Rose Leaf Diseases is a dataset of rose leaf diseases designed to provide high-quality image data for the development and benchmarking of models for detecting rose leaf diseases, and is widely used in the construction of plant monitoring systems.

Dataset composition

The original version of this dataset contains 2,458 images of rose leaves from Bangladesh, categorized into five types: black spot, downy mildew, leaf dryness, healthy leaves, and insect holes.

• Black Spot: 335 images
• Downy Mildew: 316 images
• Dry Leaf Disease: 712 sheets
• Healthy Leaf: 668 sheets
• Insect Hole: 427 images To balance the class distribution and improve model robustness, the data underwent data augmentation processing including rotation, cropping, scaling, flipping, and brightness/contrast adjustment, ultimately expanding to 12,991 rose leaf images. The number of samples for each augmentation class is as follows:
• Black Spot: 2,567 images
• Downy Mildew: 2,564 images
• Dry Leaf (Dry Leaf Disease): 2,641 sheets
• Healthy Leaf: 2,634 sheets
• Insect Hole: 2,585 sheets

  

Citation

DOI (Digital Object Identifier):https://doi.org/10.34740/kaggle/dsv/16438706

@misc{md_parvez_kabir_sazzadul_islam_fernaz_nahar_nur_2026,
title={Rose Leaf Disease Dataset},
url={https://www.kaggle.com/dsv/16438706},
DOI={10.34740/KAGGLE/DSV/16438706},
publisher={Kaggle},
author={Md Parvez Kabir and Sazzadul Islam and Fernaz Nahar Nur},
year={2026}
}