Comprehensive High-Resolution Eggplant Leaf Image Dataset for Plant Disease Detection

This is a comprehensive version of the Eggplant Leaf Image Dataset, designed to support machine learning and deep learning research in agriculture, plant pathology, and computer vision. This dataset addresses class imbalance and model generalization challenges by including a significantly expanded collection of images through controlled data augmentation. The dataset contains a total of 2,180 high-resolution images (4000×6000 pixels), evenly distributed across six categories of eggplant leaf conditions: 1. Healthy: 400 images (80 original + 320 augmented)2. Insect-Pest: 360 images (40 original + 320 augmented)3. Leaf-Spot: 350 images (50 original + 300 augmented)4. Mosaic-Virus: 360 images (15 original + 345 augmented)5. Small-Leaf: 360 images (20 original + 340 augmented)6. Wilt: 350 images (50 original + 300 augmented) All original images were captured using a Canon EOS 1300D DSLR camera under consistent natural lighting conditions. Files are saved in JPG format, and image resolution is preserved within ±5% of the original dimensions to maintain visual fidelity. Data augmentation was performed using the Albumentations library, applying transformations such as rotation, flipping, brightness and color shifts, and padding. The augmentation process was seeded to ensure reproducibility, and all configuration parameters are documented in the accompanying metadata. The metadata.csv file provides a class-wise summary including original image count, augmented image count, augmentation ratios, and the exact augmentation pipeline used. The augmentation was seeded for reproducibility. Note: Original and augmented images are stored together in each class folder. Augmented images are distinguishable by the inclusion of "_aug_" in their filenames. There is no separate folder for augmented images. Files:EggplantLeaf-ImageDataset.zip — Contains all 2,180 images organized by class, along with metadata and readme.metadata.csv — Class-level summary and augmentation details.Readme.md — Technical documentation and usage notes.