Since their discovery in 1998 (Nobel Prize) we have learnt a lot about the parameters that govern neutrino oscillations, but there are still many questions remaining. Perhaps the most exciting of these is to determine whether neutrino oscillations violate charge-parity symmetry (CPV), and so could potentially explain why we live in a matter-dominated universe. This project involves the analysis of a unique set of photographs captured by a drone underwater in Super-K. Machine learning image segmentation techniques will be explored to accurately identify photosensors in each photo. Then using the photogrammetry technique, the geometry of Super-K can be measured for the first time after being filled with water. The result will be used by physics analysis through the detector Monte Carlo simulation.