YOLIC labeling: A semi-automated image annotation tool with segment anything model for cell-wise labeling

We introduce YOLIC Labeling, a tool designed to streamline the creation of high-quality datasets for cell wise object localization and classification. This tool integrates the Segment Anything Model (SAM) with customizable cell configurations (predefined regions of interest within images) to offer efficient and precise annotations. Key features include SAM-assisted labeling, manual polygon-based annotation, and semi-automatic labeling capabilities. By reducing manual labeling effort while maintaining accuracy, the tool supports the development of robust object localization and classification models, particularly those based on the You-Only-Look-at-Interested-Cells (YOLIC) methodology. YOLIC Labeling addresses the growing demand for efficient, versatile image annotation solutions in computer vision, with applications ranging from autonomous driving to smart industrial systems.