time:11/12/2016 U.S Pacific time By: Cypress McCarthy
In this article, I will show you guys how to install Dlib (C++ library) on your PC, using QT and MingW compiler. Before start, you should download Dlib, Qt, cmake and MingW( Qt has already been included).
Your may know this before you install Dlib on your PC. Dlib is a C++ library, containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge(from Dlib.net).
Such many features it has: Documents，High Quality Portable Code，Machine Learning Algorithms，Image Processing...
There are few of materials to us how to install Dlib on your PC with Qt and MingW instead of Visual Studio(what a big software, ha), even though the Dlib.net provides an article: How to compile.
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decomposition the Dlib file
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**using cmake **
1th: Browse the source file and mkdir a build file
2th:press Configure button, choose the MinGW Makefiles.
3th:
4th:click Generate button
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mingw32-make
waiting...
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Qt create a new project
the file of .pro should looks like that: (It also should include opencv library for what the demo is needed)
QT += core QT -= gui CONFIG += c++11 TARGET = FaceL_LandMark CONFIG += console CONFIG -= app_bundle TEMPLATE = app SOURCES += main.cpp \ INCLUDEPATH +=D:\opencv2.4.13\build\install\include LIBS +=-L"D:\opencv2.4.13\build\install\x86\mingw\bin" LIBS += -lopencv_core2413 -lopencv_highgui2413 -lopencv_imgproc2413 QMAKE_CXXFLAGS_RELEASE += -mavx //NOTE it can speed the Dlib!! INCLUDEPATH+=E:\dlib-19.2\dlib LIBS +=-L"E:\dlib-19.2\build" LIBS+=-ldlib LIBS += -lmingw32 LIBS+=-lOle32 LIBS+=-lOleaut32 LIBS+=-lm LIBS+= -ldinput8 LIBS+=-lcomctl32 LIBS+=-ldxguid LIBS+= -ldxerr8 LIBS+=-luser32 LIBS+=-lgdi32 LIBS+=-lwinmm LIBS+= -limm32 LIBS+= -lole32 LIBS+=-loleaut32 LIBS+=-lshell32 LIBS+= -lversion LIBS+= -luuid LIBS+=-lglut32 LIBS+=-lopengl32 LIBS+=-lglu32 LIBS+=-lgdi32 LIBS+=-lwinmm LIBS += -lws2_32
DEMO;
#include <QCoreApplication>
#include <dlib/opencv.h>
#include <opencv2/highgui/highgui.hpp>
#include <dlib/image_processing/frontal_face_detector.h>
#include <dlib/image_processing/render_face_detections.h>
#include <dlib/image_processing.h>
#include <dlib/gui_widgets.h>
#include <dlib/image_processing/frontal_face_detector.h>
#include <dlib/gui_widgets.h>
#include <dlib/image_io.h>
#include <iostream>
#include<opencv2/opencv.hpp>
#include<opencv2/opencv_modules.hpp>
#define FACE_DOWNSAMPLE_RATIO 4
#define SKIP_FRAMES 2
#define DLIB_PNG_SUPPORT
#define DLIB_JPEG_SUPPORT
using namespace cv;
using namespace std;
using namespace dlib;
int main(int argc, char** argv)
{
QCoreApplication a(argc, argv);
try
{
cv::VideoCapture cap(1); //**NOTE: if you have one camera,(0) instad of (1)**
//i have two camera,(1) is the front one.
if (!cap.isOpened())
{
cerr << "Unable to connect to camera" << endl;
return 1;
}
image_window win;
// Load face detection and pose estimation models.
frontal_face_detector detector = get_frontal_face_detector();
shape_predictor pose_model;
deserialize("shape_predictor_68_face_landmarks.dat") >> pose_model;
// Grab and process frames until the main window is closed by the user.
while(!win.is_closed())
{
// Grab a frame
cv::Mat temp;
cap >> temp;
// Turn OpenCV's Mat into something dlib can deal with. Note that this just
// wraps the Mat object, it doesn't copy anything. So cimg is only valid as
// long as temp is valid. Also don't do anything to temp that would cause it
// to reallocate the memory which stores the image as that will make cimg
// contain dangling pointers. This basically means you shouldn't modify temp
// while using cimg.
cv_image<bgr_pixel> cimg(temp);
// Detect faces
std::vector<dlib::rectangle> faces = detector(cimg);
// Find the pose of each face.
std::vector<full_object_detection> shapes;
for (unsigned long i = 0; i < faces.size(); ++i)
shapes.push_back(pose_model(cimg, faces[i]));
// Display it all on the screen
win.clear_overlay();
win.set_image(cimg);
win.add_overlay(render_face_detections(shapes));
}
}
catch(serialization_error& e)
{
cout << "You need dlib's default face landmarking model file to run this example." << endl;
cout << "You can get it from the following URL: " << endl;
cout << " http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2" << endl;
cout << endl << e.what() << endl;
}
catch(exception& e)
{
cout << e.what() << endl;
}
}
NOTE:using release instead of debug model can accelerate the detection speed
You should download it from the following URL: //http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2 as the detector .
Go to the release file,
projestname.exe shape_predictor_68_face_landmarks.dat
that's it!