代码C++， opencv实现人脸识别，人脸检测，人脸匹配，视频中的人脸检测，摄像头下的人脸检测等

代码C++， opencv实现人脸识别，人脸检测，人脸匹配，视频中的人脸检测，摄像头下的人脸检测等

2018-01-22 19:59:20 易大飞 阅读数 8291更多

分类专栏： CV 人脸对齐，人脸检测

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本文链接：https://blog.csdn.net/stf1065716904/article/details/79132793

前一段时间写了一个人脸相关的算法，包括视频中的人脸检测，相机的人脸检测，图像中人脸检测，还有人脸识别。

使用的是VS2013和opencv。

首先创建头文件common.h

 

1. #ifndef _COMMON_H

2. #define _COMMON_H

3.  

4. #include

5. #include

6. #include

7. #include

8. #include

9. #include

10. #include

11. #include

12. #include

13. #include

14. #include

15. //#include

16.  
17.  

18. static const char help[] = "face detection on image: needs image\n" \

19. "face detection on video: needs video\n" \

20. "face detection on camera: needs camera\n" \

21. "face recognition: needs images\n";

22.  

23. /*

24. 功能：判断该路径指向的是文件还是文件夹

25.  

26. 函数：isFileOrFolder

27.  

28. 文件返回： 0

29. 文件夹返回： 1

30. */

31. bool isFileOrFolder(const std::string fileName);

32.  

33. #endif

然后就是创建common.cpp文件，这里面有相关的实现。

 

 

1. #include "common.h"

2.  

3. bool isFileOrFolder(const std::string fileName)

4. {

5. const char* path = fileName.c_str();

6. struct _stat buf = { 0 };

7. _stat(path, &buf);

8. return buf.st_mode & _S_IFDIR;

9. }

然后就是视频中的人脸检测创建文件face_detection_video.h

 

 

1. #ifndef _FACE_DETETION_VIDEO_H_

2. #define _FACE_DETETION_VIDEO_H_

3.  

4. #include "common.h"

5. void face_detetion_video(const std::string videoPath, const std::string cascadeName);

6.  

7. #endif

 

接着创建对应的cpp文件，face_detection_video.cpp

 

1. #include "face_deteion_video.h"

2.  

3. void face_detetion_video(const std::string videoPath, const std::string cascadeName)

4. {

5. cv::VideoCapture cap(videoPath);

6. if (!cap.isOpened())

7. {

8. std::cout << "不能打开该视频文件！" << std::endl;

9. return;

10. }

11.  

12. double scale = 2;

13. cv::CascadeClassifier cascade;

14. cascade.load(cascadeName);

15. std::vector faces;

16.  

17. double fps = cap.get(CV_CAP_PROP_FPS); //获取帧率

18.  

19. bool isVideoRewriteFile = true; // 是否把视频重新写入文件, 默认是false：不重新写入文件

20. double dWidth = 0;

21. double dHeight = 0;

22. cv::Size frameSize;

23. cv::VideoWriter vdWr;

24. if (isVideoRewriteFile)

25. {

26. dWidth = cap.get(CV_CAP_PROP_FRAME_WIDTH);

27. dHeight = cap.get(CV_CAP_PROP_FRAME_HEIGHT);

28. frameSize = cv::Size(static_cast(dWidth), static_cast(dHeight));

29.  

30. size_t pos = videoPath.find_last_of('.');

31. std::string videoWritePath = videoPath.substr(0, pos);

32. videoWritePath = videoWritePath + "_Result.avi";

33. vdWr = cv::VideoWriter(videoWritePath, CV_FOURCC('M', 'J', 'P', 'G'), fps, frameSize, true);

34. if (!vdWr.isOpened())

35. {

36. std::cout << "不能写入视频！" << std::endl;

37. isVideoRewriteFile = false;

38. }

39. }

40.  

