A fundus image processing method comprising: receiving a collected fundus image; identifying the fundus image via a first neural network to generate a first feature set of the fundus image; identifying the fundus image via a second neural network to generate a second feature set of the fundus image, wherein the first feature set and the second feature set indicate different lesion attributes of the fundus image; combining the first feature set and the second feature set to obtain a combined feature set of the fundus image; and inputting the combined feature set into a classifier to obtain a classification result.