Garden Flower Impatiens Recognition Image Dataset

Currently, the horticulture and agriculture fields face certain challenges in plant recognition and management, especially in situations where there is a wide variety of plants with similar forms. Manual recognition is inefficient and prone to errors. Existing algorithms have low recognition rates, and datasets are often not comprehensive. The Garden Flower Impatiens Recognition Image Dataset aims to improve the accuracy and efficiency of plant recognition, addressing the automation needs in horticultural management. Data collection is done with high-resolution cameras under natural light conditions to ensure clear and realistic images. Quality control involves multiple rounds of manual annotation and consistency checks, reviewed by an expert team with a background in botany to ensure annotation accuracy. The data is uniformly preprocessed, including size adjustment, color correction, etc., and stored in JPG format to effectively organize and improve retrieval efficiency. The dataset's high annotation precision (over 95%), based on advanced data augmentation techniques, ensures data integrity and consistency. Compared to similar datasets, this dataset has high scarcity and uniqueness, particularly having a significant advantage in recognizing Impatiens species. The dataset not only enhances the accuracy of recognition algorithms but also significantly improves work efficiency in horticultural management. Its high scalability can be applied to recognition tasks of more plant species.