Desk Drawer Interaction Area Detection Dataset

The current retail e-commerce industry faces an urgent need for product display and user interaction, especially in the furniture field. Efficiently identifying and displaying the open and closed states of furniture products is a significant challenge. Existing solutions often rely on manual annotation, which is inefficient and prone to errors. This dataset aims to solve the automatic identification of furniture open and closed positions through high-quality image data, enhancing user experience and interaction accuracy. The dataset's structure includes collected furniture images, captured with high-resolution cameras under different lighting and angles to ensure data diversity. The data has undergone multiple rounds of annotation and consistency checks, reviewed by professionals to ensure annotation accuracy and consistency. Data is stored in JPG format, organized in a folder structure for easy subsequent use and access.