Lip Mask Image Classification Dataset

The lip care market in the current retail e-commerce industry is growing rapidly, with increasing consumer demand for lip mask products. However, there is a significant phenomenon of product homogenization in the market, making it difficult for consumers to quickly identify suitable products. Existing product classification methods largely rely on manual labeling, which is inefficient and prone to errors. This dataset aims to improve the identification efficiency of lip mask products using image classification technology, catering to market and consumer needs. Data collection was accomplished through web crawling technology, capturing images of lip mask products from major e-commerce platforms to ensure data diversity and timeliness. We adopted multiple rounds of labeling and expert review for quality control to ensure data accuracy and consistency. The data storage format is JPG, with all images organized by category for convenient subsequent use.