Fabric Defect Detection based on Improved Object as Point

In the field of fabric manufacturing, many factories still utilise traditional manual detection method. It requires a lot labour, resulting in high error rates and low efficiency. this paper, we represent realtime automated method based on object as point. This work makes three attributions. First, build defects database augment data to training intelligence model. Second, provide real-time algorithm, which have potential be applied manufacturing. Third, figure out CenterNet with soft NMS will improved performance defect area, is considered an NMS-free algorithm. Experiment results indicated that our lightweight network can effectively efficiently detect five different defects.