Various non-structural features can be added to the structure depiction. Along with atom numbering and chirality labels, there are also curved mechanism arrows, straight reaction arrows, chemical identity labels, rest group labels, and reaction condition labels. The arrow images are randomly picked from a set of available images resized, rotated, and pasted in a position where do (curved arrows) or do not (reaction arrows) overlap with the chemical structure depiction. The labels are generated by arbitrarily combining a variety of available text elements. For example, a chemical identity label is generated as a number (e.g., '1'), a number-letter combination (e.g., '1a'), a number-number combination (e.g., '1-4') or a number-letter-letter combination ('1a-d'). Similarly, rest group labels are generated by combining rest group variables (e.g., 'R', 'X') with randomly picked superatom labels. The list of superatoms that is used here was originally published along with the rule-based OCSR system OSRA . Reaction condition labels are generated by combining the name of a chemical compound, a solvent, and a time. The font size and type for the labels are randomly chosen. The available font types include standard fonts like Arial and Times New Roman but also fewer common fonts that contain, for example, Asian or Greek-style characters. This ensures that there are diverse types of non-structural elements around the chemical structure that a potential deep learning-based OCSR system can learn to ignore as noise. Furthermore, the image augmentation library imgaug is used to add additional image perturbations. This includes a mild rotation, shearing, salt and pepper noise, brightness and colour adjustments, JPEG compression and pixelation.