| ---
|
| license: apache-2.0
|
| authors:
|
| - "Ishan Shah (Ishan-Axibo)"
|
| task_categories:
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| - robotics
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| tags:
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| - tsfile
|
| - timeseries
|
| - tabular
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| - robotics
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| - lerobot
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| - manipulation
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| - bimanual
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| - cube-stacking
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| modality:
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| - timeseries
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| - tabular
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| pretty_name: "Piper Stacking EE TsFile"
|
| configs:
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| - config_name: default
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| data_files:
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| - split: train
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| path: data/piper_stacking_ee_train.tsfile
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| size_categories:
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| - 10K<n<100K
|
| ---
|
|
|
| # Piper Stacking EE TsFile
|
|
|
| This dataset is an Apache TsFile conversion of
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| [`axiboai/piper_stacking_ee`](https://huggingface.co/datasets/axiboai/piper_stacking_ee), a LeRobot v2.1 bimanual
|
| robot-manipulation dataset for stacking a red cube on a blue cube.
|
|
|
| Modalities: Time-series. The converted repository contains numeric robot
|
| observations, actions, frame timing, episode/task tags, and mirrored source
|
| metadata. All three camera video streams remain in the original Hugging
|
| Face dataset.
|
|
|
| ## Source Dataset and Author
|
|
|
| - Source dataset: [`axiboai/piper_stacking_ee`](https://huggingface.co/datasets/axiboai/piper_stacking_ee)
|
| - Pinned source revision: [`7f79b7c26d815766cf0f6d041edde20e7033e573`](https://huggingface.co/datasets/axiboai/piper_stacking_ee/tree/7f79b7c26d815766cf0f6d041edde20e7033e573)
|
| - Publishing organization: [AXIBO (`axiboai`)](https://huggingface.co/axiboai)
|
| - Source uploader/contributor: [Ishan Shah (`Ishan-Axibo`)](https://huggingface.co/Ishan-Axibo)
|
| - Authorship evidence: the source repository's file history attributes the uploaded dataset tree to `Ishan-Axibo`; the source card provides no separate formal author list.
|
| - License: Apache-2.0
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| - Robot type: `piperx_bimanual_eef_6d`
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| - LeRobot codebase version: `v2.1`
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| - Task: Stack the red cube on the blue cube.
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| - Split: `train`
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| - Scale: 155 episodes, 60,656 frames, 1 task, 30 fps
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| - Episode lengths: 57 to 707 frames (mean 391.33)
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| - Source frame files: 155 Parquet files under `data/chunk-000/`
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| - Source frame layout: `data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`
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| - Source video layout: `videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4`
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| - Paper/citation: not supplied by the source dataset card
|
|
|
| ## Converted Files
|
|
|
| - TsFile: `data/piper_stacking_ee_train.tsfile`
|
| - Table: `piper_stacking_ee_train`
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| - Rows: 60,656
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| - Episodes/devices: 155
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| - Tasks: 1
|
| - Time precision: milliseconds
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| - Metadata: `meta/` is mirrored from the source, with `meta/info.json` rewritten to describe the TsFile artifact and video policy.
|
|
|
| ## TsFile Schema
|
|
|
| `Time` is synthesized as `round(timestamp * 1000)` milliseconds and restarts
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| from 0 for each episode.
|
|
|
| TAG columns:
|
|
|
| - `episode_index`
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| - `task_index`
|
|
|
| Scalar FIELD columns:
|
|
|
| - `frame_index`
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| - `sample_index`, renamed from source column `index`
|
|
|
| Flattened FLOAT FIELD groups:
|
|
|
| - `observation.state[20]` -> `observation_state_0` ... `observation_state_19`
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| - `action[20]` -> `action_0` ... `action_19`
|
|
|
| The source uses the same 20-dimensional order for state and action:
|
|
|
| | Index | Source dimension | State FIELD | Action FIELD |
|
| |---:|---|---|---|
|
| | 0 | `left_x` | `observation_state_0` | `action_0` |
|
| | 1 | `left_y` | `observation_state_1` | `action_1` |
|
| | 2 | `left_z` | `observation_state_2` | `action_2` |
|
| | 3 | `left_rot6d_0` | `observation_state_3` | `action_3` |
|
| | 4 | `left_rot6d_1` | `observation_state_4` | `action_4` |
|
| | 5 | `left_rot6d_2` | `observation_state_5` | `action_5` |
|
| | 6 | `left_rot6d_3` | `observation_state_6` | `action_6` |
|
| | 7 | `left_rot6d_4` | `observation_state_7` | `action_7` |
|
| | 8 | `left_rot6d_5` | `observation_state_8` | `action_8` |
|
| | 9 | `left_gripper` | `observation_state_9` | `action_9` |
|
| | 10 | `right_x` | `observation_state_10` | `action_10` |
|
| | 11 | `right_y` | `observation_state_11` | `action_11` |
|
| | 12 | `right_z` | `observation_state_12` | `action_12` |
|
| | 13 | `right_rot6d_0` | `observation_state_13` | `action_13` |
|
| | 14 | `right_rot6d_1` | `observation_state_14` | `action_14` |
|
| | 15 | `right_rot6d_2` | `observation_state_15` | `action_15` |
|
| | 16 | `right_rot6d_3` | `observation_state_16` | `action_16` |
|
| | 17 | `right_rot6d_4` | `observation_state_17` | `action_17` |
|
| | 18 | `right_rot6d_5` | `observation_state_18` | `action_18` |
|
| | 19 | `right_gripper` | `observation_state_19` | `action_19` |
|
|
|
| ## Conversion Notes
|
|
|
| - The shared config-driven `lerobot` converter is used; the dataset-specific
|
| script is a thin local orchestration and validation entry point and is not part of the dataset upload; the conversion script is retained locally.
