polygone-nms 0.1.7

Description:

polygonenms 0.1.7

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.