To this end, we manually selected 2702 images from patents and patent applications to contain chemical structures of different types, chemical reactions as well as images that do not contain interpretable chemical structures. This dataset is a new, independent test set for image-2-structure recognition methods that provides heterogeneous data including images with different resolutions and different chemistry content types. The dataset is not intended to represent all available images containing chemical structures but is rather inspired by our everyday task of identifying chemicals in patent images. Thus, each of the respective images was in the centre of interest for one of our chemistry clients -both from pharma as well as from chemistry -comprising a mixture of small to medium sized molecules, from inorganic complexes up to peptidic structures and typical heterocyclic structures. In most cases, these images were found to pose problems with a correct structure prediction using our OSRA tool. Thus, this image collection is rather an ad hoc collection of molecules with different modalities instead of a systematic collection following clearly defined principles.