| | --- |
| | license: mit |
| | task_categories: |
| | - robotics |
| | - video-classification |
| | tags: |
| | - minecraft |
| | - vla |
| | - vision-language-action |
| | - gaming |
| | - behavioral-cloning |
| | size_categories: |
| | - 1M<n<10M |
| | --- |
| | |
| | # Minecraft VLA Stage 1: Action Pretraining Data |
| |
|
| | Vision-Language-Action training data for Minecraft, processed from OpenAI's VPT contractor dataset. |
| |
|
| | ## Dataset Description |
| |
|
| | This dataset contains frame-action pairs from Minecraft gameplay, designed for training VLA models following the [Lumine](https://www.lumine-ai.org/) methodology. |
| |
|
| | ### Source |
| | - **Original**: [OpenAI VPT Contractor Data](https://github.com/openai/Video-Pre-Training) (7.x subset) |
| | - **Videos**: ~17,886 videos (~330 hours of early-game gameplay) |
| | - **Task**: "Play Minecraft" with focus on first 30 minutes of new worlds |
| |
|
| | ### Format |
| |
|
| | Each sample contains: |
| | | Field | Type | Description | |
| | |-------|------|-------------| |
| | | `image` | bytes | 640x360 JPEG frame | |
| | | `video_id` | string | Source video identifier | |
| | | `frame_idx` | int | Frame number at 5Hz | |
| | | `action` | string | Lumine-format action string | |
| |
|
| | ### Action Format |
| |
|
| | ``` |
| | <|action_start|> mouse_x mouse_y scroll ; K1 ; K2 ; K3 ; K4 <|action_end|> |
| | ``` |
| |
|
| | - `mouse_x`, `mouse_y`: Mouse delta (-1000 to 1000) |
| | - `scroll`: Hotbar scroll (always 0 - VPT uses number keys) |
| | - `K1` to `K4`: Key combinations per 50ms chunk |
| |
|
| | **Example:** |
| | ``` |
| | <|action_start|> 45 -12 0 ; W ; W Space ; W LMB ; W LMB <|action_end|> |
| | ``` |
| |
|
| | ### Processing Details |
| |
|
| | - **Frame rate**: 5 FPS (downsampled from VPT's 20 FPS) |
| | - **Action chunks**: 4 per frame (each 50ms = 200ms total) |
| | - **Filtering**: Idle frames removed, loading screens filtered |
| |
|
| | ## Usage |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | |
| | # Streaming (recommended - no download required) |
| | ds = load_dataset("TESS-Computer/minecraft-vla-stage1", split="train", streaming=True) |
| | |
| | for sample in ds: |
| | image = sample["image"] # PIL Image or bytes |
| | action = sample["action"] |
| | # Process... |
| | ``` |
| |
|
| | ## Training Pipeline |
| |
|
| | This is Stage 1 of a 3-stage training pipeline: |
| | 1. **Stage 1** (this dataset): Action pretraining - learn observation→action mapping |
| | 2. **Stage 2**: Instruction following - add task instructions from JARVIS-VLA |
| | 3. **Stage 3**: Reasoning - add chain-of-thought before complex actions |
| |
|
| | ## Citation |
| |
|
| | If you use this dataset, please cite: |
| | - [OpenAI VPT](https://arxiv.org/abs/2206.11795) - Original contractor data |
| | - [JARVIS-VLA](https://craftjarvis.github.io/JarvisVLA/) - Instruction annotations |
| | - [Lumine](https://www.lumine-ai.org/) - Training methodology |
| |
|
| | ## License |
| |
|
| | MIT License. Original VPT data is released under MIT by OpenAI. |
| |
|
