PepperDisease

This dataset is a curated collection of images and metadata used for the study titled "A Multi-Modal Framework for Pepper Disease and Pest Detection". The dataset includes high-quality images of pepper plants exhibiting various symptoms of diseases and pest infestations, annotated with relevant metadata for use in machine learning and deep learning applications. It is designed to support researchers and practitioners in developing and evaluating models for accurate disease diagnosis and pest identification in agricultural settings.
This dataset is particularly suited for:

Developing supervised learning models for disease and pest detection.
Training image classification, object detection, and segmentation algorithms.
Evaluating the robustness of algorithms under varying environmental conditions.

Due to confidentiality agreements with agricultural partners, this dataset represents only a subset of the complete data used in the study.
The complete dataset and associated code are available upon request. Please contact the corresponding author for details.
After project completion, the full dataset will be made publicly available on GitHub.

本数据集为精心挑选的图像及元数据集合，旨在支持对名为《基于多模态框架的辣椒病害与害虫检测》的研究。数据集包含高质量的辣椒植株图像，展示了多种病害症状及害虫侵染情况，并附有相关元数据，以供机器学习与深度学习应用中使用。其旨在辅助研究人员与从业者开发与评估农业环境下的疾病诊断及害虫识别模型。该数据集尤其适用于：

开发用于病害和害虫检测的监督学习模型。
训练图像分类、目标检测与分割算法。
评估算法在不同环境条件下的鲁棒性。

鉴于与农业合作伙伴的保密协议，本数据集仅代表研究中使用的完整数据的一个子集。完整数据集及相应代码可根据需求提供，详情请联系通讯作者。项目完成后，完整数据集将公开发布于GitHub平台。