inputting an image to be detected into a detection model being pre-constructed and detecting the image to be detected;

wherein the detection model comprises:

a defect classification identification sub-model configured to identify a classification of a defect in the image to be detected; wherein the defect classification identification sub-model comprises a plurality of base models and a secondary model;

the plurality of base models are configured to respectively determine an initial classification of the defect in the image to be detected; and

the secondary model is configured to determine a final classification of the defect in the image to be detected according to input data obtained by integrating output data of the plurality of base models;

wherein the detection model further comprises: a defect position identification sub-model configured to mark a position of the defect in the image to be detected;

wherein the defect position identification sub-model is an object detector; and

wherein the defect position identification sub-model is obtained by training the object detector based on an original data set;

the training the object detector based on the original data set comprises:

acquiring the original data set comprising a plurality of images to be detected with known defects; and

classifying first regions corresponding to defects of all classifications of defects in the plurality of images to be detected with known defects into one classification as a foreground and classifying regions outside the first regions in the plurality of images to be detected with known defects into the other classification as a background such that the object detector only distinguishes between the foreground and the background when the object detector is trained, to identify only positions of the defects.