植物叶片病害严重程度评估数据集

1、数据来源与采集机制：
本数据集公开数据库资源构成，图像涵盖不同植物种类、典型病害类型及其各级严重程度标签，确保评估任务的全面性。
2、数据处理、分级标注与增强：
对采集的图像进行质量筛查、去噪、裁剪等清洗操作后，由专业人员依据病斑面积、分布、颜色变化等指标进行严重程度分级标注。
3、模型训练与持续优化流程：
清洗与标注后的数据被用于训练植物病害严重程度评估模型，模型可输出病害等级、病斑面积估计或相应的严重度指数。

1. Data Source and Acquisition Mechanism: This dataset is constructed from public database resources. The included images cover various plant species, typical disease types and severity labels of all grades, ensuring the comprehensiveness of the evaluation tasks.
2. Data Processing, Graded Annotation and Augmentation: After performing cleaning operations such as quality screening, denoising and cropping on the collected images, professional annotators conduct graded annotation of disease severity based on indicators including lesion area, distribution and color changes.
3. Model Training and Continuous Optimization Process: The cleaned and annotated data is used to train the plant disease severity evaluation model, which can output disease severity grades, lesion area estimates or corresponding severity indices.

搜集汇总

背景与挑战

背景概述

该数据集包含12098张植物叶片病害图像，用于评估病害严重程度，由贵州大学自行产生。它支持农业病害自动评估、植物健康监测和精准农业等应用场景，数据经过专业分级标注，适用于模型训练和科研教学。