Multi-mode piping detection method and system based on improved yolov5

The invention relates to the field of computer vision, and provides a multi-modal piping detection method and system based on improved yolov5, and the method comprises the steps: S1, constructing a first modal training image data set, a second modal training image data set, and a third modal training image data set; s2, the improved yolov5 model is trained through the first modal training image data set, the second modal training image data set and the third modal training image data set, and a trained improved yolov5 model is obtained; and S3, inputting an image to be detected into the trained improved yolov5 model to obtain a piping detection result. According to the method, the CBAM attention network and the Focus focus loss function are added into the original yolov5 model, and the GIOULoss loss function is replaced by the CIOULoss loss function, so that the detection performance and the robustness of the yolov5 model are integrally improved; therefore, the trained improved yolov5 model can perform piping