41. while (1)

42. {

43. cv::Mat_ frame;

44. bool bSuccess = cap.read(frame);

45. if (!bSuccess)

46. {

47. break;

48. }

49.  

50. cv::Mat smallImg(cvRound(frame.rows / scale), cvRound(frame.cols / scale), CV_8UC1); //cvRound对double型数据进行四舍五入

51. cv::resize(frame, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);

52. cvtColor(smallImg, smallImg, CV_RGB2GRAY);

53. cv::equalizeHist(smallImg, smallImg); //equalizeHist提高图像的亮度和对比度

54.  

55. cascade.detectMultiScale(smallImg, faces,

56. 1.1, 2, 0

57. /*|CV_HAAR_FIND_BIGGEST_OBJECT

58. |CV_HAAR_DO_ROUGH_SEARCH*/

59. | CV_HAAR_SCALE_IMAGE

60. ,

61. cv::Size(30, 30));

62.  

63. for (std::vector::const_iterator r = faces.begin(); r != faces.end(); r++){

64. cv::Rect rect(0, 0, 0, 0);

65.  

66. rect.x = int(r->x*scale);

67. rect.y = int(r->y*scale);

68. rect.width = int((r->width - 1)*scale);

69. rect.height = int((r->height - 1)*scale);

70.  

71. cv::rectangle(frame, rect, cv::Scalar(0, 0, 0), 3, 8);

72. }

73.  

74. //是否把检测结果写入文件

75. if (isVideoRewriteFile)

76. {

77. vdWr.write(frame);

78. }

79.  

80. cv::imshow("Video", frame);

81. cv::waitKey((int)(1000 / fps));

82.  

83. }

84.  

85. cap.release();

86. vdWr.release();

87. }

然后是图像中的寻找人脸，文件名face_detection_img.h

 

 

1. #ifndef _FACE_DETETION_IMAGE_H_

2. #define _FACE_DETETION_IMAGE_H_

3.  

4. #include "common.h"

5.  

6. void face_detetion_img(const std::string imagePath, const std::string cascadeName);

7.  
8.  
9.  

10. #endif

接着就是对应头文件face_detection_img.cpp

 

 

1. #include "face_detetion_img.h"

2.  
3.  

4. void face_detetion_img(const std::string imgPath, const std::string cascadeName)

5. {

6. //bool fileOrFolder = isFileOrFolder(imgPath);

7.  

8. std::ifstream fin;

9. fin.open(imgPath);

10.  

11. cv::CascadeClassifier cascade;

12. double scale = 1.3;

13. std::vector faces;

14. cv::Mat gray;

15.  

16. // --Detection

17. cascade.load(cascadeName);

18. std::string name;

19. while (getline(fin, name)){

20. name.erase(0, name.find_first_not_of(" \t"));

21. name.erase(name.find_last_not_of(" \t") + 1);

22.  

23. // Read Image

24. cv::Mat_ image = cv::imread(name, 0);

25. if (image.empty())

26. {

27. continue;

28. }

29.  

30. // Read Opencv Detection Bbx

31. cv::Mat smallImg(cvRound(image.rows / scale), cvRound(image.cols / scale), CV_8UC1); //cvRound对double型数据进行四舍五入

32. cv::resize(image, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);

33. cv::equalizeHist(smallImg, smallImg); //equalizeHist提高图像的亮度和对比度

34. // --Detection

35. cascade.detectMultiScale(smallImg, faces,

36. 1.1, 2, 0

37. /*|CV_HAAR_FIND_BIGGEST_OBJECT

38. |CV_HAAR_DO_ROUGH_SEARCH*/

39. | CV_HAAR_SCALE_IMAGE

40. ,

41. cv::Size(30, 30));

42. for (std::vector::const_iterator r = faces.begin(); r != faces.end(); r++){

43. cv::Rect rect(0, 0, 0, 0);

44.  

45. rect.x = int(r->x*scale);

46. rect.y = int(r->y*scale);

47. rect.width = int((r->width - 1)*scale);

48. rect.height = int((r->height - 1)*scale);

49.  

