Green Chili Damage Recognition Dataset

The current agricultural industry faces challenges such as untimely crop pest and disease recognition and low accuracy, leading to serious crop losses. Existing recognition solutions often rely on manual experience, which is inefficient and prone to errors. This dataset aims to provide high-quality images of green chili damage to train deep learning models and improve the accuracy and efficiency of damage recognition. Data collection uses professional cameras under different lighting and environmental conditions to ensure diversity and representativeness. In terms of quality control, the data undergoes multiple rounds of annotation and consistency checks to ensure annotation accuracy. The data is stored in JPG format, organized by category, facilitating subsequent model training and testing.