The mathematical model for photometric stereo makes several restricting assumptions, which are often not fulfilled in real-life applications. Specifically, an object surface does not always satisfies Lambert’s cosine law, leading to reflection issues. Moreover, the camera and the light source, in some situations, have to be placed at a close distance from the target, rather than at infinite distance from it. When studying algorithms for these complex situations, it is extremely useful to have at disposal synthetic datasets with known exact solutions, to assert the accuracy of a solution method. The aim of this paper is to present a Matlab package which constructs such datasets on the basis of a chosen exact solution, providing a tool for simulating various real camera/light configurations. This package, starting from the mathematical expression of a surface, or from a discrete sampling, allows the user to build a set of images matching a particular light configuration. Setting various parameters makes it possible to simulate different scenarios, which can be used to investigate the performance of reconstruction algorithms in several situations and test their response to lack of ideality in data. The ability to construct large datasets is particularly useful to train machine learning based algorithms.