Developed a real-time camera visualization node for the Stanford-AUV/RoboSub repository, focusing on enhancing testing and debugging workflows in ROS 2 environments. The solution, implemented in Python with OpenCV and ROS 2, subscribes to both raw and compressed image topics, converts incoming data to OpenCV format, and displays the streams in separate windows for improved situational awareness during field operations. Robust error handling was incorporated to manage image conversion issues, and the node ensures proper resource cleanup on shutdown. This feature streamlines the process of diagnosing issues by providing immediate visual feedback from the robot’s camera stack during development and testing.