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 # Moon Detection Dataset for YOLOv8
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 This dataset was developed as part of the CubeRT-02 project, a CubeSat mission aimed at testing AI-powered vision systems in aerospace contexts. It consists of 7500+ annotated images for object detection of the Moon, optimized for use with the YOLOv8 architecture.
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 ## 📸 Dataset Collection & Annotation
 **Initial set**: ~400 web-sourced images used for theoretical model exploration.
 **Main dataset**: 7500+ images captured over 6 months using smartphones and amateur camera devices, reflecting real-world scales, perspectives, and conditions.
 **Cleaning**: Manual filtering of blurry, low-quality, or irrelevant images.
 **Annotation**: Performed via Roboflow platform with bounding boxes for YOLOv8.
 **Augmentation**: Basic augmentations applied during preparation; none used during final training due to negative effects on performance.
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 ## 📁 Dataset Structure
 This dataset follows the YOLOv8 format. A Python script and a YAML configuration file are included to help you easily train or test the dataset using Ultralytics' YOLOv8 implementation.
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 ## Authors
 Luis Adrian Cabrera | https://github.com/LuisAdrian5519
 Jesse Banda Chaidez | https://github.com/Jessebnda