MLBB Video Analysis
5 大平台、6 个批处理器、90%+ 准确率——从人工审核到自动化流水线
5
Platforms Covered
90%+
Analysis Accuracy
1,207+
Videos Reviewed
25
Python Modules
Reviewing thousands of videos across five social platforms manually is a nightmare—inconsistent criteria, reviewer fatigue, and weeks of turnaround. We replaced that with an automated pipeline: platform-specific fetchers handle the quirks of YouTube, Instagram, TikTok, VK, and Facebook APIs, while 6 batch processors manage parallel execution with checkpointing.
The fast text analyzer achieves 90%+ accuracy at 8-thread concurrency, processing 1000+ videos per batch. For cases requiring visual verification, dedicated video analyzers extract frames and run AI inference. The system was refactored from a 25-file legacy monolith into a modular architecture with unified CLI, making it maintainable and extensible.