| --- |
| license: cc-by-nc-sa-4.0 |
| task_categories: |
| - robotics |
| tags: |
| - LeRobot |
| configs: |
| - config_name: default |
| data_files: Task_A/base/data/chunk-000/episode_000000.parquet |
| --- |
| # KAI0 |
| <div align="center"> |
| <a href=""> |
| <img src="https://img.shields.io/badge/GitHub-grey?logo=GitHub" alt="GitHub Badge"> |
| </a> |
| <a href="https://huggingface.co/OpenDriveLab-org/Kai0"> |
| <img src="https://img.shields.io/badge/Model-grey?logo=Model" alt="Model Badge"> |
| </a> |
| <a href="https://mmlab.hk/research/kai0"> |
| <img src="https://img.shields.io/badge/Research_Blog-grey?style=flat" alt="Research Blog Badge"> |
| </a> |
| </div> |
| |
| # TODO |
| - [ ] The advantage label will be coming soon. |
|
|
| ## Contents |
| - [About the Dataset](#about-the-dataset) |
| - [Load the Dataset](#get-started) |
| - [Download the Dataset](#download-the-dataset) |
| - [Dataset Structure](#dataset-structure) |
| - [Folder hierarchy](#folder-hierarchy) |
| - [Details](#details) |
| - [License and Citation](#license-and-citation) |
|
|
| ## [About the Dataset](#contents) |
| - **~134 hours** real world scenarios |
| - **Main Tasks** |
| - ***Task_A*** |
| - Single task |
| - Initial state: T-shirts are randomly tossed onto the table, presenting random crumpled configurations |
| - Manipulation task: Operate the robotic arm to unfold the garment, then fold it |
| - ***Task_B*** |
| - Garment classification and arrangement task |
| - Initial state: Randomly pick a garment from the laundry basket |
| - Classification: Determine whether the garment is a T-shirt or a dress shirt |
| - Manipulation task: |
| - If it is a T-shirt, fold the garment |
| - If it is a dress shirt, expose the collar, then push it to one side of the table |
| - ***Task_C*** |
| - Single task |
| - Initial state: Hanger is randomly placed, garment is randomly positioned on the table |
| - Manipulation task: Operate the robotic arm to thread the hanger through the garment, then hang it on the rod |
| - **Count of the dataset** |
|
|
| | Task | Base (episodes count/hours) | DAgger (episodes count/hours) | Total(episodes count/hours) | |
| |------|-----------------------------|-------------------------------|-----------------------------| |
| | Task_A | 3,055/~42 hours | 3,457/ ~13 Hours | 6,512 /~55 hours | |
| | Task_B | 5988/~31 hours | 769/~22 hours | 6757/~53 hours | |
| | Task_C | 6954/~61 hours | 686/~12 hours | 7640/~73 hours | |
| | **Total** | **15,997/~134 hours** | **4,912/~47 hours** | **20,909/~181 hours** | |
| |
| ## [Load the dataset](#contents) |
| - This dataset was created using [LeRobot](https://github.com/huggingface/lerobot) |
| - The dataset's version is LeRobotDataset v2.1 |
| ### 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> |
| ``` |
|
|
| ## [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" |
| ``` |
|
|
| ## [Dataset Structure](#contents) |
|
|
| ### [Folder hierarchy](#contents) |
| Under each task directory, data is partitioned into two subsets: base and dagger. |
| - base |
| contains |
| original demonstration trajectories of robotic arm manipulation for garment arrangement tasks. |
| - dagger |
| contains on-policy recovery trajectories collected via iterative DAgger, designed to populate failure recovery modes absent in static demonstrations. |
| ```text |
| Kai0-data/ |
| ├── Task_A/ |
| │ ├── base/ |
| │ │ ├── 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 |
| │ └── dagger/ |
| ├── Task_B/ |
| │ ├── base/ |
| │ └── dagger/ |
| ├── Task_C/ |
| │ ├── base/ |
| │ └── dagger/ |
| └── 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": ..., # the total episodes in the dataset |
| "total_frames": ..., # The total number of video frames in any single camera perspective |
| "total_tasks": ..., # Total number of tasks |
| "total_videos": ..., # The total number of videos from all camera perspectives in the dataset |
| "total_chunks": ..., # The number of chunks in the dataset |
| "chunks_size": ..., # The max number of episodes in a chunk |
| "fps": ..., # Video frame rate per second |
| "splits": { # how to split the dataset |
| "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": { # the camera perspective |
| "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": { # the camera perspective |
| ... |
| }, |
| "observation.images.hand_right": { # the camera perspective |
| ... |
| }, |
| "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](#Task_A/meta/tasks.jsonl) |
| Contains task language prompts (natural language instructions) that specify the manipulation task to be performed. Each entry maps a task_index to its corresponding task description, which can be used for language-conditioned policy training. |
|
|
| # 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={} |
| } |
