Diabetic retinopathy classification device based on local lesion characteristics

The invention belongs to the field of medical image classification, and relates to deep learning, in particular to a diabetic retinopathy classification device based on local lesion features, which isused for solving the problems of poor classification effect of a depth model on a fundus image, lack of interpretability of a result and the like. According to the method, the global features and thelocal lesion information of the fundus image are extracted respectively, so that the information in the image with serious lesion degree can be fully utilized, and the problem of poor application effect of deep learning in the field of sugar network lesion classification caused by insufficient and unbalanced data volume is solved; in addition, in the local focus information extraction process, the labeling result of the local focus information in the fundus image is output, the problem that the interpretability degree of a deep learning model result is low is solved, and the auxiliary effecton disease diagnosis of oph