README.md

---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
task_categories:
- image-classification
- unconditional-image-generation
---

## Nebula Image Dataset

### Overview
This dataset contains a collection of images depicting various types of nebulas. Nebulas are large, diffuse astronomical objects composed of ionized gases, dust, and plasma. They are often found near star-forming regions and are an important part of the life cycle of stars.

### Dataset Description
The dataset includes about one hundred high-resolution images of different nebulas, such as emission nebulas, reflection nebulas, and planetary nebulas. The images were collected from public astronomical sources and have been carefully curated to ensure high quality and diversity.

### Data Format
The dataset is stored in the Parquet file format, which is a columnar data format that provides efficient storage and query performance. The Parquet file contains a single column, `train`, which holds the file paths to the individual nebula images.

## Usage
You can use this dataset for a variety of machine learning and computer vision tasks, such as:

- Nebula classification
- Nebula segmentation
- Nebula generation or synthesis
- Astronomical image processing and analysis

To get started, cite the [datasets section](https://huggingface.co/datasets/nroggendorff/nebulae#datasets).

### License
This dataset is licensed under the [MIT License](LICENSE). You are free to use, modify, and distribute the data as long as you provide attribution.

### Datasets
```py
from datasets import load_dataset

config.dataset_name = "nroggendorff/nebulae"
dataset = load_dataset(config.dataset_name, split="train")
```

### Acknowledgements
The images in this dataset were collected from various public astronomical sources. We would like to thank the astronomers and organizations who have contributed to the advancement of our understanding of nebulas and other celestial phenomena.