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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.
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