Our current pipeline of predicting structures from images uses OSRA version 2.1.5. Assuming a hypothetical 1:1:1 mixture of single structure, multi structure and reaction images and with the found OSRA precision values for these three modalities we would end up with an average score of F 1 = (78+62+64)/3*100% = 68% score. Using a hypothetical hybrid system with MolScribe for single images, OSRA for multi structure images and RxnScribe for reactions would yield a better overall F 1 = (93+62+86)/3*100% = 80% score. To achieve this goal, we need to pre-process the images by a classifier that is able to distinguish between these 3 different image modalities. Also, classifying whether or not the image does or does not contain any chemistry can avoid processing time and costs. Therefore, we have developed a Chemical Image Classifier (ChemIC) that classifies any image into one of those 4 categories.