Garden Flower Water Lily Identification Image Dataset

In garden management and agroforestry research, plant identification is a key task. Currently, image processing techniques based on high-definition images still have room for improvement in recognition accuracy, especially for morphologically diverse water lily flowers. Most existing solutions perform inadequately in cross-species feature recognition and adaptability, unable to effectively cope with complex natural landscapes and lighting variations. This dataset is constructed to improve the accuracy and adaptability of water lily image recognition, thereby meeting the needs of automated garden management and precise plant research. Data collection is conducted using professional-grade digital cameras under various natural light conditions, covering multiple water lily varieties. Images undergo multiple rounds of expert review and consistency checks to ensure high annotation accuracy and consistency. A botanical expert team with more than 20 members is responsible for the annotation. Data preprocessing employs image enhancement techniques and noise filtering, with all data classified and stored in JPEG format for quick access and use.