50. cv::rectangle(image, rect, cv::Scalar(0, 255, 0), 3, 8);

51. }

52.  

53. cv::imshow("test", image);

54. char s = cv::waitKey(0);

55. if ('s' == s )

56. {

57. size_t pos = name.find_last_of('.');

58. std::string filename = name.substr(0, pos);

59.  

60. filename = filename + ".bmp";

61. std::cout << filename << std::endl;

62. cv::imwrite(filename, image);

63. }

64. }

65. fin.close();

66. }

然后就是从摄像投中读取人脸信息。创建文件face_detection_camera.h

 

 

1. #ifndef _FACE_DETETION_CAMERA_H_

2. #define _FACE_DETETION_CAMERA_H_

3.  

4. #include "common.h"

5. void face_detetion_camera(const std::string cascadeName);

6.  

7. #endif

接着就是对应cpp文件，face_detection_camera.cpp

 

 

1. #include "face_detetion_camera.h"

2.  

3. void face_detetion_camera(const std::string cascadeName)

4. {

5. cv::VideoCapture cap(0);

6. if (!cap.isOpened())

7. {

8. std::cout << "不能打开该视频文件！" << std::endl;

9. return;

10. }

11.  

12. double scale = 2;

13. cv::CascadeClassifier cascade;

14. cascade.load(cascadeName);

15. std::vector faces;

16.  

17. bool isVideoRewriteFile = false; // 是否把摄像头读取的数据写入文件。

18. double dWidth = 0;

19. double dHeight = 0;

20. cv::Size frameSize;

21. cv::VideoWriter vdWr;

22. char tmp[1024] = { 0 };

23. if (isVideoRewriteFile)

24. {

25. dWidth = cap.get(CV_CAP_PROP_FRAME_WIDTH);

26. dHeight = cap.get(CV_CAP_PROP_FRAME_HEIGHT);

27. frameSize = cv::Size(static_cast(dWidth), static_cast(dHeight));

28.  

29. time_t t = time(0);

30. memset(tmp, 0, sizeof(tmp));

31. strftime(tmp, sizeof(tmp), "../camera_out_video/%Y.%m.%d-%H.%M.%S", localtime(&t));

32. std::string videoWritePath(tmp);

33. videoWritePath = videoWritePath + ".avi";

34. vdWr = cv::VideoWriter(videoWritePath, CV_FOURCC('M', 'J', 'P', 'G'), 20, frameSize, true);

35. if (!vdWr.isOpened())

36. {

37. std::cout << "不能写入视频！" << std::endl;

38. isVideoRewriteFile = false;

39. }

40. }

41.  

42. while (1)

43. {

44. cv::Mat frame;

45. bool bSuccess = cap.read(frame);

46. if (!bSuccess)

47. {

48. break;

49. }

50.  

51. cv::Mat smallImg(cvRound(frame.rows / scale), cvRound(frame.cols / scale), CV_8UC1); //cvRound对double型数据进行四舍五入

52. cv::resize(frame, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);

53. cvtColor(smallImg, smallImg, CV_RGB2GRAY);

54. cv::equalizeHist(smallImg, smallImg); //equalizeHist提高图像的亮度和对比度

55.  

56. cascade.detectMultiScale(smallImg, faces,

57. 1.1, 2, 0

58. /*|CV_HAAR_FIND_BIGGEST_OBJECT

59. |CV_HAAR_DO_ROUGH_SEARCH*/

60. | CV_HAAR_SCALE_IMAGE

61. ,

62. cv::Size(30, 30));

63.  

64. for (std::vector::const_iterator r = faces.begin(); r != faces.end(); r++){

65. cv::Rect rect(0, 0, 0, 0);

66.  

67. rect.x = int(r->x*scale);

68. rect.y = int(r->y*scale);

69. rect.width = int((r->width - 1)*scale);

70. rect.height = int((r->height - 1)*scale);

71.  

