Fruit Tree Growth Stage Classification Dataset

The current agricultural industry faces the challenge of accurately monitoring the growth stages of fruit trees. Traditional methods of manual observation are inefficient and prone to errors. Existing solutions often lack specificity and fail to provide real-time feedback on the growth of fruit trees. This dataset aims to use image classification technology to address the technical challenges of identifying fruit tree growth stages, assisting farmers and agricultural managers in optimizing management decisions. The dataset is constructed mainly through a combination of drone photography and ground collection methods, ensuring coverage of various growth environments. For quality control, multiple rounds of annotation and expert review are used to ensure data accuracy and consistency. The data is stored in JPEG format and organized by image ID for easy retrieval and use.