Dlib在VS2013上的配置方法

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Dlib官网地址：http://dlib.net/

Dlib移植到Android：http://blog.csdn.net/brightming/article/details/50595977

Dlib人脸对齐（特征点检测）：http://blog.csdn.net/sunshine_in_moon/article/details/50150435

1、解压Dlib；

E:\Dlib\dlib-19.1

E:\Dlib\dlib-19.1-debug

2、CMake；

3、VS2013+Dlib；

#include "stdafx.h"#include <iostream>#include <dlib/image_processing/frontal_face_detector.h>#include <dlib/gui_widgets.h>#include <dlib/image_io.h>#include <iostream>#include <fstream>using namespace dlib;using namespace std;// ----------------------------------------------------------------------------------------int main(int argc, char** argv){try{frontal_face_detector detector = get_frontal_face_detector();//定义一个frontal_face_detctor类的实例detector，用get_frontal_face_detector函数初始化该实例image_window win;//一个显示窗口array2d<unsigned char> img;load_image(img, "33.jpg");// 加载一张图片，从argv[i](图片路劲)加载到变量imgpyramid_up(img);//对图像进行上采用，检测更小的人脸// Now tell the face detector to give us a list of bounding boxes// around all the faces it can find in the image.//开始检测，返回一系列的边界框std::vector<rectangle> dets = detector(img);//detector（）函数检测人脸，返回一系列边界盒子cout << "Number of faces detected: " << dets.size() << endl;//dets.size 人脸数量// 在原图片上显示结果win.clear_overlay();win.set_image(img);win.add_overlay(dets, rgb_pixel(255, 0, 0));cout << "Hit enter to process the next image..." << endl;cin.get();}catch (exception& e){cout << "\nexception thrown!" << endl;cout << e.what() << endl;}}

#include "stdafx.h"#include <iostream>#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_io.h>#include <iostream>#include <fstream>using namespace dlib;using namespace std;// ----------------------------------------------------------------------------------------int main(int argc, char** argv){try{frontal_face_detector detector = get_frontal_face_detector();//定义一个frontal_face_detctor类的实例detector，用get_frontal_face_detector函数初始化该实例image_window win, win_faces;//一个显示窗口shape_predictor sp;//定义个shape_predictor类的实例  deserialize("shape_predictor_68_face_landmarks.dat") >> sp;// Loop over all the images provided on the command line.// 循环所有的图片array2d<unsigned char> img;load_image(img, "02.jpg");// 加载一张图片，从argv[i](图片路劲)加载到变量imgpyramid_up(img);//对图像进行上采用，检测更小的人脸// Now tell the face detector to give us a list of bounding boxes  // around all the faces in the image.  std::vector<rectangle> dets = detector(img);//检测人脸，获得边界框  cout << "Number of faces detected: " << dets.size() << endl;//检测到人脸的数量  // Now we will go ask the shape_predictor to tell us the pose of  // each face we detected.  //****调用shape_predictor类函数，返回每张人脸的姿势  std::vector<full_object_detection> shapes;//注意形状变量的类型，full_object_detection  for (unsigned long j = 0; j < dets.size(); ++j){full_object_detection shape = sp(img, dets[j]);//预测姿势，注意输入是两个，一个是图片，另一个是从该图片检测到的边界框  cout << "number of parts: " << shape.num_parts() << endl;//cout << "pixel position of first part:  " << shape.part(0) << endl;//获得第一个点的坐标,注意第一个点是从0开始的  //cout << "pixel position of second part: " << shape.part(1) << endl;//获得第二个点的坐标  /*自己改写，打印出全部68个点*/for (int i = 1; i < 69; i++){cout << "第 " << i << " 个点的坐标： " << shape.part(i - 1) << endl;}// You get the idea, you can get all the face part locations if  // you want them.  Here we just store them in shapes so we can  // put them on the screen.  shapes.push_back(shape);}// Now let's view our face poses on the screen.  //**** 显示结果  win.clear_overlay();win.set_image(img);win.add_overlay(render_face_detections(shapes));// We can also extract copies of each face that are cropped, rotated upright,  // and scaled to a standard size as shown here:  //****我们也能提取每张剪裁后的人脸的副本，旋转和缩放到一个标准尺寸  dlib::array<array2d<rgb_pixel> > face_chips;extract_image_chips(img, get_face_chip_details(shapes), face_chips);win_faces.set_image(tile_images(face_chips));cout << "Hit enter to process the next image..." << endl;cin.get();}catch (exception& e){cout << "\nexception thrown!" << endl;cout << e.what() << endl;}}

#include "stdafx.h"#include <iostream>#include <opencv2/opencv.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_io.h>#include <iostream>#include <fstream>using namespace dlib;using namespace std;using namespace cv;// ----------------------------------------------------------------------------------------int main(int argc, char** argv){char img_file[] = "02.jpg";char landmark_file[] = "shape_predictor_68_face_landmarks.dat";//  Mat img = imread(img_file);//  frontal_face_detector detector = get_frontal_face_detector();shape_predictor sp;deserialize(landmark_file) >> sp;array2d<rgb_pixel> arrImg;load_image(arrImg, img_file);std::vector<dlib::rectangle> dets = detector(arrImg);for (unsigned long j = 0; j < dets.size(); ++j){full_object_detection shape = sp(arrImg, dets[j]);for (unsigned long i = 0; i<shape.num_parts(); i++){point pt = shape.part(i);int x = pt.x();int y = pt.y();line(img, Point(pt.x(), pt.y()), Point(pt.x(), pt.y()), Scalar(0, 0, 255), 2);}}//  imshow("img", img);waitKey();return 0;}

Dlib使用OpenCV的Mat格式

#include "stdafx.h"#include <iostream>#include <opencv2/opencv.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_io.h>#include <dlib/opencv.h>#include <iostream>#include <fstream>using namespace dlib;using namespace std;using namespace cv;// ----------------------------------------------------------------------------------------int main(int argc, char** argv){try{char img_file[] = "02.jpg";char landmark_file[] = "shape_predictor_68_face_landmarks.dat";//  //Mat img = imread(img_file);namedWindow("img", 1);Mat img;VideoCapture cap("Duan2.mp4");int totalFrameNumber = cap.get(CV_CAP_PROP_FRAME_COUNT);cap >> img;int w = img.cols;int h = img.rows;cout << w << ", " << h << endl;//  frontal_face_detector detector = get_frontal_face_detector();shape_predictor sp;deserialize(landmark_file) >> sp;for (int nFrmNum = 0; nFrmNum < totalFrameNumber; nFrmNum++) {// get frame from the videocap >> img;cout << nFrmNum << " =======================" << endl;if (!img.empty()){cv_image<bgr_pixel> cimg(img);// Detect faces std::vector<dlib::rectangle> dets = detector(cimg);for (unsigned long j = 0; j < dets.size(); ++j){full_object_detection shape = sp(cimg, dets[j]);for (unsigned long i = 0; i < shape.num_parts(); i++){point pt = shape.part(i);int x = pt.x();int y = pt.y();line(img, Point(pt.x(), pt.y()), Point(pt.x(), pt.y()), Scalar(0, 0, 255), 2);char ptr[20];sprintf(ptr, "%d", i);putText(img, ptr, Point(pt.x(), pt.y()), 1, 1.0, Scalar(0, 0, 255));}}imshow("img", img);waitKey(1);}}}catch (exception& e){cout << e.what() << endl;}waitKey();return 0;}