Existing image-recognition methods can enhance the datacollection efficiency for exploring unknown materials. Furthermore, the use of images eliminates the need for data processing, such as interpolation. This study's approach has the potential to significantly improve data efficiency by eliminating the need for extensive preprocessing and to enable chemist-like classifications of chemical structures, paving the way for more intuitive and automated methodologies in materials discovery and computational chemistry.