These data contain 250 images of hatchery marked and unmarked otolith images. The images include otoliths with one of four distinct marks. There are 50 images that contain each of the four marks, and 50 images of unmarked otoliths. The images were used to train and test neural networks for use in identifying the marks. The networks were trained on the first thirty images in each class. The remaining twenty images in each class can be used for testing. Two trained networks are included: "binarynet" distinguishes marked and unmarked images, and "classnet" classifies marked images. Two versions of "binarynet" are available: one trained on the same database as "classnet" and a second iteration stored in a "retrained" directory that was finetuned using adversarial samples selected from the training images by "classnet." Finally, a set of software utilities written in python are included that show how the networks were trained and process the images for classification by the networks.