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# 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])
```
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