Recent advancements have improved image recognition, especially in Fine-Grained Image Recognition (FGIR). FGIR is essential for smart cities, public safety, ecological protection, and agriculture. The primary challenge is distinguishing subtle differences between objects with similar appearances. Current FGIR methods fall under three categories, but there is no unified open-source library available.
To address this, researchers at Nanjing University of Science and Technology introduce Hawkeye, a PyTorch-based library for FGIR. It offers 16 representative methods across six paradigms and emphasizes modular design for easy integration and customization. Hawkeye also prioritizes readability, simplifies the training process, provides YAML configuration files, and allows users to tailor experiments accordingly.
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