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add data_card.yaml

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+ # Dataset Metadata
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+
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+ dataset_info:
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+ name: AgriField3D
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+ description: >
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+ AgriField3D is a curated dataset of 3D point clouds representing fully field-grown maize plants
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+ from a diverse maize genetic panel. This dataset contains over 1,000 point clouds of maize plants,
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+ collected using a Terrestrial Laser Scanner, and includes various versions of point clouds such as raw,
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+ segmented, and reconstructed surfaces. It is designed to support advanced AI applications in agricultural
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+ research, particularly maize phenotyping and plant structure analysis.
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+
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+ version: 1.0
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+ license: CC-BY-NC-4.0
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+ authors:
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+ - Elvis Kimara
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+ - Mozhgan Hadadi
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+ - Jackson Godbersen
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+ - Aditya Balu
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+ - Zaki Jubery
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+ - Adarsh Krishnamurthy
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+ - Patrick Schnable
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+ - Baskar Ganapathysubramanian
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+ citation: >
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+ @article{kimara2025AgriField3D,
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+ title = "AgriField3D: A Curated 3D Point Cloud Dataset of Field-Grown Plants from a Maize Diversity Panel",
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+ author = "Elvis Kimara, Mozhgan Hadadi, Jackson Godbersen, Aditya Balu, Zaki Jubery, Adarsh Krishnamurthy, Patrick Schnable, Baskar Ganapathysubramanian",
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+ year = "2025"
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+ }
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+
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+ intended_use:
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+ - AI-based agricultural research
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+ - Maize phenotyping
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+ - Plant structure analysis
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+ - 3D data-driven studies in agriculture
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+
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+ features:
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+ - Point clouds: `.ply` format
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+ - Resolutions: 100k, 50k, 10k points
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+ - Data types: Raw, segmented, reconstructed surfaces
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+ - Plant types: Various maize genetic backgrounds
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+ - Segmentation: Individual leaves and stalks color-labeled
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+ - Metadata: Quality of point clouds, leaf count, tassels, and maize cobs presence
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+
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+ dataset_size:
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+ raw_point_clouds:
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+ - "FielGrwon_ZeaMays_RawPCD_100k.zip: 1045 .ply files (100K points per plant)"
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+ - "FielGrwon_ZeaMays_RawPCD_50k.zip: 1045 .ply files (50K points per plant)"
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+ - "FielGrwon_ZeaMays_RawPCD_10k.zip: 1045 .ply files (10K points per plant)"
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+ segmented_point_clouds:
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+ - "FielGrwon_ZeaMays_SegmentedPCD_100k.zip: 520 .ply files (100K points per segmented plant)"
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+ - "FielGrwon_ZeaMays_SegmentedPCD_50k.zip: 520 .ply files (50K points per segmented plant)"
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+ - "FielGrwon_ZeaMays_SegmentedPCD_10k.zip: 520 .ply files (10K points per segmented plant)"
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+ reconstructed_surfaces:
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+ - "FielGrwon_ZeaMays_Reconstructed_Surface_stl.zip: 520 .ply files (reconstructed surfaces)"
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+ - "FielGrwon_ZeaMays_Reconstructed_Surface_dat.zip: 520 .ply files (NURBS surface data)"
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+
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+ dependencies:
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+ - Python 3.6+
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+ - open3d (for visualization)
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+ - MeshLab, CloudCompare (for additional point cloud manipulation)
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+ - trimesh (for 3D mesh processing)
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+
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+ installation_instructions: |
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+ To install the dataset, clone the repository and install the dependencies:
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+ ```bash
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+ git clone https://huggingface.co/datasets/BGLab/AgriField3D
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+ cd AgriField3D
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+ pip install -r requirements.txt
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+ ```
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+
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+ download_instructions: |
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+ 1. Download the zipped files from the following links:
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+ - FielGrwon_ZeaMays_RawPCD_100k.zip
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+ - FielGrwon_ZeaMays_RawPCD_50k.zip
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+ - FielGrwon_ZeaMays_RawPCD_10k.zip
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+ - FielGrwon_ZeaMays_SegmentedPCD_100k.zip
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+ - FielGrwon_ZeaMays_SegmentedPCD_50k.zip
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+ - FielGrwon_ZeaMays_SegmentedPCD_10k.zip
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+ - FielGrwon_ZeaMays_Reconstructed_Surface_stl.zip
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+ - FielGrwon_ZeaMays_Reconstructed_Surface_dat.zip
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+ 2. Extract the `.zip` files:
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+ ```bash
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+ unzip FielGrwon_ZeaMays_RawPCD_100k.zip
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+ unzip FielGrwon_ZeaMays_RawPCD_50k.zip
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+ unzip FielGrwon_ZeaMays_RawPCD_10k.zip
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+ unzip FielGrwon_ZeaMays_SegmentedPCD_100k.zip
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+ unzip FielGrwon_ZeaMays_SegmentedPCD_50k.zip
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+ unzip FielGrwon_ZeaMays_SegmentedPCD_10k.zip
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+ ```
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+
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+ visualization_instructions: |
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+ Use the following Python code to visualize the point clouds:
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+ ```python
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+ import open3d as o3d
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+
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+ # Load and visualize a PLY file
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+ pcd = o3d.io.read_point_cloud("FielGrwon_ZeaMays_RawPCD_100k/0001.ply")
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+ o3d.visualization.draw_geometries([pcd])
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+ ```
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+
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+ repository_links:
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+ - https://huggingface.co/datasets/BGLab/AgriField3D