Abstract
In order to meet the business needs of power inspection. The requirement is to identify the target quickly and in batches. In this paper, yolov4 convolution neural network is used as the technical to realize the target detection process of power inspection photos. Firstly, the training data set of power patrol inspection is accurately labeled by labelimg. Then it is trained by the deep learning framework of Darknet. And the results are satisfactory. The test results show that tthe Precision is 0.92 and the Recall is 0.904 after training by the self-designed training data set of electric power inspection target detection.This detection effect can meet part of the requirements of target detection in power inspection. However, there are two problems in this test: the lack of data annotation set in power inspection and the serious overlap of different objects in some photos of the data set. The author of this paper hopes the relevant researchers to correct and supplement.
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