The arthropod compound eye is the most prevalent eye type in the animal kingdom, with an impressive range of shapes and sizes. Studying its natural range of morphologies provides insight into visual ecology, development, and evolution. In contrast to the camera-type eyes we possess, external structures of compound eyes often reveal resolution, sensitivity, and field of view if the eye is spherical. Non-spherical eyes, however, require measuring internal structures using imaging technology like MicroCT (μCT). μCT is a burgeoning 3D X-Ray imaging technique that has been used to image arthropod muscles, brains, ocelli, and eyes. Thus far, there is no efficient tool to automate characterizing compound eye optics in either 2D or 3D data. We present two open-source programs: (1) the ommatidia detecting algorithm (ODA), which automatically measures ommatidia count and diameter in 2D images, and (2) a μCT pipeline (ODA-3D), which calculates anatomical acuity, sensitivity, and field of view across the eye by applying the ODA to 3D data. We validate these algorithms on images, images of replicas, and μCT scans from eyes of ants, fruit flies, moths, and a bee.