72. cv::rectangle(frame, rect, cv::Scalar(0, 0, 0), 3, 8);

73. }

74.  

75. //是否把检测结果写入文件

76. if (isVideoRewriteFile)

77. {

78. vdWr.write(frame);

79. }

80.  

81. cv::imshow("Video", frame);

82. if (27 == cv::waitKey(20)){ // 按下ESC键，结束视频

83. break;

84. }

85.  

86. }

87.  

88. cap.release();

89. vdWr.release();

90. }

最后是人脸识别的头文件：face_recognition.h

 

 

1. #ifndef _FACE_RECOGNITION_H_

2. #define _FACE_RECOGNITION_H_

3.  

4. #include "common.h"

5.  

6. void preDeal_original_img(const std::string recognitionPath, const std::string cascadeName);

7. std::vector> get_CropFace_And_ImgPathName(const std::string recognitionPath, const std::string cascadeName);

8. bool matchFace(cv::Mat detectFace, cv::Mat dbFace);

9. void face_recognition(std::string recognitionPath, const std::string cascadeName);

10.  

11. #endif

 

以及对应的cpp文件：face_recognition.cpp

1. #include "face_recognition.h"

2.  

3. void preDeal_original_img(const std::string recognitionPath, const std::string cascadeName)

4. {

5. std::ifstream fin;

6. fin.open(recognitionPath);

7. if (!fin)

8. {

9. std::cout << "Cannot open " + recognitionPath << std::endl;

10. return;

11. }

12.  

13. // --Detection

14. cv::CascadeClassifier cascade;

15. cascade.load(cascadeName);

16. if (cascade.empty())

17. {

18. std::cout << "Cascade path error!" << std::endl;

19. return;

20. }

21.  

22. double scale = 1.3;

23. std::vector faces;

24. cv::Mat gray;

25.  

26. std::string name;

27. std::string camera_face = "../camera_face/";

28. while (getline(fin, name)){

29. if (name.empty())

30. {

31. continue;

32. }

33. name.erase(0, name.find_first_not_of(" \t"));

34. name.erase(name.find_last_not_of(" \t") + 1);

35.  

36. // Read Image

37. cv::Mat img = cv::imread(name);

38. if (img.empty())

39. {

40. continue;

41. }

42.  

43. cv::Mat_ image;

44. if (img.channels() != 1)

45. {

46. cvtColor(img, image, CV_BGR2GRAY);

47. image.convertTo(image, CV_8UC1);

48. }

49. else{

50. image = img;

51. }

52.  
53.  

54. // 改变图像

55. cv::Mat smallImg(cvRound(image.rows / scale), cvRound(image.cols / scale), CV_8UC1); //cvRound对double型数据进行四舍五入

56. cv::resize(image, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);

57. cv::equalizeHist(smallImg, smallImg); //equalizeHist提高图像的亮度和对比度

58. // --Detection

59. cascade.detectMultiScale(smallImg, faces,

60. 1.1, 3, 0

61. /*|CV_HAAR_FIND_BIGGEST_OBJECT

62. |CV_HAAR_DO_ROUGH_SEARCH*/

63. | CV_HAAR_SCALE_IMAGE

64. ,

65. cv::Size(30, 30));

66. if (faces.size() > 0)

67. {

68. size_t pos = name.find_last_of('\\');

69. std::string filename = name.substr(pos + 1);

70.  

71. if (-1 == _access(camera_face.c_str(), 0))

72. {

73. _mkdir(camera_face.c_str());

74. }

75.  

76. filename = camera_face + filename;

77. std::cout << filename << std::endl;

78. cv::imwrite(filename, img);

79. }

80.  

81. }

82. fin.close();

83.  

84. //处理后的图片路径名写入Path_Image.txt中

85. std::string getImgPathTxt = "cd " + camera_face + " && dir /b/s/p/w *.jpg > Path_Images.txt";

86. system(getImgPathTxt.c_str());

87. }

88.  

