Planet Detection Computer Vision Project
This image dataset contains images of planets from our solar system. The dataset includes images of all eight planets in our solar system. The images are labeled with metadata that identifies the planet or object in the image.
The goal of this dataset is to train a computer vision model for object detection, specifically for detecting planets from our solar system.
By using this dataset for training, the model will be able to identify planets in images taken from telescopes or other space-based instruments. This has important applications in astronomy and space exploration, as it can help scientists identify and study planets in our solar system and beyond.
Trained Model API
This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.
YOLOv8
This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
planet-detection_dataset,
title = { Planet Detection Dataset },
type = { Open Source Dataset },
author = { College },
howpublished = { \url{ https://universe.roboflow.com/college-qcgpx/planet-detection } },
url = { https://universe.roboflow.com/college-qcgpx/planet-detection },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { jan },
note = { visited on 2024-05-14 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the Planet Detection project in your project.
