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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
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- Initial set: ~400 web-sourced images used for theoretical model exploration.
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- Main dataset: 7500+ images captured over 6 months using smartphones and amateur camera devices, reflecting real-world scales, perspectives, and conditions.
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- Cleaning: Manual filtering of blurry, low-quality, or irrelevant images.
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- Annotation: Performed via Roboflow platform with bounding boxes for YOLOv8.
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- Augmentation: Basic augmentations applied during preparation; none used during final training due to negative effects on performance.
 
 
 
 
 
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- 📁 Dataset Structure
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  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
 
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  Luis Adrian Cabrera | https://github.com/LuisAdrian5519
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  Jesse Banda Chaidez | https://github.com/Jessebnda
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- Contributors
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- José Alejandro Padilla Pérez | PadillaPepe777
 
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  Erick Blanco Nakashima
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  Juan Pablo Riojas Pesqueira
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  Guillermo Villegas
 
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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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+ ---
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+
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+ ## 📸 Dataset Collection & Annotation
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+
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+ **Initial set**: ~400 web-sourced images used for theoretical model exploration.
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+ **Main dataset**: 7500+ images captured over 6 months using smartphones and amateur camera devices, reflecting real-world scales, perspectives, and conditions.
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+ **Cleaning**: Manual filtering of blurry, low-quality, or irrelevant images.
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+ **Annotation**: Performed via Roboflow platform with bounding boxes for YOLOv8.
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+ **Augmentation**: Basic augmentations applied during preparation; none used during final training due to negative effects on performance.
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+
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+ ## 📁 Dataset Structure
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  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
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  Luis Adrian Cabrera | https://github.com/LuisAdrian5519
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  Jesse Banda Chaidez | https://github.com/Jessebnda
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+ ## Contributors
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+
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+ José Alejandro Padilla Pérez | https://github.com/PadillaPepe777
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  Erick Blanco Nakashima
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  Juan Pablo Riojas Pesqueira
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  Guillermo Villegas