C++ dlib实现人脸识别-精品文档资料整理.docx

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1、C+ dlib实现人脸识别void line_one_face_detections(cv:Mat img, std:vector dlib:full_object_detection fs) int i, j; for(j j fs.size(); j ) cv:Point p1, p2; for(i i i ) / 下巴到脸颊 0 16 /左边眉毛 17 21 /右边眉毛 21 26 /鼻梁 27 30 /鼻孔 31 35 /左眼 36 41 /右眼 42 47 /嘴唇外圈 48 59 /嘴唇内圈 59 67 switch(i) case 16: case 21: case 26: cas

2、e 30: case 35: case 41: case 47: case 59: break; default: break; p1.x fsj.part(i).x(); p1.y fsj.part(i).y(); p2.x fsj.part(i 1).x(); p2.y fsj.part(i 1).y(); cv:line(img, p1, p2, cv:Scalar(0,0,255), 1); 使用方式 在build建立faces文件夹 放入人名图像。 CMakeLists.txt 同理修改 会报错。 修改CMakeLists.txt 解决。 #链接库TARGET_LINK_LIBRAR

3、IES(dlib_detector2 dlib $OpenCV_LIBS -lpthread) 三、视频人脸识别并保存 image3.cpp #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

4、dlib/dnn.h #include dlib/data_io.h #include dlib/clustering.h #include dlib/string.h #include opencv2/highgui/highgui.hpp #include opencv2/core/core.hpp #include opencv2/opencv.hpp #include opencv2/imgproc/imgproc.hpp #include iostream #include vector #include ctime #include string #include map #inc

5、lude sstream #ifdef _cplusplus extern C #endif #include stdlib.h #include string.h #include unistd.h #include dirent.h #ifdef _cplusplus #endif /由于dlib以及opencv中有相当一局部类同名 故不能同时对它们使用using namespace 否那么会出现一些莫名其妙的问题 /且dlib库以及标准std库中的类发生冲突 如map,string 类等等 using namespace std; using namespace cv; /using n

6、amespace dlib; void getFiles(std:string path, std:map std:string, std:string files); void line_one_face_detections(cv:Mat img, std:vector dlib:full_object_detection fs); /定义好一堆模板别名 以供后续方便使用 template template int,template typename class,int,typename class block, int N, template typename class BN, typ

7、ename SUBNET using residual dlib:add_prev1 block N,BN,1,dlib:tag1 SUBNET template template int,template typename class,int,typename class block, int N, template typename class BN, typename SUBNET using residual_down dlib:add_prev2 dlib:avg_pool 2,2,2,2,dlib:skip1 dlib:tag2 block N,BN,2,dlib:tag1 SUB

8、NET ; template int N, template typename class BN, int stride, typename SUBNET using block BN dlib:con N,3,3,1,1,dlib:relu BN dlib:con N,3,3,stride,stride,SUBNET template int N, typename SUBNET using ares dlib:relu residual block,N,dlib:affine,SUBNET ; template int N, typename SUBNET using ares_down

9、dlib:relu residual_down block,N,dlib:affine,SUBNET ; template typename SUBNET using alevel0 ares_down 256,SUBNET template typename SUBNET using alevel1 ares 256,ares 256,ares_down 256,SUBNET template typename SUBNET using alevel2 ares 128,ares 128,ares_down 128,SUBNET template typename SUBNET using

10、alevel3 ares 64,ares 64,ares 64,ares_down 64,SUBNET ; template typename SUBNET using alevel4 ares 32,ares 32,ares 32,SUBNET using anet_type dlib:loss_metric dlib:fc_no_bias 128,dlib:avg_pool_everything alevel0 alevel1 alevel2 alevel3 alevel4 dlib:max_pool 3,3,2,2,dlib:relu dlib:affine dlib:con 32,7,

