Rose Leaf Disease Detection Dataset

Roses are cherished worldwide as symbols of love, purity, and affection, and they also serve as an important commercial crop. However, various leaf diseases significantly impact their aesthetic value and economic profitability. To address this challenge, we developed a specialized dataset of rose leaf images, aimed at advancing research in machine learning for disease identification.

This dataset was collected through field visits to Golaap Gram, Allah Vorsha Nursery, and Daffodil Nursery. All images were captured under natural daylight to ensure clear and detailed visuals. The dataset is organized into four distinct categories, with both original and augmented versions:
Without Augmentation:
● Black Spot: 432 images
● Downy Mildew: 390 images
● Insects Infected: 431 images
● Healthy: 795 images
Total: 2,048 images
Augmented Classes:
● Black Spot: 4,320 images
● Downy Mildew: 3,900 images
● Insects Infected: 4,310 images
● Healthy: 7,950 images
Total Augmented: 20,480 images
To maximize its usefulness for research purposes, the dataset has undergone comprehensive preprocessing, including image classification, noise reduction, background removal, and augmentation. The augmented dataset significantly enhances the diversity and size of the original dataset, providing a robust foundation for training and testing machine learning models.

玫瑰作为爱情的象征、纯洁的表征以及情感的寄托，在全球范围内备受珍视，同时亦作为一项重要的商业作物而存在。然而，诸多叶片病害对其美学价值和经济收益产生了显著影响。为应对这一挑战，我们精心构建了一组专用的玫瑰叶片图像数据集，旨在推动机器学习在疾病识别领域的研究进展。

本数据集通过实地考察Golaap Gram、Allah Vorsha苗圃以及Daffodil苗圃而收集。所有图像均在自然光线下拍摄，以确保图像清晰且细节丰富。数据集被划分为四个独特的类别，包括原始图像及其增强版本：

未增强类别：
● 黑斑病：432张图像
● 霜霉病：390张图像
● 虫害感染：431张图像
● 健康：795张图像
总计：2,048张图像

增强类别：
● 黑斑病：4,320张图像
● 霜霉病：3,900张图像
● 虫害感染：4,310张图像
● 健康：7,950张图像
总计增强：20,480张图像

为最大化其在研究目的上的实用性，数据集经历了全面的预处理，包括图像分类、噪声降低、背景移除和增强。增强数据集显著增加了原始数据集的多样性和规模，为机器学习模型的训练和测试提供了坚实的基石。

搜集汇总

背景与挑战

背景概述

该数据集专注于玫瑰叶片病害的检测，包含原始和增强后的图像，总计20,480张，分为黑斑病、霜霉病、虫害感染和健康叶片四个类别。数据集经过预处理，适用于机器学习模型的训练和测试。