During March 2026, Begetan focused on stabilizing and extending the ArcFace RKNN inference path within the blakeblackshear/frigate repository. He addressed a critical bug by refining input formatting and data conversion, ensuring that ArcFace models operate reliably with the RKNN runner. His work involved implementing robust normalization and shape handling, as well as converting face data from normalized formats back to uint8 to meet RKNN runtime requirements. Utilizing Python and leveraging skills in data processing and model inference, Begetan’s contributions improved cross-environment compatibility and reduced runtime errors, resulting in a more resilient and production-ready ArcFace RKNN workflow.