Electric Kettle Appearance Classification Dataset

The retail e-commerce industry is rapidly evolving, facing challenges in accurately classifying diverse product designs. Existing solutions often fall short due to the high variability in product appearances, leading to misclassification and inefficiencies. This dataset aims to address these issues by providing a comprehensive collection of images for various types of electric kettles, enabling better training of machine learning models for accurate classification. Data was collected through a systematic process involving high-resolution image capture in controlled lighting conditions to ensure clarity and reduce background noise. Quality control measures include multiple rounds of labeling by trained professionals, consistency checks, and expert reviews to ensure high accuracy. The dataset is organized in JPG format, with each image accompanied by its corresponding metadata stored in a structured directory format.