89. std::vector> get_CropFace_And_ImgPathName(const std::string recognitionPath, const std::string cascadeName)

90. {

91. std::vector> cropFaceAndImgPathNames;

92. std::pair cropFaceAndImgPathName;

93.  

94. cv::CascadeClassifier cascade;

95. cascade.load(cascadeName);

96. if (cascade.empty())

97. {

98. std::cout << "Cascade path error!" << std::endl;

99. return std::vector>();

100. }

101.  

102. std::ifstream fdatabase;

103. fdatabase.open(recognitionPath);

104. if (!fdatabase)

105. {

106. std::cout << "Cannot open " + recognitionPath << std::endl;

107. return std::vector>();

108. }

109.  

110. double scale = 1.3;

111. std::vector faces;

112. cv::Mat gray;

113. std::string name;

114.  

115. std::cout << "[";

116.  

117. while (getline(fdatabase, name)){

118. if (name.empty())

119. {

120. continue;

121. }

122. name.erase(0, name.find_first_not_of(" \t"));

123. name.erase(name.find_last_not_of(" \t") + 1);

124.  

125. // Read Image

126. cv::Mat img = cv::imread(name);

127. if (img.empty())

128. {

129. continue;

130. }

131. cv::Mat image;

132. if (img.channels() != 1)

133. {

134. cvtColor(img, image, CV_BGR2GRAY);

135. image.convertTo(image, CV_8UC1);

136. }

137. else{

138. image = img;

139. }

140.  

141. // Read Opencv Detection Bbx

142. cv::Mat smallImg(cvRound(image.rows / scale), cvRound(image.cols / scale), CV_8UC1); //cvRound对double型数据进行四舍五入

143. cv::resize(image, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);

144. cv::equalizeHist(smallImg, smallImg); //equalizeHist提高图像的亮度和对比度

145. // --Detection

146. cascade.detectMultiScale(smallImg, faces,

147. 1.1, 3, 0

148. /*|CV_HAAR_FIND_BIGGEST_OBJECT

149. |CV_HAAR_DO_ROUGH_SEARCH*/

150. | CV_HAAR_SCALE_IMAGE

151. ,

152. cv::Size(30, 30));

153. for (std::vector::iterator r = faces.begin(); r != faces.end(); r++)

154. {

155. cv::Rect face;

156. face.x = int(r->x * scale);

157. face.y = int(r->y * scale);

158. face.width = int(r->width * scale);

159. face.height = int(r->height * scale);

160.  

161. // 边界检查，左边界，上边界，右边界，下边界。

162. /*face.x = face.x < 1 ? 1 : face.x;

163. face.y = face.y < 1 ? 1 : face.y;

164. face.width = (face.x + face.width) > image.cols ? (image.cols - face.x) : face.width;

165. face.height = (face.y + face.height) > image.rows ? (image.rows - face.y) : face.height;*/

166.  

167. cv::Mat cropFace;

168. cropFace = img(face);

169. /*cv::moveWindow("cropface", 960 - cropFace.cols / 2, 540 - cropFace.rows / 2);

170. cv::imshow("cropface", cropFace);

171. cv::waitKey(100);

172. cv::destroyWindow("cropface");*/

173.  

174. cropFaceAndImgPathName = make_pair(cropFace, name); //cropFaceAndImgPathName = std::pair(cropFace, name);

175.  

176. cropFaceAndImgPathNames.push_back(cropFaceAndImgPathName);

177.  

178. std::cout << '.';

179. }

180.  

181. }

182.  

183. fdatabase.close();

184.  

185. std::cout << "]" << std::endl;

186.  

187. return cropFaceAndImgPathNames;

188. }

189.  

190. bool matchFace(cv::Mat detectFace, cv::Mat dbFace)

191. {

192. IplImage* srcImg = cvCloneImage(&(IplImage)detectFace);

193. IplImage* dstImg = cvCloneImage(&(IplImage)dbFace);

194.  

