Intelligent Real-Time Counting of Construction Materials Based on Object Detection

Abstract:

The intelligent counting method of steel based on the deep learning target detection technology is studied in this paper. First， many pictures of steel bars， round steel pipe， and square steel pipe at the construction site are obtained and marked， and a data set containing nearly 400 000 counting points is constructed. Based on the YOLOv4 object detection algorithm， an intelligent steel counting model is established， and the counting accuracy of the steel model is improved by improving its network structure， loss function， and adopting appropriate training strategies. The maximum average precision of the model is 91.41%， with a mean absolute error of 4.07. Based on the above achievements， an APP software is developed， and the real-time counting is completed by taking photos and uploading them.