| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| tags: |
| - LeRobot |
| - tsfile |
| - time-series |
| - modality:timeseries |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/berkeley_cable_routing.tsfile |
| --- |
| |
| # berkeley_cable_routing |
|
|
| This dataset is a TsFile conversion of the Hugging Face dataset |
| [`lerobot/berkeley_cable_routing`](https://huggingface.co/datasets/lerobot/berkeley_cable_routing). |
| The source dataset was created using [LeRobot](https://github.com/huggingface/lerobot). |
|
|
| Modalities: Time-series. The original repository also contains video streams; videos are not |
| included in this converted repository. |
|
|
| ## Source Dataset |
|
|
| - Original dataset: [`lerobot/berkeley_cable_routing`](https://huggingface.co/datasets/lerobot/berkeley_cable_routing) |
| - License: `apache-2.0` |
| - LeRobot codebase version: `v3.0` |
| - Robot type: `unknown` |
| - Task: `route cable` |
| - Split: `train` (`0:1647`) |
| - Source scale from `meta/info.json`: `1,647` episodes, `42,328` frames, `1` task |
| - Sampling rate: `10` fps |
| - Source data layout: `data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet` |
| - Source video layout: `videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4` |
|
|
| ## Converted Files |
|
|
| - TsFile: `data/berkeley_cable_routing.tsfile` |
| - Converted rows: `42,328` |
| - TsFile table: `berkeley_cable_routing` |
| - Time precision: milliseconds |
| - TAG columns: `episode_index`, `task_index` |
|
|
| The conversion follows the LeRobot v3 data path in `meta/info.json` and uses the |
| `file-*.parquet` frame data layout. |
|
|
| ## Schema |
|
|
| `Time` is synthesized as `round(timestamp * 1000)` in milliseconds. The source |
| `timestamp` column is dropped because it is redundant with `Time / 1000` seconds. |
|
|
| TAG columns: |
|
|
| - `episode_index` |
| - `task_index` |
|
|
| FIELD columns: |
|
|
| - `frame_index` |
| - `sample_index` (renamed from source `index`) |
| - `next_reward` (renamed from source `next.reward`) |
| - `next_done` (renamed from source `next.done`, stored as `0/1`) |
| - `observation_state_0` to `observation_state_7` |
| - `action_0` to `action_6` |
|
|
| Vector features are flattened by preserving the source feature name and replacing |
| `.` with `_`. For example, `observation.state` becomes |
| `observation_state_0` to `observation_state_7`, and `action` becomes |
| `action_0` to `action_6`. |
|
|
| ## Video Policy |
|
|
| The following source video features are not converted into TsFile and are not |
| uploaded here: |
|
|
| - `observation.images.top_image` |
| - `observation.images.wrist225_image` |
| - `observation.images.wrist45_image` |
| - `observation.images.image` |
|
|
| Use the original dataset for videos: |
| [`lerobot/berkeley_cable_routing/videos`](https://huggingface.co/datasets/lerobot/berkeley_cable_routing/tree/main/videos). |
|
|
| ## Validation |
|
|
| The converted TsFile was validated with the project pipeline and read back using |
| the TsFile Python SDK: |
|
|
| - staged Parquet rows: `42,328` |
| - TsFile metadata rows: `42,328` |
| - TsFile query rows: `42,328` |
|
|
| ## Usage |
|
|
| ```python |
| from tsfile import TsFileReader |
| |
| path = "data/berkeley_cable_routing.tsfile" |
| with TsFileReader(path) as reader: |
| schemas = reader.get_all_table_schemas() |
| print(schemas.keys()) |
| ``` |
|
|
