Various chemical structure depictions of the selected SMILES strings were generated using the RanDepict toolkit . The images were created with a resolution of 512 x 512 pixels per image. Each data point was represented by two 8-bit PNG images -one with and one without any image augmentations, excluding hand-drawn-like augmentations. The purpose of introducing augmentation on the images is to mimic real-world scanned pages and to add more complexity. The models were trained using a dataset consisting of 2,048,000 images. These generated images were used as the input for the encoder, and the SMILES strings were defined as the desired decoder output. The SMILES strings were split into meaningful tokens using the Keras tokenizer. The resulting tokenisation scheme splits the input after heavy atoms (such as "C" and "O"), open and closed brackets (such as "(" and ")"), bond symbols ("=" and "#"), special characters(".", "-", "+", "\", "/", "@", "%" and "*"), as well as after every single-digit number. A start token "<start>" and an end token "<end>" were added to the beginning and end of each sequence, respectively. Additionally, each tokenised string was padded using "<pad>" tokens.