|
| - The train split is merged into one table-model TsFile. Filter by
|
| `episode_index` and `task_index` to select an episode or task.
|
| - Vector columns are flattened to scalar TsFile fields. Full source prefixes
|
| are preserved, with `.` replaced by `_`.
|
| - The source `timestamp` column is dropped after Time synthesis because it is
|
| redundant with `Time / 1000` seconds.
|
| - Source `index` is renamed to `sample_index`; `frame_index` is retained.
|
| - All 155 source Parquet schemas are identical, both vector widths are exactly
|
| 20, and no numeric row, episode, task, state dimension, or action dimension is dropped.
|
| - FLOAT fields use GORILLA + LZ4; INT64 fields and Time use TS_2DIFF + LZ4.
|
| The config also requires RLE + LZ4 for BOOLEAN fields (none occur in this source).
|
|
|
| ## Videos
|
|
|
| Videos are not duplicated in this converted repository. They remain under the
|
| original source revision's `videos/chunk-000/` tree in three frame-aligned streams:
|
|
|
| - [`observation.images.cam_front`](https://huggingface.co/datasets/axiboai/piper_stacking_ee/tree/7f79b7c26d815766cf0f6d041edde20e7033e573/videos/chunk-000/observation.images.cam_front): 155 MP4 files, 652,759,687 bytes
|
| - [`observation.images.cam_left_wrist`](https://huggingface.co/datasets/axiboai/piper_stacking_ee/tree/7f79b7c26d815766cf0f6d041edde20e7033e573/videos/chunk-000/observation.images.cam_left_wrist): 155 MP4 files, 585,180,346 bytes
|
| - [`observation.images.cam_right_wrist`](https://huggingface.co/datasets/axiboai/piper_stacking_ee/tree/7f79b7c26d815766cf0f6d041edde20e7033e573/videos/chunk-000/observation.images.cam_right_wrist): 155 MP4 files, 459,890,635 bytes
|
|
|
| Together, the source contains 465 MP4 files totaling 1,697,830,668 bytes
|
| (about 1.58 GiB). Each stream contains one
|
| `episode_XXXXXX.mp4` file per episode. Numeric rows remain aligned through
|
| `episode_index`, `frame_index`, and the source episode metadata. The source
|
| metadata describes 640x480 AV1 video at 30 fps without audio.
|
|
|
| ## Validation
|
|
|
| The generated TsFile was opened and fully queried with the Apache TsFile Java
|
| reader bundled with the conversion tools. Source, staged-Parquet, and TsFile
|
| readback row counts all equal 60,656. The file contains one table, 155
|
| episode/task devices, 2 TAG columns, and 42 FIELD columns.
|
|
|
| The detailed `VALIDATION.md` and `validation_report.json` checks are retained locally and |
| are intentionally not included in the dataset upload.
|
|
|
| ## Usage
|
|
|
| ```python
|
| from tsfile import TsFileReader
|
|
|
| reader = TsFileReader("data/piper_stacking_ee_train.tsfile")
|
| table_name = "piper_stacking_ee_train"
|
| columns = [
|
| "episode_index",
|
| "task_index",
|
| "frame_index",
|
| "sample_index",
|
| "action_0",
|
| "observation_state_0",
|
| ]
|
|
|
| with reader.query_table(table_name, columns, batch_size=65536) as result:
|
| batch = result.read_arrow_batch()
|
| print(batch.to_pandas().head())
|
| ```
|
|
|
