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tags:
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- scene
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  Scene-N1 Release Date: July 26, 2025 All the data and code within this repo
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<!-- <div align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/64e6d9d229a548f66aff6e5b/y9cRIMFKBcY1qsxJ58y7Y.jpeg"/>
</div> -->

# SceneData-N1

<!-- 
## 🔑 Key Features

- **Unified Format for Different Benchmarks**
  
  InternData-N1 consolidates three subsets—VLN-CE, VLN-PE, and VLN-N1—into the mainstream LeRobot (v2.1) format, facilitating convenient usage across different systems and diverse benchmarks.

- **Diverse Data Covering Different Embodiments, Tasks, and Scenes**

  InternData-N1 offers diversity through its foundation of 3,000+ scene assets, extensive randomization across different robot embodiments and viewpoints, and rephrased instructions generated by LLMs for common navigation tasks.

- **High Quality Through Effective Generation and Filtering**

  InternData-N1 ensures high quality by employing effective data generation strategies (producing smooth and safe trajectories) and rigorous filtering (excluding samples with very few reference objects). This results in state-of-the-art performance for models trained on it, such as InternVLA-N1.

## 📅 TODO List

- [x] **InternData-N1 subsets**: 2.8k+ VLN-PE, 150k+ VLN-CE, 6k+ VLN-N1 episodes
- [ ] **Release 200k+ VLN-N1** (in 2 weeks)
- [ ] **VLN-CE v1 -> v1.3** (in one month)

## 📋 Table of Contents

- [InternData-N1](#interndata-n1)
  - [🔑 Key Features](#-key-features)
  - [📅 TODO List](#-todo-list)
  - [📋 Table of Contents](#-table-of-contents)
  - [🔥 Get Started](#-get-started)
    - [Download the Dataset](#download-the-dataset)
  - [Dataset Structure](#dataset-structure)
    - [Scene Data Assets](#scene-data-assets)
    - [Core Dataset Structure](#core-dataset-structure)

## 🔥 Get Started

### Download the Dataset

To download the full dataset, you can use the following commands. If you encounter any issues, please refer to the official Hugging Face documentation.

```bash
# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install

# When prompted for a password, use an access token with read permissions.
# Generate one from your settings: https://huggingface.co/settings/tokens
git clone https://huggingface.co/datasets/InternRobotics/InternData-N1

# If you want to clone without large files - just their pointers
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/InternRobotics/InternData-N1

``` -->
## Dataset Structure


```
scene_data/
├── gradio_scene_assets/
├── n1_eval_scenes/ 
│   ├── Materials
│   ├── SkyTexture
│   ├── internscenes_home
│   └── internscenes_commercial
├── mp3d_pe/ 
├── mp3d_n1/
└── mp3d_ce/
 
```

-   `scene_data/mp3d_pe/`: Improved Matterport3D scene assets for VLN-PE benchmark.
-   `scene_data/mp3d_n1/`: Base Matterport3D scans used for generating VLN-N1 trajectory data.
-   `scene_data/mp3d_ce/`: Matterport3D scene assets for VLN-CE benchmark.
-   `scene_data/n1_eval_scenes/`: Scene assets for VLN-N1 benchmark.
-   `scene_data/gradio_scene_assets/`: Selection of MP3D_CE scenes (with ceilings removed) for rapid interactive testing of the [InternVLA-N1](https://huggingface.co/InternRobotics/InternVLA-N1) model. These simplified environments allow users to quickly verify model performance in key scenarios.

> **Note**: The original scene datasets can be obtained from [Matterport3D](https://niessner.github.io/Matterport/).




# License and Citation
All the data and code within this repo are under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). Please consider citing our project if it helps your research.

```BibTeX
@misc{scene_n1,
  title={Scene-N1 Dataset},
  author={Scene-N1 Dataset contributors},
  howpublished={\url{https://huggingface.co/datasets/InternRobotics/Scene-N1}},
  year={2025}
}
```