| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| tags: |
| - tsfile |
| - timeseries |
| - tabular |
| modality: |
| - timeseries |
| - tabular |
| pretty_name: G1 Dex3 Block Stacking TsFile |
| size_categories: |
| - 100K<n<1M |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/unitreerobotics_g1_dex3_blockstacking.tsfile |
| --- |
| |
| # G1 Dex3 Block Stacking TsFile |
|
|
| This repository is an Apache TsFile conversion of |
| [`unitreerobotics/G1_Dex3_BlockStacking_Dataset`](https://huggingface.co/datasets/unitreerobotics/G1_Dex3_BlockStacking_Dataset), |
| a LeRobot manipulation dataset for stacking three cubic blocks on a desktop in |
| red, yellow, and blue order. |
|
|
| ## Source dataset |
|
|
| - Original dataset: https://huggingface.co/datasets/unitreerobotics/G1_Dex3_BlockStacking_Dataset |
| - Author / repository owner: Unitree Robotics (`unitreerobotics`) |
| - Source-tree contributors shown by Hugging Face: `Henry-Ellis`, `lv-1` |
| - License: Apache-2.0 |
| - Robot: Unitree G1, 7-DOF dual-arm, with three-finger Dex3 hands |
| - Recording frequency: 30 Hz |
| - Cameras: two head-mounted streams (`cam_left_high`, `cam_right_high`) and two wrist-mounted streams (`cam_left_wrist`, `cam_right_wrist`) |
| - Resolution: 640x480 RGB; source video codec is AV1 |
| - Split: `train` (`0:301` episodes) |
| - Episodes / rows / tasks: 301 / 281,196 / 1 |
| - Source data shards: 1 chunk / 1 Parquet file; source card reports 1,204 video files |
| - Source frame file: `data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet` |
| |
| The task description in the original card is to stack three 5 cm cubic blocks on |
| black tape on the desktop from bottom to top in red, yellow, and blue order. |
| |
| ## Converted files |
| |
| - TsFile: `data/unitreerobotics_g1_dex3_blockstacking.tsfile` |
| - Table: `unitreerobotics_g1_dex3_blockstacking` |
| - Rows: 281,196 |
| - Episodes: 301 |
| - Episode files: 1 merged table-model TsFile |
| - Time precision: milliseconds |
| - Source metadata: `meta/tasks.parquet`, `meta/episodes/...`, and `meta/stats.json` are retained; `meta/info.json` documents the conversion. |
|
|
| ## Schema |
|
|
| | Role | Columns | |
| | --- | --- | |
| | TIME | `Time` (`INT64` timestamp, milliseconds) | |
| | TAG / device metadata | `episode_index`, `task_index` (original source names) | |
| | FIELD | `frame_index`, `sample_index` (renamed from source `index`) | |
| | FIELD FLOAT | `observation_state_0` ... `observation_state_27` | |
| | FIELD FLOAT | `action_0` ... `action_27` | |
|
|
| `Time = round(timestamp * 1000)`. The source timestamp is in seconds and |
| restarts at zero for each episode, so `Time` is monotonic within each |
| (`episode_index`, `task_index`) device. The source `timestamp` column is dropped |
| after synthesis because it is redundant with `Time / 1000`. |
|
|
| Vector columns are flattened row-major while preserving source prefixes: |
|
|
| - `observation.state[28]` -> `observation_state_0` ... `observation_state_27` |
| - `action[28]` -> `action_0` ... `action_27` |
|
|
| The source `index` is renamed to `sample_index`; `frame_index`, |
| `episode_index`, and `task_index` are preserved. No numeric state/action rows |
| are dropped. Image/video feature columns are not written into TsFile because |
| the local source Parquet contains numeric references only. |
|
|
| ## Encoding and compression |
|
|
| The compact TsFile profile is used to avoid producing a file larger than the |
| source Parquet: |
|
|
| - FLOAT/DOUBLE: `GORILLA` + `LZ4` |
| - INT32/INT64: `TS_2DIFF` + `LZ4` |
| - Time: `TS_2DIFF` + `LZ4` |
| - BOOLEAN: `RLE` + `LZ4` (no BOOLEAN fields are present in this dataset) |
| - TAG columns: TsFile table/device TAG mechanism |
|
|
| The staged Parquet and local validation report are kept outside the upload set |
| under `.conversion_work/`. |
|
|
| ## Videos and attribution |
|
|
| Videos are not included in this TsFile repository. They remain in the original |
| Hugging Face dataset at: |
|
|
| - [`videos/observation.images.cam_left_high`](https://huggingface.co/datasets/unitreerobotics/G1_Dex3_BlockStacking_Dataset/tree/main/videos/observation.images.cam_left_high) |
| - [`videos/observation.images.cam_left_wrist`](https://huggingface.co/datasets/unitreerobotics/G1_Dex3_BlockStacking_Dataset/tree/main/videos/observation.images.cam_left_wrist) |
| - [`videos/observation.images.cam_right_high`](https://huggingface.co/datasets/unitreerobotics/G1_Dex3_BlockStacking_Dataset/tree/main/videos/observation.images.cam_right_high) |
| - [`videos/observation.images.cam_right_wrist`](https://huggingface.co/datasets/unitreerobotics/G1_Dex3_BlockStacking_Dataset/tree/main/videos/observation.images.cam_right_wrist) |
|
|
| The source metadata video pattern is |
| `videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4`. |
| `episode_index` and `frame_index` remain unchanged in the TsFile so consumers |
| can align a time-series row with its original video frame. |
|
|
| ## Read example |
|
|
| ```python |
| import sys |
| sys.path.insert(0, r"D:\\code\\.deps") |
| from tsfile import TsFileReader |
| |
| path = r"D:\\code\\py\\unitreerobotics_G1_Dex3_BlockStacking_Dataset\\data\\unitreerobotics_g1_dex3_blockstacking.tsfile" |
| reader = TsFileReader(path) |
| table = reader.get_all_table_schemas()["unitreerobotics_g1_dex3_blockstacking"] |
| columns = [c.get_column_name() for c in table.get_columns() if c.get_column_name() != "Time"] |
| with reader.query_table("unitreerobotics_g1_dex3_blockstacking", columns, batch_size=65536) as result: |
| batch = result.read_arrow_batch() |
| ``` |
|
|
| ## Citation |
|
|
| Please cite the original Unitree Robotics dataset repository and the LeRobot |
| project when using this conversion. No separate paper or BibTeX entry was |
| provided in the source dataset card. |
|
|