195. IplImage* src;

196. IplImage* dst;

197.  

198. if (srcImg->nChannels != 1)

199. {

200. src = cvCreateImage(cvSize(srcImg->width, srcImg->height), srcImg->depth, 1);

201. cvCvtColor(srcImg, src, CV_BGR2GRAY);

202. }

203.  

204. if (dstImg->nChannels != 1)

205. {

206. dst = cvCreateImage(cvSize(dstImg->width, dstImg->height), dstImg->depth, 1);

207. cvCvtColor(dstImg, dst, CV_BGR2GRAY);

208. }

209.  

210. int histogramBins = 256;

211. float histogramRange1[2] = { 0, 255 };

212. float *histogramRange[1] = { &histogramRange1[0] };

213. CvHistogram *Histogram1 = cvCreateHist(1, &histogramBins, CV_HIST_ARRAY, histogramRange);

214. CvHistogram *Histogram2 = cvCreateHist(1, &histogramBins, CV_HIST_ARRAY, histogramRange);

215.  

216. cvCalcHist(&src, Histogram1);

217. cvCalcHist(&dst, Histogram2);

218.  

219. cvNormalizeHist(Histogram1, 1);

220. cvNormalizeHist(Histogram2, 1);

221.  
222.  

223. // CV_COMP_CHISQR,CV_COMP_BHATTACHARYYA这两种都可以用来做直方图的比较，值越小，说明图形越相似

224. //printf("CV_COMP_CHISQR : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_CHISQR));

225. //printf("CV_COMP_BHATTACHARYYA : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_BHATTACHARYYA));

226.  
227.  

228. // CV_COMP_CORREL, CV_COMP_INTERSECT这两种直方图的比较，值越大，说明图形越相似

229. //printf("CV_COMP_CORREL : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_CORREL));

230. //printf("CV_COMP_INTERSECT : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_INTERSECT));

231. double simility = cvCompareHist(Histogram1, Histogram2, CV_COMP_CHISQR);

232.  

233. if (simility > 0.5)

234. {

235. return false;

236. }

237.  

238. return true;

239. }

240.  

241. void face_recognition(std::string recognitionPath, const std::string cascadeName)

242. {

243. bool isPreDeal = false;

244. if (isPreDeal) //是否进行预处理

245. {

246. preDeal_original_img(recognitionPath, cascadeName);

247. recognitionPath = "../camera_face/";

248. }

249.  

250. //获取数据库中人脸图像

251. std::string face_Database = "../face_database/Path_Images.txt";

252. std::vector> cropFaceAndImgPathNames;

253. std::cout << "开始数据库中人脸数据的读取..." << std::endl;

254. cropFaceAndImgPathNames = get_CropFace_And_ImgPathName(face_Database, cascadeName);

255. std::cout << "结束数据库中人脸数据的读取。" << std::endl;

256.  

257. //开始人脸匹配

258. std::ifstream frecognition;

259. frecognition.open(recognitionPath);

260. if (!frecognition)

261. {

262. std::cout << "Images path Error!" << std::endl;

263. return;

264. }

265.  

266. cv::CascadeClassifier cascade;

267. cascade.load(cascadeName);

268. if (cascade.empty())

269. {

270. std::cout << "Cascade path error!" << std::endl;

271. return;

272. }

273.  

274. double scale = 1.3;

275. std::vector faces;

276. cv::Mat gray;

277. std::string name;

278.  

279. bool isExist = false; //数据库中是否存在该匹配文件

280.  

281. while (getline(frecognition, name)){

282. if (name.empty())

283. {

284. continue;

285. }

286. name.erase(0, name.find_first_not_of(" \t"));

287. name.erase(name.find_last_not_of(" \t") + 1);

288.  

