Concealer Products Image Classification Dataset

The current retail e-commerce industry faces challenges such as a wide variety of products and difficulties in user selection, especially for concealer products where consumers often struggle to find suitable products. Existing e-commerce platforms fall short in terms of product display and recommendation algorithms, unable to accurately meet user needs. This dataset aims to enhance product recognition accuracy through high-quality images of concealer products, thereby optimizing recommendation systems. Data collection is primarily performed using e-commerce platforms' API and web scraping technology, gathering concealer product images from major e-commerce sites to ensure diversity and comprehensiveness of the data. For quality control, multiple rounds of annotation and consistency checks are conducted to ensure the accuracy of each image's annotation. Data storage is in JPG format, organized by category folders for ease of subsequent analysis and use.