Chips Product Occlusion Image Dataset

The retail e-commerce industry faces significant challenges in accurately identifying products in images, especially when occlusions occur. Existing solutions often struggle with occluded items, leading to inefficiencies in inventory management and product recognition. This dataset aims to address the specific technical issue of occlusion detection in product images, fulfilling the need for more robust visual recognition systems in retail applications. The dataset is structured to include images of popular chip brands such as Lay's, Pringles, and Doritos, with various levels of occlusion. Data collection involved capturing images in diverse retail settings, utilizing high-resolution cameras to ensure clarity. Quality control measures included multiple rounds of annotations, consistency checks among annotators, and expert reviews to ensure data accuracy. The images are organized in JPG format for efficient storage and retrieval.