SI Figure 3. Six images were randomly selected from the test set during training that evaluate the performance of training on the final step (50,000). On each image, the left side is the computer-generated image and the right side is the human labeled image.

Appendix 3: Intersection over union

The model was evaluated throughout the training process using intersection over union (IOU), the degree of overlap between human labeled and computer-generated identifications. Higher IOU represents a greater overlap of the two. For our model, IOU did not depend on the number of images input for training; rather, the uniqueness of objects due to shape and texture was the determining factor. IOU graphs for all object classes are displayed in Supplementary material Fig. 4.