---
license: apache-2.0
task_categories:
- robotics
- video-generation
- world-models
tags:
- cosmos
- nvidia
- robot-learning
- manipulation
- multi-view
size_categories:
- n<1K
---

# Cosmos 2.5 Multi-View Robot Manipulation Dataset

This dataset contains multi-view robot manipulation demonstrations formatted for training with NVIDIA Cosmos 2.5 world models.

## Dataset Description

- **Total Episodes**: 150
- **Files per Episode**: 4 (3 videos + 1 caption file)
- **Total Files**: 600
- **Dataset Size**: ~1.1 GB
- **Video Format**: MP4
- **Caption Format**: JSONL

## Dataset Structure

```
processeddata/
└── input/
    ├── episode_000001/
    │   ├── caption.jsonl
    │   ├── pinhole_base.mp4
    │   ├── pinhole_side.mp4
    │   └── pinhole_wrist.mp4
    ├── episode_000002/
    │   ├── caption.jsonl
    │   ├── pinhole_base.mp4
    │   ├── pinhole_side.mp4
    │   └── pinhole_wrist.mp4
    ...
    └── episode_000150/
        ├── caption.jsonl
        ├── pinhole_base.mp4
        ├── pinhole_side.mp4
        └── pinhole_wrist.mp4
```

## File Descriptions

### Video Files
Each episode contains three synchronized video views:
- **pinhole_base.mp4**: Base/overhead camera view
- **pinhole_side.mp4**: Side camera view
- **pinhole_wrist.mp4**: Wrist-mounted camera view

### Caption Files
Each `caption.jsonl` file contains three lines (one per view) with:
- `caption`: Natural language description of the task
- `view`: Camera view identifier
- `tag`: Additional metadata (nullable)

Example caption.jsonl:
```json
{"caption": "Pick up the bottle and place it into the blue box", "view": "pinhole_base", "tag": null}
{"caption": "Pick up the bottle and place it into the blue box", "view": "pinhole_wrist", "tag": null}
{"caption": "Pick up the bottle and place it into the blue box", "view": "pinhole_side", "tag": null}
```

## Usage

### Loading the Dataset

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("JeffrinSam/cosmos2.5multip")

# Access episode data
episode_path = "processeddata/input/episode_000001"
```

### Using with Cosmos 2.5

This dataset is formatted for training world models with NVIDIA Cosmos 2.5. Each episode provides:
- Multi-view synchronized videos for spatial understanding
- Natural language task descriptions
- Structured format compatible with Cosmos data loaders

## Applications

- Robot manipulation learning
- Multi-view world model training
- Vision-language grounding for robotics
- Physical AI simulation
- Video prediction models

## Citation

If you use this dataset, please cite:

```bibtex
@misc{cosmos2.5multip,
  title={Cosmos 2.5 Multi-View Robot Manipulation Dataset},
  author={JeffrinSam},
  year={2025},
  publisher={HuggingFace},
  howpublished={\url{https://huggingface.co/datasets/JeffrinSam/cosmos2.5multip}}
}
```

## License

This dataset is released under the Apache 2.0 License.

## Related Resources

- [NVIDIA Cosmos](https://www.nvidia.com/en-us/ai/cosmos/)
- [Physical AI Documentation](https://docs.nvidia.com/cosmos/)
- [LeRobot Framework](https://github.com/huggingface/lerobot)