp is dropped after this conversion because it is exactly the seconds representation of Time; Time restarts at zero for each episode.

Vector names preserve their source prefixes (. becomes _) and append a zero-based element index. The three video features (observation.images.front, .wrist, .top) are omitted from the TsFile because TsFile stores the numeric time-series table while the original MP4 files remain at the source URL.

Encoding and Compression

The local conversion used the type-aware TsFile writer profile requested for this dataset:

• —FLOAT/DOUBLE: GORILLA with LZ4
• —INT32/INT64 and Time: TS_2DIFF with LZ4
• —BOOLEAN (if present): RLE with LZ4
• —TAG columns: TsFile table/device TAG mechanism

The generated TsFile is 1,456,157 bytes. The merged staged Parquet is 1,235,578 bytes, and the 91 source Parquet shards total 3,152,836 bytes.

Validation

Apache TsFile Python SDK readback succeeded. The TsFile metadata row count and query readback both equal the staged Parquet count: 73,578 rows. All 91 episode devices have monotonic Time values with no duplicate (episode_index, task_index, Time) keys.

Usage

from tsfile import TsFileReader

reader = TsFileReader("data/williamdgomez_snow_sb.tsfile")
table = reader.get_all_table_schemas()["williamdgomez_snow_sb"]
columns = [c.get_column_name() for c in table.get_columns() if c.get_column_name() != "Time"]

with reader.query_table("williamdgomez_snow_sb", columns, batch_size=65536) as result:
    batch = result.read_arrow_batch()

Citation

The original dataset card does not provide a paper or BibTeX citation.