LemonLENS: A Real-World Dataset for Multi-Class Lemon Leaf Disease Classification

This dataset contains high-resolution images of lemon (Citrus limon) leaves collected from Baburhat, Chandpur, Bangladesh. The purpose of this dataset is to support machine learning and deep learning-based classification and detection of various lemon leaf diseases. The dataset is organized into nine distinct classes based on visual symptoms. All images were manually collected using a mobile camera and later resized for efficient processing. This dataset can be used for training, testing, and validating image classification models. Classes and Number of Images: 1. Algal Leaf Spot: 500 images 2. Black Spot: 500 images 3. Citrus Canker: 500 images 4. Citrus Pest: 500 images 5. Citrus Scab: 500 images 6. Greening: 500 images 7. Healthy Leaf: 500 images 8. Leaf Curl: 500 images 9. Yellowspot: 500 images Total Images: 4500 Image Details: Original Resolution: 3024 x 4032 pixels Compressed Resolution: 1920 x 1080 pixels Image Format: JPG Color Mode: RGB Collection Device: Smartphone camera Location: Baburhat, Chandpur, Bangladesh