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.
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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