A Comprehensive Image Dataset of Plum Leaf and Fruit for Disease Detection and Classification
Description
The Plum Leaf and Fruit Disease Dataset is a comprehensive collection of images designed to facilitate research in computer vision, machine learning, and deep learning for plant disease identification and classification. This dataset includes images of plum leaves and fruits affected by various diseases, enabling researchers to develop automated detection systems for early diagnosis and prevention in agriculture. Original Dataset: - Number of images: 3,554 - Data format: .jpeg, .jpg Processed Dataset: - Number of images: 3,554 - Data format: .jpg Augmented Dataset: - Number of images: 18,000 - Data format: .jpg Augmentation Techniques: 1. Rotation; 2. Flipping; 3. Brightness; 4. Contrast adjustments; 5. Blurring; 6. Shearing; and 7. Scaling Impact on Agricultural Disease Diagnosis: - Early Disease Detection: Automating disease detection reduces dependency on manual inspection, allowing farmers to take preventive measures promptly. - Precision Agriculture: AI-driven models assist in targeted pesticide application, reducing environmental impact and costs. - Scalability & Deployment: The dataset can be used to develop real-time mobile applications for farmers, integrated with IoT-based smart farming systems.