OCR-Based Video Review System: Technology Selection, Optimization, and Model Fine-Tuning
An OCR‑based video review system using PaddleOCR’s DB detector and SVTR recognizer, combined with multi‑level frame deduplication, message‑queue task decoupling, Redis prioritization, and dynamic thread‑pool scheduling, was fine‑tuned on 5 000 samples to cut daily frames from 794 million to 3.6 million, achieving automated detection of over 230 abnormal videos per day and replacing three manual reviewers, with future plans for GPU acceleration and cross‑instance GRPC dispatch.