Garden Flower Peony (Woody) Identification Image Dataset

In modern garden and agricultural fields, accurately identifying and classifying flower varieties is an important task to improve horticultural management efficiency. However, current traditional identification methods rely on human experience, facing common issues of low accuracy and inefficiency. Existing methods using simple image processing software for identification are often lacking in detail and easily disturbed by the environment, failing to meet the needs of actual production. Therefore, this dataset aims to improve the accuracy and efficiency of peony variety identification through machine learning and deep learning technologies. The data is collected using high-resolution cameras in natural environments during different seasons to ensure diversity and authenticity. Quality control uses a multi-round annotation mechanism, and all images are reviewed by experts to ensure accuracy. The annotation team consists of 20 professionals with backgrounds in botany and horticulture. Data preprocessing includes denoising, standardization, and image enhancement. Data is classified and stored by variety and flowering period to facilitate model training.