/face-detection-opencv-cpp

Face Detection using OpenCV C++ on Ubuntu

Primary LanguageC++

Face Detection OpenCV C++

Instalation

Install OpenCV

On Ubuntu can use this tutorial from OpenCV Documentation

  1. Install minimal preruquisites On terminal sudo apt update && sudo apt install -y cmake g++ wget unzip

  2. Download and package the sources

wget -O opencv.zip https://github.com/opencv/opencv/archive/master.zip
wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/master.zip
unzip opencv.zip
unzip opencv_contrib.zip

  1. Create new directory for build file and switch current directory on it mkdir -p build && cd build

  2. Configure or generate build scripts for the preferred build system using cmake cmake -DOPENCV_EXTRA_MODULES_PATH=../opencv_contrib-master/modules ../opencv-master

  3. Build it cmake --build

  4. Build or run compilation process make -j4

  5. Check build results ls bin ls lib

  6. Install sudo make install

By default OpenCV will be installed to the /usr/local directory, all files will be copied to following locations:

/usr/local/bin - executable files
/usr/local/lib - libraries (.so)
/usr/local/cmake/opencv4 - cmake package
/usr/local/include/opencv4 - headers
/usr/local/share/opencv4 - other files (e.g. trained cascades in XML format)

How to use

Use the face detection file

  1. If using vscode, rename vscode file as .vscode as hidden folder and can be detected by vscode. This is vscode setting for build, compiler, and include folder

  2. Launch vscode with cpp file, try to launch from terminal in current directory with code . to launch vscode from contain folder

  3. Run make on terminal with current directory of face-recognition.cpp file and MakeFile

    • Run fr-cpp object file for the result of face-recognition.cpp with ./fr-cpp on terminal

    • if not using MakeFile, you can compile from terminal Ubuntu after setting current directory with this code

g++ tutorial-cascade-classifier.cpp -o tcc.out `pkg-config --cflags --libs opencv4`.

  1. after done use the face recognition, push ESC button to stop capture on the window frame