Electric Equipment Panel Detection and Segmentation based on Mask R-CNN

This paper proposed a method for detecting the panel of equipment in the power room based on deep learning technology. For a real-time image, we can achieve the purpose of equipment panel detection and segmentation, which facilitate the task of equipment monitoring. We use the Mask R-CNN algorithm to detect how many target devices there are in the picture and to find the category corresponding to each device. In each target device, the foreground and background are distinguished at the pixel level. The method is described as follows. First of all, we collected a total of 4,500 pictures in 60 categories of power room equipment for our experiments. Next, we labeled all the pictures using Labelimg, which is an open source software for data annotation, the marked pictures were preprocessed as the data set to train and test the proposed model. The well performance on the test set shows that our proposed method has a certain implementability and effectiveness.