README.md

---
license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- robotics
- bimanual
- manipulation
- tsfile
- timeseries
- format:tsfile
pretty_name: key-unlock-dagger-v2 (TsFile)
size_categories:
- 10K<n<100K
configs:
- config_name: default
  data_files:
  - split: train
    path: data/key_unlock_dagger_v2.tsfile
modality:
- tabular
- timeseries
---

# key-unlock-dagger-v2 (TsFile)

This dataset is an Apache TsFile conversion of the Hugging Face dataset
[`YOLO2431/key-unlock-dagger-v2`](https://huggingface.co/datasets/YOLO2431/key-unlock-dagger-v2).
The source dataset was created using [LeRobot](https://github.com/huggingface/lerobot).

Modalities: Time-series. The original repository also contains synchronized RGB
and depth video streams; videos are not included in this converted repository.

## Source Dataset

- Original dataset: [`YOLO2431/key-unlock-dagger-v2`](https://huggingface.co/datasets/YOLO2431/key-unlock-dagger-v2)
- License: `apache-2.0`
- LeRobot codebase version: `v2.1`
- Robot type: `yam_bimanual`
- Split: `train` (`0:161`)
- Source scale from `meta/info.json`: `161` episodes, `34,279` frames, `1` task
- Source video count from `meta/info.json`: `483`
- Sampling rate: `30` fps
- Source data layout: `data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`
- Source RGB video layout: `videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4`
- Source depth video files are also present under `videos/chunk-000/observation.depth_ffv1.*/*.mkv`

Task:

- `Grab the key with the left hand and hand it to the right hand. Pick up the lock, insert the key into the keyhole, and turn to unlock. Open the shackle to show success, then put the unlocked lock with the key still in it into the lock box.`

## Converted Files

- TsFile: `data/key_unlock_dagger_v2.tsfile`
- Converted rows: `34,279`
- Episodes: `161`
- TsFile table: `key_unlock_dagger_v2`
- Time precision: milliseconds
- TAG columns: `episode_index`, `task_index`
- TsFile size: `5,871,955` bytes

## 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 30 fps, consecutive frames are spaced by about 33 ms.

TAG columns:

- `episode_index`
- `task_index`

FIELD columns:

- `frame_index`
- `sample_index` (renamed from source `index`)
- `observation_state_0` to `observation_state_31`
- `action_0` to `action_31`

Vector features are flattened by preserving the source feature name and replacing
`.` with `_`. For example, `observation.state` becomes `observation_state_0` to
`observation_state_31`. The 32-element `observation.state` and `action` vectors
use the source order:
`left_pos_x`, `left_pos_y`, `left_pos_z`, `left_rot6d_0` to `left_rot6d_5`,
`right_pos_x`, `right_pos_y`, `right_pos_z`, `right_rot6d_0` to
`right_rot6d_5`, `left_gripper`, `right_gripper`, `left_joint_0` to
`left_joint_5`, and `right_joint_0` to `right_joint_5`.

## Video Policy

The following source visual features are not converted into TsFile and are not
uploaded here:

- `observation.images.head`
- `observation.images.left_wrist`
- `observation.images.right_wrist`
- `observation.depth_ffv1.head`
- `observation.depth_ffv1.left_wrist`
- `observation.depth_ffv1.right_wrist`

Use the original dataset for RGB and depth videos:
[`YOLO2431/key-unlock-dagger-v2/videos`](https://huggingface.co/datasets/YOLO2431/key-unlock-dagger-v2/tree/main/videos).

## Metadata

The source `meta/` files are mirrored in this repository. `meta/info.json` is
updated so `data_path` points to `data/key_unlock_dagger_v2.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: `34,279`
- TsFile metadata rows: `34,279`
- TsFile query rows: `34,279`
- TsFile size: `5,871,955` bytes

## Usage

```python
from tsfile import TsFileReader

path = "data/key_unlock_dagger_v2.tsfile"
with TsFileReader(path) as reader:
    schemas = reader.get_all_table_schemas()
    print(schemas.keys())
```