Recovering three-dimensional shape from two-dimensional images is a long-standing problem in computer vision. First proposed in the 1980s, photometric stereo has matured to the point that accurate recovery of complex shapes and surfaces has become achievable. However, such methods typically demand multiple image captures, highly controlled scene conditions and elaborate experiment designs which require calibration. Building on previous work, we propose using a variant of photometric stereo which needs only a single image of an object in a colourful environment and we now remove the requirement of a calibration step. Instead we build an entirely synthetic graphics model of our capture environment (a colourful box) and carry out a synthetic calibration. The validity of this approach is demonstrated by benchmarking real world experiments against ground truth data and comparison with previous work.