Over the past decade, the use of automation and specialized software for protein crystallization have become general practice in both academic and industrial settings alike. Advancements in both crystallization automation and software have allowed for higher experiment throughput and an increase in the number and rate of structures determined. With automated imaging systems, researchers can now run even more experiments and program a schedule for capturing images of their protein drops to see how those conditions are performing over time. One bottleneck to this process is manually scoring those protein drop images, which is often very time consuming and tedious.