Baseball Cap Occluded Images

The retail e-commerce industry faces significant challenges in accurately identifying products in images, particularly when they are partially obscured. Current solutions often struggle with recognizing items like baseball caps when they block important visual cues such as logos. This dataset aims to address the technical issues related to occluded object detection in images, providing a rich resource for training models capable of understanding complex visual scenarios. The dataset was compiled using images sourced from various e-commerce platforms, captured under diverse lighting conditions and angles. Quality control measures include multi-round annotations, consistency checks, and expert reviews to ensure high accuracy and reliability. The images are stored in JPG format, organized in directories based on occlusion types to facilitate easy access and retrieval.