Abstract: In order to regularize the standard management of "two tickets" in electric power operation,a lightweight image detection and recognition framework based on deep learning is proposed to realize the rapid recognition of seals and date information in the paper "two tickets" images. This framework starts with the detection of key information such as seal and date based on the YOLOv4 network, followed by the seal and date identification based on MoblileNetv3 and indigenously designed Ghost-OCRNet network. In allusion to the current situation that the date information involves the mixture of handwriting and printed fonts, a lightweight Ghost-OCRNet identification network is designed, which is available to sequentially identify the date without division. The experimental results show that the average running speed of the proposed paper work ticket image recognition method is 5.6 frames/s（FPS） and the recognition accuracy is 93.5 %, which is available for the realtime operation requirements under the premise of ensuring the recognition accuracy.