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--- |
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license: apache-2.0 |
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pretty_name: StarCloud |
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size_categories: |
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- 1B<n<10B |
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viewer: false |
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--- |
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# StarCloud |
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**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. |
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**1 Million Star 3D Demo:** https://starcloud.ruben-roy.com |
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--- |
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## Dataset Overview |
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| File | Points | Approx. Size | |
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|-------------------|----------------|---------------| |
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| `galaxy_10K.ply` | 10,000 | ~0.4 MB | |
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| `galaxy_100K.ply` | 100,000 | ~4 MB | |
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| `galaxy_1M.ply` | 1,000,000 | ~38 MB | |
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| `galaxy_10M.ply` | 10,000,000 | ~382 MB | |
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| `galaxy_100M.ply` | 100,000,000 | ~3.82 GB | |
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| `galaxy_1B.ply` | 1,000,000,000 | ~38.2 GB | |
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Each file is stored in **PLY format** with 6 fields per point: |
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- `x, y, z` (spatial coordinates, `float32`) |
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- `r, g, b` (color values, `uint8`) |
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The dataset was generated using an **NVIDIA A100 40GB GPU** over the total span of 2 hours (for all files). |
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**DISCLAIMER:** The dataset was created entirely synthetically and no real astronomical data was used. |
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## Usage |
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Pandas: |
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```python |
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import pandas as pd |
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df = pd.read_csv("galaxy_1M.ply", comment="e", sep=" ", header=None) |
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df.columns = ["x", "y", "z", "r", "g", "b"] |
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print(df.head()) |
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``` |
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Open3D for visualization: |
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```python |
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import open3d as o3d |
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pcd = o3d.io.read_point_cloud("galaxy_1M.ply") |
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o3d.visualization.draw_geometries([pcd]) |
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``` |
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--- |
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## Citation / Attribution |
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If you use this dataset in research or software, credit: |
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**Ruben Roy** – *StarCloud: A Large GPU-Generated Galaxy Point Cloud Dataset* |
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--- |
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## License |
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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. |
