2023年南京农业病虫害图像识别数据集

农业病虫害对农作物的产量和品质造成了严重的威胁，因此准确、高效地检测和识别病虫害是农业生产中的重要任务。本文介绍了一个综合的农业病虫害数据集，由农业虫害检测数据集、农业病害检测数据集、农业病害分类数据集和水稻表型分割数据集组成，包含55个类别、48576张，共4.14 GB的图像样本。从公开数据源和学术论文中收集和整理数据，保证了数据集的多样性和代表性。在数据的筛选、清洗和标注过程中，采用了严格的质量控制和验证措施，以确保数据集的准确性和可靠性。该数据集可用于农业病虫害识别和水稻表型鉴定等农业视觉任务，能够为农业病虫害研究提供有价值的资源，并促进农业生产的可持续发展。

Agricultural pests and diseases pose a severe threat to the yield and quality of crops. Therefore, accurate and efficient detection and identification of pests and diseases represent an important task in agricultural production. This paper presents a comprehensive agricultural pest and disease dataset, which consists of four subsets: agricultural pest detection dataset, agricultural disease detection dataset, agricultural disease classification dataset, and rice phenotype segmentation dataset. It contains 48,576 image samples across 55 categories, with a total size of 4.14 GB. Data was collected and organized from public data sources and academic papers, ensuring the diversity and representativeness of the dataset. Strict quality control and validation measures were adopted during the data screening, cleaning and annotation processes, to guarantee the accuracy and reliability of the dataset. This dataset can be applied to agricultural vision tasks such as agricultural pest and disease identification and rice phenotype identification, providing valuable resources for agricultural pest and disease research, and promoting the sustainable development of agricultural production.