The particle count re evaluation system is used to analyze the detection report data (particle count) of friendly particle indentation inspection machines. For products with particle counts less than the set threshold, traditional image algorithms and AI deep learning systems are used for secondary re evaluation, greatly improving the detection accuracy. The real NG data is uploaded through CIM and locked.