Abstract: Transmission line is an important part of power grid. To ensure the safety of transmission line is an important means to ensure the stable operation of power system. In this paper, a transmission line detection model based on YOLO (you only look once) algorithm is proposed to detect transmission line objects in visible light images such as UAV. Transmission line identification and detection task has always been a difficult problem in the object detection task. In view of the characteristics of the transmission line slender physical structure, this paper improves the YOLO model of the micro object detection, designs an anchor for the slender physical structure, simplifies the feature extraction network Darknet, and on the basis of maintaining the performance and detection accuracy, lightweight processing of the model is carried out to obtain a lightweight YOLO model that can be trained by a single GPU. Through experiments, the performance of lightweight YOLO model is compared with the original YOLO model, Faster R-CNN and SSD on the test set, the results show detection accuracy of the lightweight YOLO model reaches 83.04%, and the prediction anchor structure and the simplified network model proposed in this paper are effective for transmission line detection.