Contributed to the roboflow/supervision and roboflow/roboflow-python repositories by delivering two features focused on enhancing computer vision workflows. Developed robust mask manipulation capabilities in Python, enabling the move_masks function to support negative offsets for flexible mask positioning and improving input validation to reduce runtime errors. Expanded model prediction input handling by allowing NumPy arrays to be processed as images, converting them to PIL Image objects and encoding them as JPEG for API integration. Emphasized comprehensive testing and clear documentation throughout, strengthening regression safety and maintainability. Work demonstrated depth in image processing, Python development, and automated testing within production codebases.