Abstract: The Kuang-chi cloud platform is used to pull the airbag with a cable rope. Since the aerial photography system is suspended under the airbag, the captured image inevitably contains the rope information, which affects the image quality and needs to eliminated in the scene analysis and object detection. A rope detection algorithm based on U-net model was proposed, which introduced the separable convolution to improve the detection speed and adopted a weighted cross entropy as a loss function to solve the problem of convergence instability caused by category imbalance. The final model was able to quickly and accurately detect the rope with fewer data in less time, and then the rope image waseliminated using the fast marching method algorithm (FMM). The test results show that the mean intersection over union(mIOU) of the algorithm reaches 62.8% and has obtained good results.