PaddyPulse-SLNR

The PaddyPulse-SLNR is a newly constructed dataset developed to support research in automated rice leaf disease classification. It consists of 2,256 high-resolution images (2592×3456 pixels) covering four major rice leaf diseases: brown spot, rice blast, Bacterial leaf streak, and sheath blight. The images were captured under a controlled white background to ensure consistency and to highlight disease characteristics at multiple scales. Data collection was carried out across key rice-growing regions in Northern Province of Sri Lanka, including Mannar, Jaffna, Mullaitivu, and Kilinochchi, incorporating diverse environmental conditions. The dataset includes images from commonly cultivated rice varieties such as Aattakkari, Bg300, Bg406, and Bg360. Image acquisition was performed using multiple devices, including Canon EOS 60D, Canon R6, Nikon D750, and iPhone 14, to ensure variability in imaging conditions. All images were manually annotated and verified by agricultural officers to ensure labeling accuracy.PaddyPulse-SLNR数据集是一个全新构建的数据集，旨在为水稻叶片病害自动分类相关研究提供支撑。该数据集包含2256张分辨率为2592×3456像素的高分辨率图像，涵盖4种主流水稻叶片病害：褐斑病、稻瘟病、细菌性条斑病以及纹枯病。所有图像均在可控白色背景下拍摄，既保证了数据集的一致性，又可多尺度凸显病害特征。数据采集工作覆盖斯里兰卡北部省的核心水稻种植区，包括曼纳尔、贾夫纳、穆莱蒂武与基利诺奇，涵盖了多样的环境条件。该数据集包含当地常见栽培水稻品种的图像，如Aattakkari、Bg300、Bg406及Bg360。图像采集使用了多款设备，包括佳能EOS 60D、佳能R6、尼康D750及iPhone 14，以确保成像条件具备多样性。所有图像均由农业官员进行手动标注与核验，以保障标注的准确性。