DECIMER Image Transformer as the DECIMER core component achieves highly accurate results on the in-domain test data. The system performs better on non-augmented test images since augmented images contain a wide range of additional non-structural elements and noise that have to be ignored in order to correctly translate a chemical structure depiction. This effect is diminished when images of a higher resolution are processed because a low-resolution image may already be comparably blurry and may turn unrecognisable when additional augmentations are applied. The DECIMER Image Transformer model produces predictions that are highly similar to the original molecules with an average Tanimoto similarity over 0.95. The translation of depictions of Markush structures yields similar results, although the proportion of perfectly predicted structures is considerably lowered. This may be traced to the relevance of the small subscript indices of the R-groups (as in 'R 1 '). It could be shown that especially in images with a lower resolution of 299 x 299 pixels, these small digits may become unrecognisable, whereas corresponding images with a resolution of 512 x 512 pixels could be processed with a significant increase in the number of perfectly-recognized Markush structures (see Supplementary Table and Supplementary Figure ). Moreover, the BLEU scores, which are consistently above 0.9 (see Supplementary Table ), confirm that the Markush structure predictions are very similar to the original SMILES strings.