Please install cppcheck in your system.
python -m virtualenv .venv
.venv\Scripts\activate
python -m pip install --upgrade pip
pip install pre-commit lizard
pre-commit install- CMake greater than 3.25.2,
- Catch v3.3.1,
- OpenCV 4.7.0 with contribs.
Just install by installer check if it is in path.
Windows version:
git clone https://github.com/catchorg/Catch2.git
cd Catch2
git checkout v3.3.1
mkdir build
cd build
cmake -G "Visual Studio 17 2022" -A x64 -D CMAKE_INSTALL_PREFIX:PATH=YOUR_CATCH_INSTALL_DIR ..
cmake --build . --config Debug
cmake --build . --config Debug --target INSTALL
cmake --build . --config Release
cmake --build . --config Release --target INSTALL
To be precise -G flag is a generator, -A is selected architecture. This is only example and you can choose some different option. At the end you must set environmental variable CATCH_DIR to YOUR_CATCH_INSTALL_DIR. Now you can delete build and cloned repository.
Windows version:
git clone https://github.com/opencv/opencv_contrib.git
cd opencv_contrib
git checkout 4.7.0
cd ..
git clone https://github.com/opencv/opencv.git
cd opencv
git checkout 4.7.0
mkdir build
cd build
cmake -G "Visual Studio 17 2022" -A x64 ^
-D CMAKE_INSTALL_PREFIX=YOUR_OPENCV_INSTALL_DIR ^
-D INSTALL_PYTHON_EXAMPLES=OFF ^
-D INSTALL_C_EXAMPLES=OFF ^
-D WITH_FFMPEG=ON ^
-D WITH_TBB=ON ^
-D INSTALL_PYTHON_EXAMPLES=OFF ^
-D BUILD_EXAMPLES=OFF ^
-D BUILD_DOCS=OFF ^
-D BUILD_PERF_TESTS=OFF ^
-D BUILD_TESTS=OFF ^
-D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules ..
cmake --build . --config Debug
cmake --build . --config Debug --target INSTALL
cmake --build . --config Release
cmake --build . --config Release --target INSTALL
At the end you must set environmental variable OPENCV_DIR to YOUR_OPENCV_INSTALL_DIR. You also should add %OPENCV_DIR%\x64\vc17\bin to path, but you must check x64\vc17 part, it depends on Visual Studio version and selected architecture. This directory, in path, enables dynamic linking of OpenCV. If you use other architecture Now you can delete build and cloned repositories.
To create project (in case of Visual Studio this command produce VS Solution), you should create directory build in your repository directory and use command:
mkdir build
cd build
cmake -G "Visual Studio 17 2022" -A x64 `
-D LINKAGE=SHARED `
-D 3RDPARTY_LIBRARIES="Catch2;OpenCV" `
-D 3RDPARTY_LIBRARIES_VERSIONS="3.3.1;4.7.0" `
-S .. -B .
After successful configuration you can open Biometry.sln and work with Visual Studio or use command line:
cmake --build . --config=[Release|Debug]
After successful build you can run tests:
ctest -C [Release|Debug] .
Our sample app makes classification of faces, implemented method is based on Local Binary Patterns Histograms(see Face Recognition with OpenCV) and Nearest Neighbor Classification. To run it with Georgia Tech dataset available with our repository you must run this executable like this:
.\FaceDetection.exe --dataset ..\..\..\testData\GeorgiaTechDatabaseCropped --extension .jpg --testNumber 2 --debug 1
.\FaceDetection.exe --dataset ..\..\..\testData\yalefaces --extension .png --testNumber 2 --debug 1
With above configuration we get 78 % of successful classification! For YaleFace dataset also shipped with our repo we get 90 %!
Our sample app finds base frequencies in some wav file. To run it you must use the following command line:
.\BaseFrequencyDetector.exe --input ..\..\..\testData\sound\abrakadabra --window 1024
It prints out founded base frequencies in windows of given size of samples. It use two methods, autocorrelation and fourier analysis. Window size should be number which is some power of two, because of use dfft.