  We introduce RP2K, a new large-scale retail product dataset for fine-grained
image classification. Unlike previous datasets focusing on relatively few
products, we collect more than 500,000 images of retail products on shelves
belonging to 2000 different products. Our dataset aims to advance the research
in retail object recognition, which has massive applications such as automatic
shelf auditing and image-based product information retrieval. Our dataset
enjoys following properties: (1) It is by far the largest scale dataset in
terms of product categories. (2) All images are captured manually in physical
retail stores with natural lightings, matching the scenario of real
applications. (3) We provide rich annotations to each object, including the
sizes, shapes and flavors/scents. We believe our dataset could benefit both
computer vision research and retail industry. Our dataset is publicly available
at https://www.pinlandata.com/rp2k_dataset.
