An image dataset for IDADP-grape disease identification

Building an image dataset for machine learning modeling is very important for efficiently identifying agricultural diseases and pests. Therefore, we have constructed an image dataset for agricultural diseases and pests research (IDADP) which covers such aspects of agricultural diseases and pests as image acquisition, classification, labeling, storage and modeling. Meanwhile, this image dataset provides online diagnosis of agricultural diseases and related technical consultation services for scholars and agricultural technicians. The grape disease dataset has about 45.4 GB, and 7 high-quality disease images such as powdery mildew and downy mildew, a total of 3622 images. As a standard dataset for machine learning modeling in large data environment, this image dataset will provide valuable basic data resources. And it has important applicability in promoting the development of agricultural disease identification.