The parameters of the optic disc are important indicators for measuring the health status and lesions of the fundus. The detection and localization of the optic disc is especially important for observing the shape of the optic disc. Research on optic disc positioning in the past mainly depends on the shape and brightness of the optic disc, and the direction of the fundus blood vessels, and image-processing methods are used to locate the optic disc in fundus images. Due to the influence of human factors, the feature extraction time is long and the optic disc positioning efficiency is low. We propose a method of locating optic disc of the fundus image based on the YOLO algorithm. The YOLO algorithm is used to divide the fundus image into N×N grids, and each grid is responsible for detecting whether the center point of the disc falls into the grid. The multi-scale method and the residual layer are fused with low-level features to locate the disc, and bounding boxes of different sizes are obtained. The bounding box with the highest score is finally selected through non-maximum suppression. We test the proposed localization method on three open databases of fundus images (DRIVE、DRISHTI-GS1 and MESSIDOR). The positioning accuracy is 100%, and the center point coordinates of the optic disc are located in the experiment. The average Euclidean distances to the center points are 22.36 px, 2.52 px, 21.42 px, respectively, which verifies the accuracy and versatility of the method.