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.