11、7,2,2, dlib:input_rgb_image_sized 150 ; /* 识别视频中的某一帧图像中是不是有库里的某个人 方法 统计出库文件夹中所有人的图片的face_descriptors 然后计算出当前图片中的人脸face_descriptors 二者之间间隔 小于0.6那么视为同一个人 ./t11 hls_faces huanlesong.mp4 */ int main(int argc, char *argv) time_t start_t, end_t; if(argc ! 3) std:cout you should specified a dir and a video

12、 stream! std:endl; return 0; time( start_t); std:map string, string files; getFiles(argv1, files); if(files.empty() std:cout No pic files found in argv1 std:endl; return 0; /加载训练好的级联分类器 利用haar级联分类器快速找出人脸区域 然后交给dlib检测人脸部位 cv:CascadeClassifier faceDetector( haarcascade_frontalface_alt2.xml /cv:Cascade

13、Classifier faceDetector( ./output/cascade.xml if(faceDetector.empty() std:cout face detector is empty! std:endl; return 0; /加载人脸形状探测器 dlib:shape_predictor sp; dlib:deserialize( ./shape_predictor_68_face_landmarks.dat ) sp; /加载负责人脸识别的DNN anet_type net; dlib:deserialize( dlib_face_recognition_resnet_m

14、odel_v1.dat ) net; /人脸描绘符库, face_descriptor - name map dlib:matrix float,0,1 , string fdlib; for(map string, string :iterator it files.begin(); it ! files.end(); it ) std:cout filename: it- second filepath: it- first std:endl; cv:Mat frame cv:imread(it- first); cv:Mat src; cv:cvtColor(frame, src, CV

15、_BGR2GRAY); dlib:array2d dlib:bgr_pixel dimg; dlib:assign_image(dimg, dlib:cv_image uchar (src); /haar级联分类器探测人脸区域 获取一系列人脸所在区域 std:vector cv:Rect objects; std:vector dlib:rectangle dets; faceDetector.detectMultiScale(src, objects); for (int i i objects.size(); i ) /cv:rectangle(frame, objectsi, CV_RG

16、B(200,0,0); dlib:rectangle r(objectsi.x, objectsi.y, objectsi.x objectsi.width, objectsi.y objectsi.height); dets.push_back(r); /正常情况下应该只检测到一副面容 if (dets.size() 0) continue; std:vector dlib:matrix dlib:rgb_pixel faces; std:vector dlib:full_object_detection shapes; for(int i i dets.size(); i ) dlib:f

17、ull_object_detection shape sp(dimg, detsi); /获取指定一个区域的人脸形状 shapes.push_back(shape); dlib:matrix dlib:rgb_pixel face_chip; dlib:extract_image_chip(dimg, dlib:get_face_chip_details(shape,150,0.25), face_chip); faces.push_back(move(face_chip); if (faces.size() 0) cout No faces found in it- second endl;

18、 continue; std:vector dlib:matrix float,0,1 face_descriptors net(faces); for(std:vector dlib:matrix float,0,1 :iterator iter face_descriptors.begin(); iter ! face_descriptors.end(); iter ) fdlib.insert(pair dlib:matrix float,0,1 , string (*iter, it- second); time( end_t); std:cout ok, all pic in lib

19、 had been keep on. use time: end_t - start_t s std:endl; /加载视频 VideoCapture capture(argv2); int frames capture.get(CAP_PROP_FRAME_COUNT);/获取视频针数目(一帧就是一张图片) double fps capture.get(CAP_PROP_FPS);/获取每针视频的频率 / 获取帧的视频宽度 视频高度 Size size Size(capture.get(CAP_PROP_FRAME_WIDTH), capture.get(CAP_PROP_FRAME_HEI

20、GHT); cout frames endl; cout fps endl; cout size endl; /创立写入对象,需要指定 帧率以及视频宽高 VideoWriter writer; /指定保存文件位置 编码器 帧率 宽高 writer.open( test.avi , VideoWriter:fourcc( M , J , P , G ), fps, size); /VideoWriter writer( VideoTest.avi ,CV_FOURCC( M , J , P , G ), 20.0,Size(480, 848); while(true) /加载待检测的图片 cv:

