LemonLENS: A Real-World Dataset for Multi-Class Lemon Leaf Disease Classification
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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 six 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: 528 images 2. Black Spot: 583 images 3. Citrus Canker: 578 images 4. Citrus Pest: 544 images 5. Greening: 528 images 6. Healthy Leaf: 505 images Total Images: 3,266 Image Details: Original Resolution: 3024 x 4032 pixels Compressed Resolution: 560 x 420 pixels Image Format: JPEG Color Mode: RGB Collection Device: Smartphone camera Location: Baburhat, Chandpur, Bangladesh



