Banana and Banana Leaf Dataset for Classification and Disease Detection

This dataset is curated to support research in banana crop health, focusing on the classification and detection of diseases affecting banana leaves and fruits. It is designed for machine learning and deep learning applications, including image classification and computer vision-based disease diagnosis.

★Dataset Overview:
The dataset includes both raw and augmented images across various categories, covering healthy and diseased banana leaves and fruits. The diseases featured include Anthracnose, Banana Fruit-Scarring Beetle, Banana Skipper Damage, Banana Split Peel, Black and Yellow Sigatoka , Chewing insect damage on banana leaf, Healthy Banana, Healthy Banana leaf and Panama Wilt Disease.

★Composition:
Raw Data: 2375 images
Augmented Data: 9513 images

★Applications:
This dataset is valuable for:

*Machine Learning & AI Research – Training models for automated disease detection.

*Agricultural Studies – Assisting researchers in understanding banana crop health.

*Farmers & Agricultural Experts – Enabling early disease identification for better crop management.

By providing a comprehensive collection of banana and banana leaf conditions, this dataset serves as an essential resource for advancing smart agriculture and precision farming techniques. This dataset isn't just for researchers; it’s also a valuable tool for farmers and agricultural specialists who want to identify diseases early and take action to protect their crops. By using this data, we can work towards smarter farming, healthier plants, and better food security.