Eyebrow Makeup Product Image Classification Dataset

The current retail e-commerce industry faces the challenge of a wide variety of products and diverse customer needs, especially in the recognition and classification of eyebrow makeup products. Traditional manual annotation methods are inefficient and prone to errors. Existing solutions often fail to meet the requirements for high precision and efficiency, thus there is an urgent need for a high-quality image classification dataset to support the development of automated recognition technologies. This dataset aims to provide a large number of eyebrow makeup product images to assist in training and optimizing image recognition models, thereby enhancing the user shopping experience. Data collection was carried out using professional photographic equipment, shot under natural and standard lighting conditions to ensure image clarity and color accuracy. To ensure data quality, we implemented multiple rounds of annotation and consistency checks, with expert review to ensure annotation accuracy. Data is stored in JPEG format, with structured storage for quick retrieval and analysis.