---
license: apache-2.0
pretty_name: StarCloud
size_categories:
- 1B<n<10B
viewer: false
---

# StarCloud

**StarCloud** is a GPU-generated synthetic starfield dataset representing a reconstruction of the Milky Way galaxy. It contains point cloud data of up to **1 billion stars**, each with spatial coordinates and RGB color values depending on the location of the star within the galaxy.

![1 Million Star Render](render.png)

**1 Million Star 3D Demo:** https://starcloud.ruben-roy.com

---

## Dataset Overview

| File              | Points         | Approx. Size  |
|-------------------|----------------|---------------|
| `galaxy_10K.ply`  | 10,000         | ~0.4 MB       |
| `galaxy_100K.ply` | 100,000        | ~4 MB         |
| `galaxy_1M.ply`   | 1,000,000      | ~38 MB        |
| `galaxy_10M.ply`  | 10,000,000     | ~382 MB       |
| `galaxy_100M.ply` | 100,000,000    | ~3.82 GB      |
| `galaxy_1B.ply`   | 1,000,000,000  | ~38.2 GB      |

Each file is stored in **PLY format** with 6 fields per point:
- `x, y, z` (spatial coordinates, `float32`)
- `r, g, b` (color values, `uint8`)

The dataset was generated using an **NVIDIA A100 40GB GPU** over the total span of 2 hours (for all files).

**DISCLAIMER:** The dataset was created entirely synthetically and no real astronomical data was used.

## Usage

Pandas:

```python
import pandas as pd

df = pd.read_csv("galaxy_1M.ply", comment="e", sep=" ", header=None)
df.columns = ["x", "y", "z", "r", "g", "b"]
print(df.head())
```

Open3D for visualization:

```python
import open3d as o3d

pcd = o3d.io.read_point_cloud("galaxy_1M.ply")
o3d.visualization.draw_geometries([pcd])
```

---

## Citation / Attribution

If you use this dataset in research or software, credit:

**Ruben Roy** – *StarCloud: A Large GPU-Generated Galaxy Point Cloud Dataset*

---

## License

The dataset is released under the **[Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0)**. Please refer to the license for usage rights and restrictions.