Garden Flower Azalea Recognition Image Dataset

In current horticultural management, accurately recognizing azalea varieties is a challenge due to the subtle differences in appearance among varieties. Traditional manual recognition is inefficient and prone to errors. Existing solutions, although utilizing some image recognition technologies, often lack specific datasets for azaleas, resulting in limited accuracy and false recognition capabilities. This dataset aims to solve the accuracy challenges in azalea recognition through large-scale, high-quality azalea image data, aiding the enhancement of intelligent horticultural management. The data consists of azalea images taken with modern high-definition cameras in different seasons and weather conditions, ensuring diversity and authenticity. The images are subjected to multiple rounds of manual and expert review for labeling, with strict control over labeling consistency. The labeling team includes botany experts and experienced horticultural professionals, with more than 20 members. Data preprocessing includes image enhancement, noise reduction, and format conversion, stored in JPG format, organized into a variety directory structure.