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Rafanoset Segmentation
This dataset provides real multispectral imagery captured in a wheat field in Portici, Italy, during January 2022, specifically for semantic segmentation of weeds. Images were collected using a handheld MicaSense RedEdge-M multispectral camera mounted on a gimbal, delivering high-resolution spectral data across multiple bands. The collection supports agricultural computer vision research focused on weed detection and segmentation within crop environments. The dataset contains 80 images with pixel-level mask annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{rana2024rafanoset,
title={RafanoSet: Dataset of raw, manually, and automatically annotated Raphanus Raphanistrum weed images for object detection and segmentation.},
author={Rana, Shubham and Gerbino, Salvatore and Barretta, Domenico and Carillo, Petronia and Crimaldi, Mariano and Cirillo, Valerio and Maggio, Albino and Sarghini, Fabrizio},
journal={Data in Brief},
volume={54},
pages={110430},
year={2024},
publisher={Elsevier}
}
This dataset was reformatted from its original format to match HuggingFace standards.
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