Macro photography is characterized by a very shallow depth of field, which challenges classical structure from motion and even camera calibration techniques, since images suffer from large defocussed areas. Computational photography methods such as focus stacking combine the sharp areas of many photos into one, which can produce spectacular images of insects or small structures. In this contribution we analyse the camera model to describe such focus stacked images in photogrammetry and computer vision and derive a camera calibration pipeline for macro photography to enable photogrammetry and 3D reconstruction of tiny objects. We demonstrate the effectiveness of the approach on raytraced images with ground truth and real images.