This project was carried out during our second year at EPITECH in Haskell.
🚀 The aim of this project was to develop an image compressor program based on the K-means algorithm.
Launch the program simply lists the various clusters in the new compressed image.
To launch the program, follow these commands from the root directory of the repository:
make fclean
make
./imageCompressor -n [number_of_clusters] -l [convergence_limit] -f [source_image_pixels_list]
NOTE: if the command
make fcleanreturn an error, it means that no cleaning was necessary.
To get the compressed image in .png format, go to pythonTester directory by executing the command cd pythonTester and follow this command:
./compressor.sh [image_to_compress_path] [number_of_clusters] [convergence_limit]
The new compressed image will be stored in /compressed_images directory.
By executing ./compressor.sh source_images/Apple_Park.jpg 8 5 command, we obtain the following result:
Original image:
Compressed image with 8 clusters and a convergence limit of 5:
