Puff Image Classification Dataset

The current retail e-commerce industry faces problems of a wide variety of products and difficulty in user choice, especially in the beauty field where consumers often struggle to find suitable products. Existing image classification methods often cannot effectively handle complex image features, resulting in low classification accuracy. This dataset aims to provide high-quality images of puffs and beauty blenders to help improve the performance of image classification models. The dataset contains 5000 high-resolution images, captured using professional photography equipment under good lighting conditions to ensure clarity and usability. In terms of quality control, the data has undergone multiple rounds of annotation and expert review to ensure consistency and accuracy of the annotations. The data is stored in JPG format for quick access and processing.