GRID: Deal with Field Segmentations Elegantly

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Getting started

• Installation: Python 3 | Rasterio | PyPI |

• First-time users: Launch GRID | Demo mode | Work with your images |

Interface

• File loading: Input files | Drag and drop |

• Define AOI: Draw AOI | Adjust AOI |

• Define POI: K-Means clustering algorithm | Binarization | Refine POI | Display/Zoom |

• Detect centroids: Major axis | Minor axis | Centroid adjustment |

• Segmentation: Dynamic | Fixed | Fine-tune results | Export results |

Inputs/Outputs

• Inputs: Images | Maps | Shapefiles |

• Outputs: Tabular results | Validation | Shapefiles | NumPy format of AOI | H5 dataset |

Advanced usage (Jupyter notebook)

• Customize Vegetation Indices

• Multi-Season Images

• Work with QGIS

• Deal with Arbitrary Field Layout

• Generate Datasets for Deep Learning

How to cite GRID

To cite GRID, you can:

• Import GRID.bib

• or manually key in the following info:

@article{Chen and Zhang:2020,
 author       = {Chunpeng James Chen and Zhiwu Zhang},
 title        = {GRID: A Python Package for Field Plot Phenotyping Using Aerial Images},
 month        = may,
 year         = 2020,
 journal      = {Remote Sensing},
 volume       = 12,
 issue        = 11,
 pages        = 1697
 doi          = {10.3390/rs12111697},
 url          = {https://doi.org/10.3390/rs12111697}
}

Support

Find any issue? Post it on GitHub or contact James Chen