Mango Leaf Disease Dataset
收藏doi.org2025-03-22 收录
下载链接:
http://doi.org/10.17632/7ghdbftp54.1
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资源简介:
This dataset contains 2,336 processed and 12,730 augmented images of mango leaves, capturing seven diseases and healthy leaves, organized into eight classes to support machine learning in disease detection and plant health monitoring. Images were collected from mango trees in Kashinathpur (Pabna) and Changao (Savar, Dhaka), Bangladesh, using a mobile phone camera over 20 days (October 15 - November 4, 2024).
#Classes and Image Count:
Anthracnose: 326 images
Bacterial Canker: 343 images
Cutting Weevil: 307 images
Die Back: 320 images
Gall Midge: 319 images
Powdery Mildew: 206 images
Sooty Mould: 265 images
Healthy: 250 images
#Purpose:
Facilitates machine learning model development for mango leaf disease detection.
Supports biodiversity research and education on tropical plant health.
Assists farmers and agricultural specialists in early disease identification for better crop management
本数据集包含2,336张经过处理的芒果叶图像及12,730张经过增强的图像,旨在捕捉七种疾病状态及健康叶片,并按八类进行组织,以支持机器学习在疾病检测与植物健康状况监测方面的应用。图像采集自孟加拉国卡辛纳特普尔(帕布纳)和昌高(萨瓦尔,达卡)的芒果树,采用智能手机相机在20天内(2024年10月15日至11月4日)完成。
#类别与图像数量:
炭疽病:326张图像
细菌性溃疡病:343张图像
切割象甲:307张图像
枯死:320张图像
茎蝇:319张图像
白粉病:206张图像
煤烟菌:265张图像
健康:250张图像
#目的:
有助于芒果叶疾病检测的机器学习模型开发。
支持生物多样性研究及热带植物健康教育的普及。
协助农民及农业专家进行早期疾病识别,以优化作物管理。
提供机构:
Mendeley Data



