File size: 2,766 Bytes
a2b8dee 800e5b0 a2b8dee 800e5b0 a2b8dee 800e5b0 a2b8dee 800e5b0 a2b8dee 800e5b0 a2b8dee |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 |
---
task_categories:
- object-detection
tags:
- roboflow
- roboflow2huggingface
---
<div align="center">
<img width="640" alt="bortle/ap_obj_dataset" src="https://huggingface.co/datasets/bortle/ap_obj_dataset/resolve/main/thumbnail.jpg">
</div>
### Dataset Labels
```
['comet', 'galaxy', 'moon', 'nebula', 'saturn', 'snr', 'star cluster']
```
### Number of Images
```json
{'valid': 6, 'test': 4, 'train': 16}
```
### How to Use
- Install [datasets](https://pypi.org/project/datasets/):
```bash
pip install datasets
```
- Load the dataset:
```python
from datasets import load_dataset
ds = load_dataset("bortle/ap_obj_dataset", name="full")
example = ds['train'][0]
```
### Roboflow Dataset Page
[https://universe.roboflow.com/bortle/astrophotographyobectdetection/dataset/3](https://universe.roboflow.com/bortle/astrophotographyobectdetection/dataset/3?ref=roboflow2huggingface)
### Citation
```
@misc{
astrophotographyobectdetection_dataset,
title = { AstrophotographyObectDetection Dataset },
type = { Open Source Dataset },
author = { Bortle },
howpublished = { \\url{ https://universe.roboflow.com/bortle/astrophotographyobectdetection } },
url = { https://universe.roboflow.com/bortle/astrophotographyobectdetection },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { apr },
note = { visited on 2025-04-08 },
}
```
### License
CC BY 4.0
### Dataset Summary
This dataset was exported via roboflow.com on April 8, 2025 at 8:58 AM GMT
Roboflow is an end-to-end computer vision platform that helps you
* collaborate with your team on computer vision projects
* collect & organize images
* understand and search unstructured image data
* annotate, and create datasets
* export, train, and deploy computer vision models
* use active learning to improve your dataset over time
For state of the art Computer Vision training notebooks you can use with this dataset,
visit https://github.com/roboflow/notebooks
To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
The dataset includes 26 images.
Objects are annotated in COCO format.
The following pre-processing was applied to each image:
* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Resize to 640x640 (Stretch)
No image augmentation techniques were applied.
|