Eyeliner Product Image Classification Dataset

The current retail e-commerce industry faces challenges such as low product recognition efficiency and poor user experience, especially in the classification of eyeliner products, where traditional methods fail to meet user demands. Existing solutions often rely on manual labeling, which is inefficient and prone to errors. This dataset aims to provide high-quality eyeliner product images to enhance recognition accuracy and support the training of deep learning models. The data collection process uses high-resolution cameras in a standardized environment to ensure image clarity and consistency. We implement multiple rounds of annotation and expert review procedures to ensure data quality and accuracy. Data are stored in JPG format for quick reading and processing.