Leaf Pest Severity Assessment Dataset

The current agricultural industry faces a serious threat from pests impacting crops. Traditional manual detection methods are inefficient and prone to errors, unable to respond timely. Existing solutions often rely on the expertise of professionals, resulting in insufficient accuracy and timeliness in pest assessment. This dataset aims to address the efficiency and accuracy issues of existing detection methods by establishing a pest severity model and using AI technology to automatically assess leaf pest severity. The dataset includes leaf images from different farmlands, captured with high resolution and annotated with the number and area of perforations, forming detailed pest assessment indicators. Data collection uses professional photography equipment to ensure image clarity and detail integrity, with collection environments being various crop fields. Quality control measures include multiple rounds of annotation and consistency checks to ensure data reliability and accuracy. The data is stored in JPG and JSON formats, organized by leaf ID for convenient subsequent data processing and analysis.