AI-MedLeafX: A Large-Scale Computer Vision Dataset for Medicinal Plant Diagnosis
Description
The AI-MedLeafX dataset is a curated collection of 10,858 original images and 65,178 augmented images of medicinal plant leaves, categorized into healthy and diseased conditions. The dataset primarily focuses on four medicinal plant species—Cinnamomum camphora, Terminalia Chebula, Moringa Oleifera, and Azadirachta Indica—and covers common leaf diseases such as Bacterial Spot, Shot Hole, Powdery Mildew, and Yellow Leaf Disease. Category: 1. Cinnamomum Camphora Healthy Leaf: 800 2. Cinnamomum Camphora Bacterial Spot: 801 3. Cinnamomum Camphora Shot Hole: 795 4. Terminalia Chebula Bacterial Spot: 803 5. Terminalia Chebula Healthy Leaf: 816 6. Terminalia Chebula Shot Hole: 802 7. Moringa Oleifera Healthy Leaf: 860 8. Moringa Oleifera Bacterial Spot: 804 9. Moringa Oleifera Yellow Leaf: 814 10. Azadirachta Indica Healthy Leaf: 1021 11. Azadirachta Indica Shot Hole: 834 12. Azadirachta indica Powdery Mildew: 854 13. Azadirachta indica Yellow Leaf: 854 Total: 10,858 This dataset is designed to facilitate machine learning (ML), deep learning (DL), and computer vision (CV) applications in plant disease recognition, aiding automated medicinal plant health monitoring and disease classification systems. The images were collected from the following locations in Dhaka, Bangladesh: - National Botanical Garden (Latitude: 23.8110° N, Longitude: 90.3563° E) - Daffodil Smart City (Latitude: 23.8720° N, Longitude: 90.2686° E) The AI-MedLeafX dataset contributes to the advancement of computer vision in plant pathology and can be extended for research in precision agriculture, herbal medicine authentication, and disease diagnosis.