Image Dataset for Detection and classification of Diseases of Guava Fruits and Leaves

The Guava Disease Detection Dataset provides annotated images of guava fruits and leaves, covering both healthy and disease-affected samples. It includes 3432 original images (1119 of fruits and 2313 of leaves) and an augmented set totaling 20344 images. Disease types for fruits include anthracnose, scab, and styler end rot, while leaves exhibit anthracnose, canker, dot, and rust. This dataset supports the development of machine learning models for precise disease detection in guava crops, enabling early interventions and improved disease management in agriculture.
#Total Original Images: 3432 images (1119 fruits, 2313 leaves)
#Augmented Images: 20344 images (10145 fruits, 10199 leaves)

#Fruit Dataset:
Healthy: 470 images
Anthracnose: 263 images
Styler End Rot: 262 images
Scab: 119 images

#Leaf Dataset:
Healthy: 1498 images
Anthracnose: 237 images
Canker: 192 images
Dot: 219 images
Rust: 167 images

#Purpose: Enables the creation of machine learning models for early guava disease detection, promoting efficient disease management and reducing crop loss.