FLAIR: Federated Learning Annotated Image is an image dataset released by Apple in 2022 for federated learning and privacy-preserving machine learning research. The associated paper is FLAIR: Federated Learning Annotated Image Repository. It aims to provide a benchmarking environment with realistic data heterogeneity for federated learning algorithms.

The dataset contains approximately 430,000 images from 51,000 Flickr users, designed to reflect the challenges faced by federated learning in real-world applications. The images are manually annotated, including over 1,600 fine-grained labels and 17 coarse-grained categories, supporting machine learning tasks of varying complexity.

Dataset Composition

• user_id: Flickr user NSID, used to construct user-based federated learning partitions.
• image_id: Flickr image ID.
• labels: List of coarse-grained labels, mapped from fine-grained labels.
• fine_grained_labels: List of fine-grained labels, indicating the main subjects in the image.
• partition: Data partition identifier, divided into train, val, and test.

Citation

@article{song2022flair,
  title={FLAIR: Federated Learning Annotated Image Repository},
  author={Song, Congzheng and Granqvist, Filip and Talwar, Kunal},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={37792--37805},
  year={2022}
}