With the continuous development of smart grid, the automatic reading system of electric energy meter based on digital image processing method is widely used. To improve the accuracy of automatic reading of traditional electric energy meter, a new method of automatic reading of electric energy meter based on YOLOv3 network is proposed. For the electric energy meter image, a counter positioning model based on the YOLOv3-Tiny network is constructed and trained, the trained target model is used to locate the counter target area, and the counter area is generated to achieve a counter image. For the counter image, a counter recognition model based on the YOLOv3 network is constructed and trained, and the trained model is used to identify the number of the counter target area. The electric energy meter data set published by the Federal University of Paraná Brazil was selected as the research object. The comparison experiment with YOLOv2-Tiny positioning model and CR-NET recognition model shows that the proposed method has higher positioning accuracy and recognition accuracy.