1. A method comprising: acquiring data of a digital image which depicts one or more objects; determining a plurality of in-focus probabilities by applying a plurality of in-focus classifier sets to the data; wherein each in-focus probability indicates a likelihood that any of the one or more objects is depicted in focus in the digital image; determining an in-focus cumulative probability based on the plurality of in-focus probabilities; determining whether the in-focus cumulative probability is below an in-focus threshold; in response to determining that the in-focus cumulative probability is below the in-focus threshold, performing the steps of: determining a plurality of slightly-out-of-focus probabilities by applying a plurality of slightly-out-of-focus classifier sets to the data; wherein each slightly-out-of-focus probability indicates a likelihood that any of the one or more objects is depicted slightly-out-of focus in the digital image; determining slightly-out-of-focus cumulative probability based on the plurality of slightly-out-of-focus probabilities; and in response to determining that the slightly-out-of-focus cumulative probability is equal to, or above, a slightly-out-of-focus threshold, determining a particular object, of the one or more objects, that is depicted in the digital image slightly-out-of-focus; and wherein the method is performed by one or more computing devices.