| --- |
| pretty_name: Player-1-Data |
| language: |
| - en |
| task_categories: |
| - image-text-to-text |
| tags: |
| - gaming |
| - imitation-learning |
| - keyboard-mouse-control |
| size_categories: |
| - 1K<n<10K |
| license: other |
| license_name: source-dependent |
| license_link: https://huggingface.co/datasets/yyyang/Player-1-Data/blob/main/SOURCES.md |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/*.json |
| dataset_info: |
| features: |
| - name: id |
| dtype: string |
| - name: game |
| dtype: string |
| - name: mode |
| dtype: string |
| - name: source |
| struct: |
| - name: recording_id |
| dtype: string |
| - name: action_clock |
| dtype: string |
| - name: action_interval_ns |
| list: int64 |
| - name: observation_span_ns |
| list: int64 |
| - name: raw_operation_clock |
| dtype: string |
| - name: issues |
| list: string |
| - name: initial_messages |
| list: |
| - name: role |
| dtype: string |
| - name: content |
| dtype: string |
| - name: observation_prompt |
| dtype: string |
| - name: turns |
| list: |
| - name: image |
| dtype: string |
| - name: reasoning |
| dtype: string |
| - name: action |
| dtype: string |
| - name: source |
| struct: |
| - name: action_interval_ns |
| list: int64 |
| - name: observation_time_ns |
| dtype: int64 |
| - name: frame_index |
| dtype: int64 |
| - name: raw_operation_interval_ns |
| list: int64 |
| --- |
| |
| # Player-1-Data |
|
|
| Player-1-Data is a collection of gameplay demonstrations for training game-control agents. It contains **6,044 trajectories and 295,207 turns**, including gameplay and in-game GUI interactions. Each turn pairs a screenshot with reasoning and a keyboard/mouse action. |
|
|
| The dataset is part of [Player-1: Learning to Play from Synthetic Experience](https://player-1-project.github.io/); see the [paper](https://player-1-project.github.io/assets/player-1.pdf) for the overall method. |
|
|
| ## Contents |
|
|
| | File | Description | |
| | --- | --- | |
| | `data/<trajectory_id>.json` | One trajectory per file | |
| | `images/<trajectory_id>/` | Screenshots referenced by the trajectory | |
| | `recordings.jsonl` | Source recording and session references | |
| | `SOURCES.md` | Source links and usage terms | |
| | `to_parquet.py` | Converter to the SFT training format | |
|
|
| Each trajectory has a `id`, `game`, `mode`, source information, initial messages and ordered `turns`. A turn contains `image`, `reasoning`, `action` and source timing information. Image paths are relative to `images/`. Turns are stored individually; a reader can assemble history as needed. |
|
|
| ## Sources |
|
|
| The trajectories come from five recording sources: |
|
|
| | Source | Trajectories | |
| | --- | ---: | |
| | GameHorizon Suite | 1,761 | |
| | D2E | 1,005 | |
| | Gaming500 | 985 | |
| | Pixel2Play | 1,140 | |
| | VPT | 1,153 | |
|
|
| `recordings.jsonl` connects trajectories to their original sessions and filenames. Original recordings are not included. The action and video timestamps may use different clocks; use the declared clock and frame index when relating them. See [SOURCES.md](SOURCES.md) for source links and license terms; source and third-party game-content terms apply. |
|
|
| ## Read a trajectory |
|
|
| ```python |
| import json |
| from pathlib import Path |
| |
| root = Path("/path/to/Player-1-Data") |
| trajectory = json.loads(next((root / "data").glob("*.json")).read_text(encoding="utf-8")) |
| turn = trajectory["turns"][0] |
| image_path = root / "images" / turn["image"] |
| print(trajectory["game"], image_path, turn["reasoning"], turn["action"]) |
| ``` |
|
|
| ## Training format |
|
|
| Convert the file tree into training Parquet and images using: |
|
|
| ```bash |
| python /path/to/Player-1-Data/to_parquet.py --output /path/to/output |
| ``` |
|
|
| The output contains one Parquet row group per trajectory. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{ouyang2026player1learningplaysynthetic, |
| title={Player-1: Learning to Play from Synthetic Experience}, |
| author={Mingyu Ouyang and Yiran Wang and Siyuan Hu and Xingyilang Yin and Huiqiang Sun and Guangzhi Wang and Junfu Pu and Cheng Cheng and Honghao Chen and Ying Shan and Mike Zheng Shou and Hwee Tou Ng}, |
| year={2026}, |
| eprint={2610.20584}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2610.20584}, |
| } |
| ``` |
|
|
