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README.md

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 # AgriField3D: A Curated 3D Point Cloud Dataset of Field-Grown Plants From A Maize Diversity Panel
 
+## Overview
+The application of artificial intelligence (AI) in three-dimensional (3D) agricultural research, particularly for maize, 
+has been limited by the scarcity of large-scale, diverse datasets. While 2D image datasets are abundant, they cannot capture 
+essential structural details such as leaf architecture, plant volume, and spatial arrangements that 3D data can provide. 
+To address this limitation, we present a curated dataset of 3D point clouds of fully field-grown maize plants with diverse 
+genetic backgrounds designed to be AI-ready for advancing agricultural research. Our dataset comprises over 1,000 high-quality 
+point clouds representing diverse maize varieties collected using a Terrestrial Laser Scanner. To enhance the usability of the 
+dataset, we performed graph-based segmentation to isolate individual leaves and stalk point clouds. Each leaf is assigned a 
+consistent color label across all plants based on its order from bottom to top (e.g., all first leaves are the same color, 
+all second leaves are the same color, and so on). Similarly, all stalks are assigned a single, distinct color. A rigorous 
+quality control process was undertaken to manually correct any errors in the segmentation and leaf ordering. This ensures 
+accurate segmentation and consistent color labeling and facilitates precise leaf counting and structural analysis. Additionally, 
+the dataset includes metadata describing point cloud quality, the number of leaves, and the presence of tassels and maize cobs. 
+To support diverse AI applications, we provide code that can sub-sample each point cloud to create a user-defined resolution 
+(100k, 50k, 10k points, etc.) through uniform downsampling. All versions were manually quality-checked to ensure the preservation 
+of topology and plant structure. This dataset lays the foundation for leveraging 3D data to enable advanced applications in agricultural 
+research, particularly for maize phenotyping and plant structure studies.
 ## Dataset Structure
 
 The dataset consists of two compressed `.zip` files, which contain the 3D point cloud data: