Computing systems and computer-implemented methods can be used for automatically generating a digital line drawing of the contents of a photograph. In various examples, these techniques include use of a neural network, referred to as a generator network, that is trained on a dataset of photographs and human-generated line drawings of the photographs. The training data set teaches the neural network to trace the edges and features of objects in the photographs, as well as which edges or features can be ignored. The output of the generator network is a two-tone digital image, where the background of the image is one tone, and the contents in the input photographs are represented by lines drawn in the second tone. In some examples, a second neural network, referred to as a restorer network, can further process the output of the generator network, and remove visual artifacts and clean up the lines.