Binocular vision-based power transmission channel hidden danger identification tracking method

A binocular vision-based power transmission channel hidden danger identification tracking method comprises the steps of collecting monitoring data in a power transmission line visual inspection system, and constructing a common external damage hidden danger sample data set of a power transmission line and a power transmission channel; constructing a left-eye and right-eye image hidden danger identification tracking model based on binocular vision; performing convolution and left-eye and right-eye association path operation on input binocular vision information by utilizing deep learning and binocular vision technologies; carrying out loss calculation on the left-eye and right-eye image hidden danger object segmentation contours detected by the initial model and the real segmentation contours in the data set, and carrying out iterative optimization until the whole loss function is completely converged; and putting the trained model into test and use, and receiving binocular vision inputto realize hidden danger