Papaya Leaf Disease Image Dataset

This dataset comprises a comprehensive collection of 3626 raw images and 18,130 augmented images of papaya leaves, capturing a diverse range of diseases and healthy conditions. Originally sourced from Ashulia, Bangladesh, the dataset includes 8 distinct classes: Anthracnose (230 images), Bacterial Spot (214 images), Curl (778 images), Healthy (594 images), Mealybug (182 images), Mite Disease (552 images), Mosaic (546 images), and Ringspot (530 images). This dataset serves as a valuable resource for researchers and practitioners in agricultural science, machine learning, and plant pathology, facilitating the development of automated disease detection and classification systems. Each image is labeled according to its corresponding class, providing a robust foundation for training and validating models aimed at enhancing papaya crop health and management.