农作物病虫草害图像识别诊断大数据集

数据集包含48种农作物700种病害的3289078张图片，102种虫害100万张图片，及400多种虫害300多万张图片。这些图片经精细过滤处理后，用于训练。通过图像识别算法、数据增强和深度学习，基于庞大的农作物病虫草害图片库，训练出识别模型。此模型能让农业生产者通过手机拍照迅速识别作物病虫草害，即时获取精准信息、防治措施、方法及用药施肥建议，提升农业生产效率与精准度。

The dataset contains 3,289,078 images covering 700 types of diseases affecting 48 crop species, 1,000,000 images for 102 pest species, and over 3,000,000 images for more than 400 pest species. All these images have undergone rigorous filtering prior to being used for model training. Leveraging image recognition algorithms, data augmentation techniques, and deep learning, a recognition model is trained based on this extensive image library of crop diseases, pests, and weeds. This model enables agricultural producers to quickly identify crop diseases, pests, and weeds by taking photos with their mobile phones, and obtain accurate information, prevention and control measures, specific operational methods, as well as pesticide and fertilization recommendations in real time, thereby improving agricultural production efficiency and precision.