# AgriField3D: A Curated 3D Point Cloud Dataset of Field-Grown Plants From A Maize Diversity Panel ## Dataset Structure The dataset consists of two compressed `.zip` files, which contain the 3D point cloud data: ``` AgriField3D/ ├── agrifield3d/ # Main Python package directory │ ├── __init__.py # Initialize the Python package │ ├── dataset.py # Python file to define dataset access functions │ └── utils.py # Helper functions (optional) ├── setup.py # Package setup configuration ├── README.md # Package description ├── requirements.txt # Dependencies ├── MANIFEST.in # Non-Python files to include in the package ├── Metadata.xlsx # Metadata for your dataset ├── PointCloudDownsampler.py # Python script for downsampling └── datasets/ # Directory for zipped datasets ├── FielGrwon_ZeaMays_RawPCD_100k.zip ├── FielGrwon_ZeaMays_RawPCD_50k.zip ├── FielGrwon_ZeaMays_RawPCD_10k.zip ├── FielGrwon_ZeaMays_SegmentedPCD_100k.zip ├── FielGrwon_ZeaMays_SegmentedPCD_50k.zip ├── FielGrwon_ZeaMays_SegmentedPCD_10k.zip ``` ### Contents of the `.zip` Files - **`FielGrwon_ZeaMays_RawPCD_100k.zip`**: - Contains 1045 `.ply` files. Each file has 100K point cloud representing an entire maize plant. - **`FielGrwon_ZeaMays_RawPCD_50k.zip`**: - Contains 1045 `.ply` files. Each file has 50K point cloud representing an entire maize plant. - **`FielGrwon_ZeaMays_RawPCD_10k.zip`**: - Contains 1045 `.ply` files. Each file has 10K point cloud representing an entire maize plant. - **`FielGrwon_ZeaMays_SegmentedPCD_100k.zip`**: - Contains 520 `.ply` files. Each file represents a segmented maize plant by 100K point cloud focusing on specific plant parts. - **`FielGrwon_ZeaMays_SegmentedPCD_50k.zip`**: - Contains 520 `.ply` files. Each file represents a segmented maize plant by 50K point cloud focusing on specific plant parts. - **`FielGrwon_ZeaMays_SegmentedPCD_10k.zip`**: - Contains 520 `.ply` files. Each file represents a segmented maize plant by 10K point cloud focusing on specific plant parts. ### How to Access 1. **Download the `.zip` files**: - [FielGrwon_ZeaMays_RawPCD_100k.zip](https://huggingface.co/datasets/BGLab/AgriField3D/resolve/main/FielGrwon_ZeaMays_RawPCD_100k.zip) - [FielGrwon_ZeaMays_RawPCD_50k.zip](https://huggingface.co/datasets/BGLab/AgriField3D/resolve/main/FielGrwon_ZeaMays_RawPCD_50k.zip) - [FielGrwon_ZeaMays_RawPCD_10k.zip](https://huggingface.co/datasets/BGLab/AgriField3D/resolve/main/FielGrwon_ZeaMays_RawPCD_10k.zip) - [FielGrwon_ZeaMays_SegmentedPCD_100k.zip](https://huggingface.co/datasets/BGLab/AgriField3D/resolve/main/FielGrwon_ZeaMays_SegmentedPCD_100k.zip) - [FielGrwon_ZeaMays_SegmentedPCD_50k.zip](https://huggingface.co/datasets/BGLab/AgriField3D/resolve/main/FielGrwon_ZeaMays_SegmentedPCD_50k.zip) - [FielGrwon_ZeaMays_SegmentedPCD_10k.zip](https://huggingface.co/datasets/BGLab/AgriField3D/resolve/main/FielGrwon_ZeaMays_SegmentedPCD_10k.zip) 2. **Extract the files**: ```bash unzip FielGrwon_ZeaMays_RawPCD_100k.zip unzip FielGrwon_ZeaMays_RawPCD_50k.zip unzip FielGrwon_ZeaMays_RawPCD_10k.zip unzip FielGrwon_ZeaMays_SegmentedPCD_100k.zip unzip FielGrwon_ZeaMays_SegmentedPCD_50k.zip unzip FielGrwon_ZeaMays_SegmentedPCD_10k.zip ``` 3. Use the extracted `.ply` files in tools like: - MeshLab - CloudCompare - Python libraries such as `open3d` or `trimesh`. ### Example Code to Visualize the `.ply` Files in Python ```python import open3d as o3d # Load and visualize a PLY file from the dataset pcd = o3d.io.read_point_cloud("FielGrwon_ZeaMays_RawPCD_100k/0001.ply") o3d.visualization.draw_geometries([pcd]) ```