README.md

---
license: cc-by-nc-nd-4.0
task_categories:
- robotics
tags:
- LeRobot
configs:
- config_name: default
  data_files: data/*/*.parquet
language:
- en
---
<span style="color: red; font-weight: bold; font-size: 24px;">⚠️ !!!  等待信息，填充链接</span>
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# Contents
- [About the Dataset](#about-the-dataset)
- [Dataset Structure](#dataset-structure)
    - [Folder hierarchy](#folder-hierarchy)
    - [Details](#details)
- [Download the Dataset](#download-the-dataset)
- [Load the Dataset](#get-started)
- [License and Citation](#license-and-citation)

# [About the Dataset](#contents)
- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot)
- **~200 hours real world scenarios** across **1** main task, **3** sub tasks
- A clothing organization task that involves identifying the type of clothing and determining the next action based on its category
- **sub-tasks**
    - **Folding**
        - Randomly pick a piece of clothing from the basket and place it on the workbench
        - If it is a short T-shirt, fold it
    - **Hanging Preparation**
        - Randomly pick a piece of clothing from the basket and place it on the workbench
        - If it is a dress shirt, locate the collar and drag the clothing to the right side
    - **Hanging**
        - Hang the dress shirt properly

# [Dataset Structure](#contents)

## [Folder hierarchy](#contents)
```text
dataset_root/
  ├── data/
  │  ├── chunk-000/
  │  │   ├──   episode_000000.parquet
  │  │   ├──   episode_000001.parquet
  │  │   └──  ...
  │  └── ...
  ├── videos/
  │   ├── chunk-000/
  │   │   ├── observation.images.hand_left
  │   │   │   ├── episode_000000.mp4
  │   │   │   ├── episode_000001.mp4
  │   │   │   └──  ...
  │   │   ├── observation.images.hand_right
  │   │   │   ├── episode_000000.mp4
  │   │   │   ├── episode_000001.mp4
  │   │   │   └──  ...
  │   │   ├── observation.images.top_head
  │   │   │   ├── episode_000000.mp4
  │   │   │   ├── episode_000001.mp4
  │   │   │   └──  ...
  │   │   └──  ...  
  ├── meta/
  │   ├── info.json
  │   ├── episodes.jsonl
  │   ├── tasks.jsonl
  │   └── episodes_stats.jsonl
  └ README.md
```

<a id='Details'></a>
## [Details](#contents)
### info.json
the basic struct of the [info.json](#meta/info.json)
```json
{
    "codebase_version": "v2.1",
    "robot_type": "agilex",
    "total_episodes": ...,
    "total_frames": ...,
    "total_tasks": ...,
    "total_videos": ...,
    "total_chunks": ...,
    "chunks_size": ...,
    "fps": ...,
    "splits": {
        "train": ...
    },
    "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
    "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
    "features": {
        "observation.images.top_head": {
            "dtype": "video",
            "shape": [
                480,
                640,
                3
            ],
            "names": [
                "height",
                "width",
                "channel"
            ],
            "info": {
                "video.height": 480,
                "video.width": 640,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
                "video.fps": 30,
                "video.channels": 3,
                "has_audio": false
            }
        },
        "observation.images.hand_left": {
            ...
        },
        "observation.images.hand_right": {
            ...
        },
        "observation.state": {
            "dtype": "float32",
            "shape": [
                14
            ],
            "names": null
        },
        "action": {
            "dtype": "float32",
            "shape": [
                14
            ],
            "names": null
        },
        "timestamp": {
            "dtype": "float32",
            "shape": [
                1
            ],
            "names": null
        },
        "frame_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "episode_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "task_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        }
    }
```

### [Parquet file format](#contents)
| Field Name | shape | Meaning |
|------------|-------------|-------------|
| observation.state | [N, 14] |left `[:, :6]`, right `[:, 7:13]`, joint angle<br> left`[:, 6]`, right `[:, 13]` , gripper open range|
| action | [N, 14]  |left `[:, :6]`, right `[:, 7:13]`, joint angle<br>left`[:, 6]`, right `[:, 13]` , gripper open range |
| timestamp | [N, 1] | Time elapsed since the start of the episode (in seconds) |
| frame_index | [N, 1] | Index of this frame within the current episode (0-indexed) |
| episode_index | [N, 1] | Index of the episode this frame belongs to |
| index | [N, 1] | Global unique index across all frames in the dataset |
| task_index | [N, 1] | Index identifying the task type being performed |

## [tasks.jsonl](#meta/tasks.jsonl)
positive/negitive: Labels indicating the advantage of each frame's action, where "positive" means the action benefits future outcomes and "negative" means otherwise.
# [Download the Dataset](#contents)
### Python Script

```python
from huggingface_hub import hf_hub_download, snapshot_download
from datasets import load_dataset

# Download a single file
hf_hub_download(
    repo_id="OpenDriveLab-org/kai0", 
    filename="episodes.jsonl",
    subfolder="meta",
    repo_type="dataset",
    local_dir="where/you/want/to/save"
)

# Download a specific folder
snapshot_download(
    repo_id="OpenDriveLab-org/kai0", 
    local_dir="/where/you/want/to/save",
    repo_type="dataset",
    allow_patterns=["data/*"]
)

# Load the entire dataset
dataset = load_dataset("OpenDriveLab-org/kai0") 
```

### Terminal (CLI)

```bash
# Download a single file
hf download OpenDriveLab-org/kai0 \
    --include "meta/info.json" \
    --repo-type dataset \
    --local-dir "/where/you/want/to/save"

# Download a specific folder
hf download OpenDriveLab-org/kai0 \
    --repo-type dataset \
    --include "meta/*" \
    --local-dir "/where/you/want/to/save"

# Download the entire dataset
hf download OpenDriveLab-org/kai0 \
    --repo-type dataset \
    --local-dir "/where/you/want/to/save"
```

# [Load the dataset](#contents)

## For LeRobot version < 0.4.0

Choose the appropriate import based on your version:

| Version | Import Path |
|---------|-------------|
| `<= 0.1.0` | `from lerobot.common.datasets.lerobot_dataset import LeRobotDataset` |
| `> 0.1.0` and `< 0.4.0` | `from lerobot.datasets.lerobot_dataset import LeRobotDataset` |

```python
# For version <= 0.1.0
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset

# For version > 0.1.0 and < 0.4.0
from lerobot.datasets.lerobot_dataset import LeRobotDataset

# Load the dataset
dataset = LeRobotDataset(repo_id='where/the/dataset/you/stored')
```

## For LeRobot version >= 0.4.0

You need to migrate the dataset from v2.1 to v3.0 first. See the official documentation: [Migrate the dataset from v2.1 to v3.0](https://huggingface.co/docs/lerobot/lerobot-dataset-v3)

```bash
python -m lerobot.datasets.v30.convert_dataset_v21_to_v30 --repo-id=<HF_USER/DATASET_ID>
```
<span style="color: red; font-weight: bold; font-size: 24px;">⚠️ !!!  等待信息填充</span>
# License and Citation
All the data and code within this repo are under [](). Please consider citing our project if it helps your research.

```BibTeX
@misc{,
  title={},
  author={},
  howpublished={\url{}},
  year={}
}