PolyGoneNMS

PolyGoneNMS is a library for efficient and distributed polygon Non-Maximum Suppression (NMS) in Python. It supports various NMS methods, intersection calculations, and can handle large numbers of polygons in 1D, 2D, and 3D spaces. PolyGoneNMS uses R-tree data structures and shapely polygon objects for optimal performance.

Benchmark Plots

Features

• Efficient polygon NMS for large numbers of polygons.
• Support for various NMS methods: Default, Soft, and Class Agnostic.
• Support for different intersection methods: IOU, IOS, and Dice.
• R-tree data structure for efficient spatial indexing and querying.
• Distributed processing support using Ray and Dask.
• Comprehensive documentation and examples.

Installation

You can install PolyGoneNMS using pip:

pip install polygone-nms

Quickstart

import numpy as np
from polygone_nms import polygone_nms

# Example input data
data = np.array([
    [0, 0, 1, 1, 0, 1, 0, 0, 1, 0.9],
    [0.5, 0.5, 1.5, 1.5, 0.5, 1.5, 0, 0, 1, 0.8],
])

# Apply NMS
results = nms(data, distributed=None, nms_method="Default", intersection_method="IOU")

print("Filtered indices:", results)

# Filtered data
print("Filtered data:")
print(data[results])

For a more detailed guide on using PolyGoneNMS, please see the Quickstart in the documentation.

Documentation

Detailed documentation is available at:

Contributing

We welcome contributions to the project! Please follow the usual GitHub process for submitting issues or pull requests.

License

This project is licensed under the MIT License.