| --- |
| license: cc-by-4.0 |
| pretty_name: TexasPokerRobot |
| size_categories: |
| - 1K<n<10K |
| tags: |
| - robotics |
| - robot-learning |
| - imitation-learning |
| - manipulation |
| - tabular |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train.csv |
| --- |
| |
| # TexasPokerRobot |
|
|
| TexasPokerRobot is a robot manipulation dataset collected in a Texas poker tabletop environment. The raw episodes are stored as compressed NumPy `.npz` files, organized by action folder. This release adds a Hugging Face-compatible manifest at `data/train.csv` so the dataset has a standard loadable split and a working Dataset Viewer while preserving the original raw episode files. |
|
|
| ## Dataset Summary |
|
|
| - 1,470 raw episode files |
| - 14 action folders, with 105 episodes per action |
| - 377.94 GB of raw `.npz` episode data |
| - RGB observations from three cameras, depth observations from three cameras, and robot joint state streams |
| - License: CC BY 4.0 |
|
|
| ## Actions |
|
|
| | Action | Episodes | Raw size | |
| | --- | ---: | ---: | |
| | `pick_up_left` | 105 | 40.19 GB | |
| | `pick_up_right` | 105 | 29.63 GB | |
| | `pull_5` | 105 | 29.69 GB | |
| | `pull_10` | 105 | 29.00 GB | |
| | `pull_50` | 105 | 31.83 GB | |
| | `pull_100` | 105 | 31.17 GB | |
| | `push_5` | 105 | 28.44 GB | |
| | `push_10` | 105 | 33.60 GB | |
| | `push_50` | 105 | 35.04 GB | |
| | `push_100` | 105 | 31.10 GB | |
| | `put_down_left` | 105 | 18.23 GB | |
| | `put_down_right` | 105 | 14.59 GB | |
| | `show_left` | 105 | 13.23 GB | |
| | `show_right` | 105 | 12.19 GB | |
|
|
| ## Manifest Fields |
|
|
| The `train` split is a manifest. Each row points to one raw episode file. |
|
|
| | Column | Description | |
| | --- | --- | |
| | `action` | Action folder name. | |
| | `episode_index` | Episode number within the action folder. | |
| | `file_path` | Path to the raw `.npz` file in this dataset repository. | |
| | `file_name` | Raw episode filename. | |
| | `format` | Raw file format, currently `npz`. | |
| | `size_bytes` | Size of the raw episode file. | |
| | `sha256` | LFS SHA-256 checksum for the raw episode file. | |
| | `download_url` | Direct Hub URL for the raw episode file. | |
| | `modalities` | Modalities present in the raw episode. | |
| | `num_rgb_cameras` | Number of RGB camera streams. | |
| | `num_depth_cameras` | Number of depth camera streams. | |
|
|
| ## Loading |
|
|
| Load the manifest with the `datasets` library: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("Winniechen2002/TexasPokerRobot") |
| row = ds["train"][0] |
| print(row["action"], row["file_path"]) |
| ``` |
|
|
| Download and inspect a raw episode: |
|
|
| ```python |
| import numpy as np |
| from huggingface_hub import hf_hub_download |
| |
| path = hf_hub_download( |
| repo_id="Winniechen2002/TexasPokerRobot", |
| filename=row["file_path"], |
| repo_type="dataset", |
| ) |
| |
| episode = np.load(path, allow_pickle=True) |
| print(episode.files) |
| ``` |
|
|
| Some robot state arrays are stored as NumPy object arrays, so loading a raw episode requires `allow_pickle=True`. Only use this option with dataset files you trust. |
|
|
| ## Intended Uses |
|
|
| This dataset is intended for robot learning research, imitation learning, action-conditioned perception, manipulation policy development, and analysis of tabletop robot trajectories. |
|
|
| ## Limitations |
|
|
| The Dataset Viewer previews the manifest rows, not the full RGB, depth, and joint-state tensors. The raw episode files are large, and no official train/validation/test benchmark split is provided beyond the manifest split. |
|
|
