During December 2024, Adsha integrated hardware-accelerated image processing features into the espressif/opencv repository, focusing on leveraging the FastCV library for performance gains. The work centered on enabling element-wise multiplication across multiple data types, including 8-bit unsigned, 16-bit signed, and 32-bit float, and implementing optimized fast-paths for pyrDown and BGR-based color conversions such as BGR to HSV and BGR to YUVApprox. Using C and C++, Adsha’s contributions reduced computational load for embedded vision tasks. The project demonstrated depth in hardware acceleration and image processing, with effective collaboration and code review practices throughout the development and mainline merge process.