Sunscreen Clothing Image Classification Dataset

The current retail e-commerce industry faces challenges of diverse product types and consumer choice difficulties, especially in the category of sunscreen clothing, where consumers need to quickly identify and select suitable products. Existing image recognition technology struggles with low accuracy and poor real-time performance in sunscreen clothing classification, leading to a suboptimal user experience. This dataset aims to address the issue of insufficient image classification accuracy by providing a large number of high-quality sunscreen clothing images to meet the market demand for efficient product recognition. The dataset includes images from different sources, collected using high-resolution cameras and shot under various lighting and background conditions to ensure data diversity. For quality control, multiple rounds of annotation and consistency checks were employed to ensure annotation accuracy. Additionally, all data is stored in JPEG format and organized by category for easy subsequent processing and analysis.