A dataset consisting of 6,000 lychee leaf images, including both original and augmented samples, captured under natural lighting with a consistent background.

A well-structured collection of 6,000 lychee leaf images captured in natural environments with a consistent background, expanded through augmentation to improve diversity and dataset balance. Every folder have equal quantity of data. Purpose: 1.Encourages the use of deep learning approaches in agricultural disease detection and analysis. 2.Assists in precise identification and categorization of lychee leaf infections under real-world conditions. 3.Supports the design of automated crop monitoring frameworks that minimize chemical usage and foster sustainable agriculture.