Skincare Lotion Image Classification Dataset

In the retail e-commerce industry, there are numerous types of skincare products, posing decision challenges for consumers. Existing image classification technologies still have deficiencies in recognition accuracy and speed, especially given product diversity and complex backgrounds. This dataset aims to enhance the accuracy of skincare lotion image classification through high-quality image samples and precise annotations, offering better product recommendation services for e-commerce platforms. Data collection was performed using professional photography equipment in a standardized environment to ensure clear images with good lighting conditions. We employed multi-round annotations and expert review mechanisms to ensure consistency and accuracy in data annotation. The data is stored in JPG format, organized by category, facilitating subsequent training and testing use.