289. // Read Image

290. cv::Mat img = cv::imread(name);

291. cv::Mat image;

292. if (img.channels() != 1)

293. {

294. cvtColor(img, image, CV_BGR2GRAY);

295. image.convertTo(image, CV_8UC1);

296. }

297. else{

298. image = img;

299. }

300.  

301. // Read Opencv Detection Bbx

302. cv::Mat smallImg(cvRound(image.rows / scale), cvRound(image.cols / scale), CV_8UC1); //cvRound对double型数据进行四舍五入

303. cv::resize(image, smallImg, smallImg.size(), 0, 0, cv::INTER_LINEAR);

304. cv::equalizeHist(smallImg, smallImg); //equalizeHist提高图像的亮度和对比度

305. // --Detection

306. cascade.detectMultiScale(smallImg, faces,

307. 1.1, 3, 0

308. /*|CV_HAAR_FIND_BIGGEST_OBJECT

309. |CV_HAAR_DO_ROUGH_SEARCH*/

310. | CV_HAAR_SCALE_IMAGE

311. ,

312. cv::Size(30, 30));

313. for (std::vector::iterator r = faces.begin(); r != faces.end(); r++)

314. {

315. cv::Rect face;

316. face.x = int(r->x * scale);

317. face.y = int(r->y * scale);

318. face.width = int(r->width * scale);

319. face.height = int(r->height * scale);

320.  

321. cv::Mat detectFace = img(face);

322.  

323. for (std::vector>::iterator dbFace = cropFaceAndImgPathNames.begin(); dbFace != cropFaceAndImgPathNames.end(); dbFace++)

324. {

325. std::pair dbFaceImg = *dbFace;

326. bool isMatch = matchFace(detectFace, dbFaceImg.first);

327. if (isMatch){

328. std::cout << name + " Matching " + dbFaceImg.second + " successful!" << std::endl;

329. cv::imshow("detectFace", detectFace);

330. cv::imshow("databaseFace", dbFaceImg.first);

331. cv::waitKey(200);

332. cv::destroyWindow("detectFace");

333. cv::destroyWindow("databaseFace");

334. isExist = true;

335. }

336. }

337.  

338. }

339. }

340.  

341. if (!isExist)

342. {

343. std::cout << name + " Matching failed!" << std::endl;

344. }

345.  

346. frecognition.close();

347. }

还有最后的主函数：main.cpp

1. #include "common.h"

2. #include "face_detetion_img.h"

3. #include "face_deteion_video.h"

4. #include "face_detetion_camera.h"

5. #include "face_recognition.h"

6.  
7.  

8. int main(int argc, char ** argv)

9. {

10.  

11. std::string cascadeFileName = "./../haarcascade_DataBase/haarcascade_frontalface_alt.xml";

12.  

13. //bool fileOrDir = isFileOrFolder(filePath);

14.  

15. if (argc < 2)

16. {

17. printf(help);

18. }

19. else if (strcmp(argv[1], "face_detetion_img") == 0)

20. {

21. std::string imgPath = "E:/1/ImagePath.txt";

22. face_detetion_img(imgPath, cascadeFileName);

23. }

24. else if (strcmp(argv[1], "face_detetion_video") == 0)

25. {

26. std::string videoPath = "E:\\DeepLeaning\\codes\\FindFaceInVideo\\VGGFace\\chengshd\\IMG_3170.mp4";

27. face_detetion_video(videoPath, cascadeFileName);

28. }

29. else if (strcmp(argv[1], "face_detetion_camera") == 0)

30. {

31. face_detetion_camera(cascadeFileName);

32. }

33. else if (strcmp(argv[1], "face_recognition") == 0)

34. {

35. std::string recognitionPath = "E:/camera/Path_Images.txt";

36. face_recognition(recognitionPath, cascadeFileName);

37. }

38. else

39. {

40. printf(help);

41. }

42.  

43. return 0;

44. }

如果想使用代码，适当修改一下都是可以使用的。