Household Paper Products Occlusion Image Dataset

Currently, the retail e-commerce industry faces challenges in accurately detecting and categorizing household paper products due to varying packaging designs and occlusions in images. Existing datasets often lack diversity in terms of occlusion scenarios and packaging types, leading to reduced model performance in real-world applications. This dataset aims to address these issues by providing a comprehensive collection of images featuring various household paper products like Kleenex, Scott, Charmin, and Tempo, focusing on different occlusion conditions. Data is collected using high-resolution cameras in controlled environments, ensuring clarity and detail. Quality control measures include multi-round annotations, consistency checks, and expert reviews to maintain high annotation precision. The images are stored in JPG format, organized by product type and occlusion level, facilitating easy access and use in training algorithms.