Garden Flower Rhododendron Identification Image Dataset

In the fields of horticulture and agriculture, accurate identification and classification of specific flowering plants such as rhododendrons are key to achieving refined management and improving production efficiency. However, traditional methods rely on manual identification, which is time-consuming and prone to errors. Existing automatic identification solutions are limited in accuracy and robustness due to insufficient data and inadequate model training. This dataset focuses on the identification of rhododendrons and aims to provide high-quality training data to improve model accuracy and compatibility. The dataset is collected in the field using professional camera equipment to ensure multi-angle, multi-environment image capture. Quality control includes multiple rounds of annotation, strict consistency checks, and review and annotation by a team with a professional botanical background, consisting of more than 20 members. Data preprocessing includes image denoising, standardization, and enhancement processing, with the final storage format in JPG organized by category. This provides researchers with a highly organized dataset for direct application in model training.