Cabinet Slot Detection Dataset

With the rapid development of the retail e-commerce industry, consumer demands for product display are increasing, especially in the purchase of large items like furniture. Users need to accurately identify where the product can be opened. However, the current manual annotation methods are inefficient and prone to errors, failing to meet the fast-growing market demands. This dataset aims to provide high-quality data for cabinet slot detection, helping models quickly and accurately determine 'where it can be opened.' Data collection uses professional shooting equipment and captures various types of cabinets under standard lighting conditions, ensuring data quality through multiple rounds of annotation and consistency checks. The data is stored in JPEG format and organized by category and shooting angle to facilitate further use and retrieval. The core advantages of this dataset are its high annotation accuracy and consistency, with annotation accuracy reaching over 95% through multiple rounds of reviews. Innovative annotation processes and data enhancement techniques have improved model performance on the slot detection task by 30%. This dataset provides high-quality training material for researchers and data support for e-commerce platforms to optimize user experience.