Banana and Banana Leaf Dataset for Classification and Disease Detection
Description
This dataset is curated to support research in the classification and detection of banana and banana leaf conditions, focusing on identifying diseases affecting banana crops. The dataset is suitable for machine learning tasks like image classification and computer vision applications. It comprises both raw and augmented data for a diverse set of banana-related categories, including healthy and diseased leaves and fruits. #Raw Data: Healthy Banana Leaf: 1,256 images Black Leaf Streak: 63 images Panama Disease: 56 images Banana Scab Moth: 20 images Black Sigatoka: 170 images Good Banana: 56 images Black Pitting/Banana Rust: 788 images Crown Rot: 57 images Fungal Disease: 565 images #Augmented Data: Healthy Banana Leaf: 6,258 images Black Leaf Streak: 315 images Panama Disease: 280 images Banana Scab Moth: 100 images Black Sigatoka: 850 images Good Banana: 172 images Black Pitting/Banana Rust: 3,965 images Crown Rot: 285 images Fungal Disease: 2,825 images #This dataset aims to facilitate the development of machine learning models for banana disease detection, promote biodiversity studies, and support education on plant health. It provides valuable insights for agricultural experts and farmers to identify diseases early for better crop management.