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Numba-accelerated local 2D Otsu thresholding for 3D images.

Project description

🧠 Local 2D Otsu Thresholding

Local 2D Otsu Thresholding is a Numba-accelerated implementation of a local 2D Otsu thresholding method for 3D images.

This algorithm adapts the 2D Otsu threshold within a sliding 3D window, enabling robust segmentation in datasets with spatially varying intensity distributions.


⚙️ Installation

Install the latest stable version from PyPI:

pip install otsu2D

🚀 Example Usage

import numpy as np
from otsu2D import getBinary

# Create sample 3D image
img = np.random.randint(0, 256, size=(10, 10, 10), dtype=np.uint8)

# Get threshold map and binary image
binary = getBinary(img, window_size=(3, 3, 3),  mean_window_size =(3,3,3))

🖥️ Command Line Usage

You can execute the script with custom parameters:

python runner.py --shape 10 10 10 --window 3 3 3 --mean_window 3 3 3

📦 Dependencies

  • NumPy
  • Numba
  • Matplotlib

Install dependencies with:

pip install numpy numba matplotlib

📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

🤝 Contributing

Contributions are welcome! If you'd like to fix a bug, add a feature, or improve performance, please open a pull request or contact the maintainers.

💬 Contact

For questions, issues, or feedback, open an issue on GitHub.

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