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