Image segmentation masks for curved arrows on molecular images from chemical reaction mechanism images

The dataset presented herein is designed as a ground truth for image segmentation tasks focused on noise extraction in Optical Chemical Structure Recognition (OCSR) processes. It comprises 73 manually extracted and annotated images from real reaction mechanism images, along with 5320 synthetic molecular images generated using RDKit, each featuring computer-drawn curved arrows on random locations on the molecular image pertinent to their respective tasks. Curved arrows are prevalent in chemical reaction mechanism images and significantly impact the accuracy of molecular identity recognition. This dataset aims to enhance OCSR tasks by enabling the pretreatment of molecular images to remove noise, thereby improving molecular recognition accuracy.