Plant Growth Stage Classification Dataset

The current agricultural industry faces challenges such as inaccurate growth stage monitoring and insufficient data. Traditional manual identification methods are inefficient and prone to errors. Existing solutions largely rely on experiential judgment, lacking scientific data support. This dataset aims to provide high-quality plant growth stage image data through image classification technology to meet the needs of intelligent agricultural management. The dataset contains 5000 images, collected using high-resolution photography equipment in different growth environments to ensure data diversity and representativeness. During data processing, multiple rounds of annotation and consistency checks were implemented to ensure high precision and consistency of the annotations. Data storage is in JPG format, organized according to strict classification standards, facilitating subsequent machine learning and deep learning model training.