Image Segmentation

A K-means based RGB/GrayScale image segmentor

A k-means segmentation project done for academical purposes. This project is a part of training on continuous integration, version control and C++ Programming, using CMake for the build automation and docker/gitlabCI for the CI pipelining.

The goal of the current project is to design and implement a library for multidimensional K-Means algorithm with a focus on image segmentation use cases.

Building

Make sure you have CMake & OpenCV installed as their documentation stipulates to.

Create a build folder to build the project into it and get the final executable called 'appLauncher' under build/app folder.

mkdir build
cmake -S . -B build/ -DCMAKE_BUILD_TYPE=RELEASE
cmake --build build/

Usage

Choose the --help option to get the min-manual of the CLI.

./appLauncher --help
# Example using default values for maximum iterations
# and centroids intialization while specifying the path
# to save thegenerated data in and the path to save the
# segmentation result file in
./appLauncher --generate data/togenerate/filepath --output segmentation/result/filepath

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

GNU AGPLv3

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Authors : (Team HPC-AI 2020-2021)

• BENCHARRADA Meryem
• RAMI Kader
• BENHARI Abdessalam
• BECHARA Fadi
• EL FAROUKI Ouadie
• LHEIMEUR Nezar

Date : 13/11/2020