End-to-end face mask detection pipeline integrating data collection, model training with YOLO11s and Faster R-CNN, benchmarking, baseline generation, and FastAPI serving on Google Colab with NVIDIA Tesla T4 GPU. Data flows from Pascal VOC annotations through verification and augmentation stages, with trained models evaluated on accuracy, precision, recall, F1, and inference latency metrics. Production monitoring tracks prediction drift using PSI, KL divergence, and embedding cosine distance stored in SQLite, enabling root cause analysis and dataset improvement cycles. Fork this diagram to customize model selection, add monitoring thresholds, or integrate diagnostic tools like Cleanlab and SHAP for automated data quality assessment.