Juice Product Occlusion Image Dataset

In the current retail e-commerce industry, there is a significant challenge in accurately recognizing products that are partially obscured by packaging or other objects. Existing solutions often struggle with occluded images, resulting in reduced accuracy in product identification and customer dissatisfaction. This dataset aims to address these challenges by providing a diverse collection of images featuring various juice products, such as Tropicana and Minute Maid, under different occlusion scenarios. The data was collected using high-resolution cameras in controlled lighting conditions to ensure clarity and consistency. Rigorous quality control measures were implemented, including multiple rounds of annotation and expert reviews to ensure the reliability of the labels. The dataset is organized in JPG format and consists of structured image files alongside their respective annotations.