Table shows the accuracy, computed using Equation 6, for each autocharacteriztion method developed in this paper. The automatic band gap extraction method demonstrates the highest accuracy of the three methods at 89.1%, relative to its human-evaluation counterpart. The simple linear relationship between x and E g within the FA 1-x MA x PbI 3 system supports the high performance of the automatic band gap extraction method. Conversely, the trace of I c (x) is parabolic rather the linear, like E g (x), implying that there are more complex chemical mechanisms at work during stability testing. We note the automatic stability measurement method has an accuracy of 87.8%, slightly lower than that of the automatic band gap extraction. Finally, the composition extraction process has an accuracy of 78.8%, which is significantly lower than the accuracies of the other autocharacterization methods, due to error propagation in acquiring Z ref for composition in this study. Overall, each of the three autocharacterization methods developed in this paper exhibits high accuracy between 78%-89%, compared to human evaluation. Furthermore, the key contribution of the developed autocharacterization methods extends past simply accelerating the throughput of sample-by-sample characterization and more largely drives scalable characterization of arbitrarily many samples through the use of com-puter vision, such that characterization is no longer the bottleneck process in high-throughput materials screening.