| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| tags: |
| - LeRobot |
| - so100 |
| - tutorial |
| - robotics |
| - tsfile |
| - timeseries |
| - format:tsfile |
| pretty_name: SO-100 Sorting (TsFile) |
| size_categories: |
| - 10K<n<100K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/so100_sorting.tsfile |
| modality: |
| - tabular |
| - timeseries |
| --- |
| |
| # SO-100 Sorting (TsFile) |
|
|
| This dataset is an Apache TsFile conversion of the Hugging Face dataset |
| [`dragon-95/so100_sorting`](https://huggingface.co/datasets/dragon-95/so100_sorting). |
| The source dataset was created using [LeRobot](https://github.com/huggingface/lerobot). |
|
|
| Modalities: Time-series. The original repository also contains synchronized video |
| streams; videos are not included in this converted repository. |
|
|
| ## Source Dataset |
|
|
| - Original dataset: [`dragon-95/so100_sorting`](https://huggingface.co/datasets/dragon-95/so100_sorting) |
| - License: `apache-2.0` |
| - LeRobot codebase version: `v2.0` |
| - Robot type: `so100` |
| - Task: `Put the object in box A into box B` |
| - Split: `train` (`0:61`) |
| - Source scale from `meta/info.json`: `61` episodes, `95,346` frames, `1` task |
| - Source video count: `122` |
| - Sampling rate: `50` fps |
| - Source data 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` |
|
|
| ## Converted Files |
|
|
| - TsFile: `data/so100_sorting.tsfile` |
| - Converted rows: `95,346` |
| - TsFile table: `so100_sorting` |
| - Time precision: milliseconds |
| - TAG columns: `episode_index`, `task_index` |
|
|
| ## Schema |
|
|
| `Time` is synthesized as `round(timestamp * 1000)` in milliseconds. The source |
| `timestamp` column is dropped because it is redundant with `Time / 1000` seconds. |
| At 50 fps, consecutive frames are spaced by about 20 ms. |
|
|
| TAG columns: |
|
|
| - `episode_index` |
| - `task_index` |
|
|
| FIELD columns: |
|
|
| - `frame_index` |
| - `sample_index` (renamed from source `index`) |
| - `action_0` to `action_5` |
| - `observation_state_0` to `observation_state_5` |
|
|
| Vector features are flattened by preserving the source feature name and replacing |
| `.` with `_`. For example, `observation.state` becomes |
| `observation_state_0` to `observation_state_5`. The 6-element `action` and |
| `observation.state` vectors use the source joint order: |
| `main_shoulder_pan`, `main_shoulder_lift`, `main_elbow_flex`, `main_wrist_flex`, |
| `main_wrist_roll`, and `main_gripper`. |
|
|
| ## Video Policy |
|
|
| The following source video features are not converted into TsFile and are not |
| uploaded here: |
|
|
| - `observation.images.laptop` |
| - `observation.images.phone` |
|
|
| Use the original dataset for videos: |
| [`dragon-95/so100_sorting/videos`](https://huggingface.co/datasets/dragon-95/so100_sorting/tree/main/videos). |
|
|
| ## Metadata |
|
|
| The source `meta/` files are mirrored in this repository. `meta/info.json` is |
| updated so `data_path` points to `data/so100_sorting.tsfile` and includes a |
| `tsfile_conversion` object documenting the Time mapping, TAG columns, flattened |
| features, dropped fields, and video policy. |
|
|
| ## Validation |
|
|
| The converted TsFile was validated with the project pipeline and read back using |
| the TsFile Python SDK: |
|
|
| - staged Parquet rows: `95,346` |
| - TsFile metadata rows: `95,346` |
| - TsFile query rows: `95,346` |
| - TsFile size: `1,682,521` bytes |
|
|
| ## Usage |
|
|
| ```python |
| from tsfile import TsFileReader |
| |
| path = "data/so100_sorting.tsfile" |
| with TsFileReader(path) as reader: |
| schemas = reader.get_all_table_schemas() |
| print(schemas.keys()) |
| ``` |
|
|
