Mahua Leaf Image Dataset

The Mahua Leaf Image Dataset is a collection of high-resolution raw images of Mahua (Madhuca longifolia / Madhuca indica) plants captured under natural field conditions. The dataset has been developed under the NMICPS–TiHAN, IIT Hyderabad project, funded by the Department of Science and Technology (DST), Government of India, to support research in computer vision, federated learning, and drone-based precision agriculture. The current release comprises unannotated raw images collected in real agricultural environments, exhibiting varying illumination conditions, background clutter, soil textures, and natural leaf litter. The images capture Mahua plants at different growth stages and show visible variability in leaf color, texture, and stress symptoms, reflecting realistic field scenarios. This dataset is intended to serve as an initial open benchmark for research in plant health analysis, image classification, object detection, and decentralized (federated) learning frameworks. Expert-verified annotation and class-labeled versions (e.g., healthy, diseased, weed-affected) are planned as future updates. The current release comprises unannotated raw images collected in real agricultural environments, exhibiting varying illumination conditions, background clutter, soil textures, and natural leaf litter. The images capture Mahua plants at different growth stages and show visible variability in leaf color, texture, and stress symptoms, reflecting realistic field scenarios. This dataset is intended to serve as an initial open benchmark for research in plant health analysis, image classification, object detection, and decentralized (federated) learning frameworks. Expert-verified annotation and class-labeled versions (e.g., healthy, diseased, weed-affected) are planned as future updates.马胡卡叶片图像数据集（Mahua Leaf Image Dataset）是一套在自然田间环境下采集的高分辨率原始图像集合，涵盖马胡卡（Madhuca longifolia / Madhuca indica）植株的相关影像。该数据集由印度政府科学技术部（Department of Science and Technology, DST）资助的印度理工学院海得拉巴分校NMICPS–TiHAN项目研发，旨在支撑计算机视觉、联邦学习以及无人机精准农业领域的研究工作。 当前发布版本包含在真实农业环境中采集的未标注原始图像，这些图像涵盖了不同光照条件、复杂背景、土壤纹理以及自然落叶等场景。拍摄对象涵盖不同生长阶段的马胡卡植株，展现出叶片颜色、纹理与胁迫症状的显著差异，贴合真实田间场景。 本数据集旨在作为植物健康分析、图像分类、目标检测以及去中心化（联邦）学习框架研究的首个开放基准数据集。后续更新计划将推出专家核验标注版以及带类别标签的版本（例如健康、染病、受杂草影响的类别）。 当前发布版本包含在真实农业环境中采集的未标注原始图像，这些图像涵盖了不同光照条件、复杂背景、土壤纹理以及自然落叶等场景。拍摄对象涵盖不同生长阶段的马胡卡植株，展现出叶片颜色、纹理与胁迫症状的显著差异，贴合真实田间场景。 本数据集旨在作为植物健康分析、图像分类、目标检测以及去中心化（联邦）学习框架研究的首个开放基准数据集。后续更新计划将推出专家核验标注版以及带类别标签的版本（例如健康、染病、受杂草影响的类别）。