In this paper, we develop four processes for the autocharacterization of perovskites: (i) a hyperspectral vision segmentation process, (ii) an automatic composition extractor, (iii) an automatic band gap computation algorithm, and (iv) an automatic stability measurement method. All the code required for reproducing the autocharacterization results described in this contribution will be made publicly available in full publication. (a) Raw image that contains reflectance information, R, for all pixels, (X, Y ), including the background; (b) visionsegmented image that contains reflectance information for only the target material deposit pixels with a unique feature index assigned to each deposit ( X, Y ). Through the segmentation process described by Algorithm 1, background pixels are removed, illustrated by the gray hatches in (b), such that only the circular material deposit pixels and their corresponding R remain. Furthermore, all material deposit pixels are assigned a unique feature index, illustrated by the purple-to-yellow colormap. Using this segmentation and unique index assignment, the optical data in the R-domain is uniquely mapped onto the deposit it was measured from. This process is equivalent for λ values in both Hyperspectral and RGB regimes.