Potato Crop Disease Augmentation Dataset

The PotatoCropDiseaseAugmentationDataset is a comprehensive collection of images designed to aid in the development and evaluation of machine learning models for detecting and classifying diseases in potato crops. This dataset includes augmented images representing both healthy and diseased potato plants, encompassing various stages of disease progression. The dataset is structured to support tasks such as disease detection, crop health monitoring, and disease classification.
Subfolders in the Dataset:
The dataset is organized into two main levels of subfolders:

Top-Level Subfolders:

augmented: Contains the disease categories and their corresponding augmented images.
common_scab
cut
dry_rot
gangrene
healthy
violet_root_rot
Inside Each Disease Folder: Each disease or health status subfolder contains images of potato plants with different augmentations applied, including:

Color_Intensity_Modifications
Cutout_Occlusion
Gaussian_Blur
Geometric_Transformations
Noise_Addition
Perspective_Transformation
Random_Brightness_Contrast
Random_Cropping
Random_Hue
Super_Resolution

####Raw_Data:: Shuvo Kumar Basak. (2025). Potato Crop Disease and Health Dataset [Data set]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/10503599

Note for Researchers Using the dataset
This dataset was created by Shuvo Kumar Basak. If you use this dataset for your research or academic purposes, please ensure to cite this dataset appropriately. If you have published your research using this dataset, please share a link to your paper. Good Luck.

马铃薯作物病害增强数据集（PotatoCropDiseaseAugmentationDataset）是一套专业化图像集合，旨在支撑马铃薯作物病害检测与分类相关机器学习模型的研发与评估工作。本数据集涵盖健康与染病马铃薯植株的增强图像，覆盖病害发展的全阶段。数据集的结构设计可适配病害检测、作物健康监测以及病害分类等多项任务需求。

数据集子文件夹结构：
本数据集采用两级子文件夹组织形式：

顶级子文件夹：
augmented：包含各类病害类别及其对应增强图像的子文件夹，下设：
common_scab（普通疮痂病）、cut（切伤）、dry_rot（干腐病）、gangrene（坏疽病）、healthy（健康植株）、violet_root_rot（紫根腐病）

各病害/健康状态子文件夹内部：每个子文件夹均收录经过各类增强处理的马铃薯植株图像，所用增强手段包括：
Color_Intensity_Modifications（颜色强度调整）、Cutout_Occlusion（抠图遮挡）、Gaussian_Blur（高斯模糊）、Geometric_Transformations（几何变换）、Noise_Addition（噪声添加）、Perspective_Transformation（透视变换）、Random_Brightness_Contrast（随机亮度对比度调整）、Random_Cropping（随机裁剪）、Random_Hue（随机色调调整）、Super_Resolution（超分辨率处理）

### 原始数据来源：
舒沃·库马尔·巴沙克（Shuvo Kumar Basak）. (2025). 马铃薯作物病害与健康数据集[数据集]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/10503599

数据集使用者须知：
本数据集由舒沃·库马尔·巴沙克（Shuvo Kumar Basak）制作。若您将本数据集用于科研或学术用途，请务必规范引用该数据集。若您基于本数据集发表了研究成果，欢迎分享您的论文链接。祝研究顺利。