1. A computer-implemented method comprising: aggregating, by a computing device, a first user image selection and a context attribute associated with the first user image selection into a preference training database for a user, wherein the first user image selection represents a record of how the user has preferred over at least one of adjusted versions of a base image when the adjusted versions are separately processed by visual effects that are different; determining, by the computing device, a visual effect preference associated with the user based on machine learning or statistical analysis of user image selections in the preference training database, wherein the user image selections represent experimental records corresponding to the visual effects, wherein the visual effect preference is an image processing rule that is particular to the context attribute, and wherein the image processing rule specifies a visual effect process to execute when a digital image is determined to be associated with the context attribute; updating, by the computing device, a photo preference profile with the visual effect preference; and providing, by the computing device, the photo preference profile to an image processor to adjust subsequently captured photographs provided to the image processor.