CampanetaWeeds2

The dataset provides pixel-aligned RGB and four-band multispectral imagery acquired in real orchard conditions, enabling cross-spectral weed-detection studies that are scarcely represented in open repositories.  Comprehensive, instance-level annotations for six agronomically relevant weed species support fine-grained object detection and class-imbalance investigation in permanent crops.  The inclusion of three separate flight acquisitions allows researchers to test temporal generalisation, illumination robustness and domain-adaptation strategies.  Accompanying metadata and processing scripts (flight logs, camera parameters, sample notebooks) facilitate reproducibility and rapid experimentation.  Down-stream applications span automated weeding, yield protection and decision-support systems, fostering sustainable orchard management and reducing herbicide usage.