21、Mat frame; capture frame; if (frame.empty() break; cv:Mat src; cv:cvtColor(frame, src, CV_BGR2GRAY); dlib:array2d dlib:bgr_pixel dimg; dlib:assign_image(dimg, dlib:cv_image uchar (src); /haar级联分类器探测人脸区域 获取一系列人脸所在区域 std:vector cv:Rect objects; std:vector dlib:rectangle dets; faceDetector.detectMultiS

22、cale(src, objects); for (int i i objects.size(); i ) cv:rectangle(frame, objectsi, CV_RGB(200,0,0); dlib:rectangle r(objectsi.x, objectsi.y, objectsi.x objectsi.width, objectsi.y objectsi.height); dets.push_back(r); /正常情况下应该只检测到一副面容 if (dets.size() 0) continue; std:vector dlib:matrix dlib:rgb_pixel

23、faces; std:vector dlib:full_object_detection shapes; for(int i i dets.size(); i ) dlib:full_object_detection shape sp(dimg, detsi); /获取指定一个区域的人脸形状 shapes.push_back(shape); dlib:matrix dlib:rgb_pixel face_chip; dlib:extract_image_chip(dimg, dlib:get_face_chip_details(shape,150,0.25), face_chip); face

24、s.push_back(move(face_chip); if (faces.size() 0) continue; line_one_face_detections(frame, shapes); std:vector dlib:matrix float,0,1 face_descriptors net(faces); /遍历库 查找相似图像 float min_distance 0.7; std:string similar_name unknown for(map dlib:matrix float,0,1 , string :iterator it fdlib.begin(); it

25、! fdlib.end(); it ) float distance length(it- first - face_descriptors0); if( distance 0.5 ) /应该计算一个最近值 if( distance min_distance) min_distance distance; similar_name it- second; if(min_distance 0.5) float similarity (0.5 - min_distance) * 100 / 0.5; stringstream strStream; strStream similar_name ,

26、similarity % endl; string s strStream.str(); cv:Point org(objects0.x, objects0.y); cv:putText(frame, s, org, cv:FONT_HERSHEY_SIMPLEX, 1.0, CV_RGB(0, 200, 0); cv:imshow( frame , frame); writer frame; /等待10ms 假如从键盘输入的是q、Q、或是Esc键 那么退出 int key cv:waitKey(5); if (key q | key Q | key 27) break; return 0;

27、void getFiles(string path, map string, string files) DIR *dir; struct dirent *ptr; char base1000; if(pathpath.length()-1 ! / ) path path / if(dir opendir(path.c_str() NULL) cout open the dir: path error! endl; return; while(ptr readdir(dir) ! NULL ) /current dir OR parrent dir if(strcmp(ptr- d_name,

28、 . ) 0 | strcmp(ptr- d_name, . ) 0) continue; else if(ptr- d_type 8) /file string fn(ptr- d_name); string name; name fn.substr(0, fn.find_last_of( . string p path string(ptr- d_name); files.insert(pair string, string (p, name); else if(ptr- d_type 10) /link file else if(ptr- d_type 4) /dir closedir(

29、dir); return ; void line_one_face_detections(cv:Mat img, std:vector dlib:full_object_detection fs) int i, j; for(j j fs.size(); j ) cv:Point p1, p2; for(i i i ) / 下巴到脸颊 0 16 /左边眉毛 17 21 /右边眉毛 21 26 /鼻梁 27 30 /鼻孔 31 35 /左眼 36 41 /右眼 42 47 /嘴唇外圈 48 59 /嘴唇内圈 59 67 switch(i) case 16: case 21: case 26: case 30: case 35: case 41: case 47: case 59: i break; default: break; p1.x fsj.part(i).x(); p1.y fsj.part(i).y(); p2.x fsj.part(i 1).x(); p2.y fsj.part(i 1).y(); cv:line(img, p1, p2, cv:Scalar(0,0,255), 1); 参考