• Genetic image generation
• Technical information
• Credits

Genetic image generation

This project is a university assignment that aims at regenerating a reference image from random shapes of random color applied. There will be lots of different tests on what method is the best and/or the fastest to get a new image as close as possible to the reference image.

Technical information

This project is built with conan, ninja and cmake using clang-7 for C++17. To use it, first install clang-7 and lldb 7, then run this:

  conan profile new default --detect
  conan profile update settings.compiler=clang default
  conan profile update settings.compiler.version=7.0 default
  conan profile update settings.compiler.libcxx=libstdc++11 default
  conan profile update env.CC=/bin/clang default
  conan profile update env.CXX=/bin/clang++ default

If you do not wish to overwrite your default profile, you can instead create a new one, for instance clang. To do so, write the name of your new profile (in this example clang) instead of default in the commands shown above.

Then, To build and run the program, go to the root of the project and run this:

  mkdir build && cd build
  conan install .. --build missing
  export CC=clang
  export CXX=clang++
  cmake .. -G Ninja
  cmake --build .

If you want to use another profile than your default one, you should run the following line instead of the second line:

  conan install .. --build missing --profile <your_profile>

This project was built and tested using clang-7, lldb and gdb on Void Linux (kernel 4.19) and Arch Linux (kernel 5.0).

Credits

Awesome C++ project template by devkoriel.